diff --git a/.circleci/config.yml b/.circleci/config.yml
new file mode 100644
index 0000000..eee5c10
--- /dev/null
+++ b/.circleci/config.yml
@@ -0,0 +1,50 @@
+# This config was automatically generated from your source code
+# Stacks detected: cicd:github-actions:.github/workflows,deps:python:.,package_manager:poetry:.,test:tox:.
+version: 2.1
+orbs:
+  python: circleci/python@2
+jobs:
+  test-python:
+    # Install dependencies and run tests
+    docker:
+      - image: cimg/python:3.10-node
+    steps:
+      - checkout
+      - python/install-packages:
+          pkg-manager: poetry
+      - run:
+          name: Check
+          command: poetry run tox -e check -v
+      - run:
+          name: docs
+          command: poetry run tox -e docs -v
+      - run:
+          name: flake8
+          command: poetry run tox -e flake8 -v
+      - run:
+          name: tests
+          command: poetry run pytest
+      - run:
+          name: coverage
+          command: poetry run tox -e report -v
+      - store_test_results:
+          path: junit.xml
+  deploy:
+    # This is an example deploy job, not actually used by the workflow
+    docker:
+      - image: cimg/base:stable
+    steps:
+      # Replace this with steps to deploy to users
+      - run:
+          name: deploy
+          command: '#e.g. ./deploy.sh'
+      - run:
+          name: found github actions config
+          command: ':'
+workflows:
+  build-and-test:
+    jobs:
+      - test-python
+    # - deploy:
+    #     requires:
+    #       - test-python
diff --git a/README.rst b/README.rst
index 350a2af..6ecde2a 100644
--- a/README.rst
+++ b/README.rst
@@ -13,7 +13,7 @@ Overview
     * - docs
       - |docs|
     * - tests, CI & coverage
-      - |github-actions| |codecov| |codacy|
+      - |github-actions| |circleci| |codecov| |codacy|
     * - codeclimate
       - |codeclimate-maintainability| |codeclimate-testcoverage|
     * - version
@@ -31,6 +31,10 @@ Overview
     :alt: GitHub Actions Build Status
     :target: https://github.com/GalKepler/keprep/actions
 
+.. |circleci| image:: https://dl.circleci.com/status-badge/img/circleci/J6A3JWLZsHZMCMZ1aCKdXb/AVFefVDaX15sp62PZ8MpA9/tree/main.svg?style=svg
+    :alt: CircleCI Build Status
+    :target: https://dl.circleci.com/status-badge/redirect/circleci/J6A3JWLZsHZMCMZ1aCKdXb/AVFefVDaX15sp62PZ8MpA9/tree/main
+
 .. |codecov| image:: https://codecov.io/github/GalKepler/keprep/graph/badge.svg?token=LO5CH471O4
     :alt: Coverage Status
     :target: https://app.codecov.io/github/GalKepler/keprep
diff --git a/poetry.lock b/poetry.lock
index cbbdca2..8ea7086 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -1,5 +1,19 @@
 # This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand.
 
+[[package]]
+name = "acres"
+version = "0.1.0"
+description = "Access resources on your terms"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "acres-0.1.0-py3-none-any.whl", hash = "sha256:7bbb3744de84d1499e5cc00f02d10f7e85c880e343722871816ca41502d4d103"},
+    {file = "acres-0.1.0.tar.gz", hash = "sha256:4765479683389849368947da9e5319e677e7323ed858d642f9736ad1c070f45b"},
+]
+
+[package.dependencies]
+importlib_resources = {version = "*", markers = "python_version < \"3.11\""}
+
 [[package]]
 name = "appnope"
 version = "0.1.4"
@@ -42,63 +56,89 @@ test = ["astroid (>=1,<2)", "astroid (>=2,<4)", "pytest"]
 
 [[package]]
 name = "attrs"
-version = "23.2.0"
+version = "24.2.0"
 description = "Classes Without Boilerplate"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "attrs-23.2.0-py3-none-any.whl", hash = "sha256:99b87a485a5820b23b879f04c2305b44b951b502fd64be915879d77a7e8fc6f1"},
-    {file = "attrs-23.2.0.tar.gz", hash = "sha256:935dc3b529c262f6cf76e50877d35a4bd3c1de194fd41f47a2b7ae8f19971f30"},
+    {file = "attrs-24.2.0-py3-none-any.whl", hash = "sha256:81921eb96de3191c8258c199618104dd27ac608d9366f5e35d011eae1867ede2"},
+    {file = "attrs-24.2.0.tar.gz", hash = "sha256:5cfb1b9148b5b086569baec03f20d7b6bf3bcacc9a42bebf87ffaaca362f6346"},
 ]
 
 [package.extras]
-cov = ["attrs[tests]", "coverage[toml] (>=5.3)"]
-dev = ["attrs[tests]", "pre-commit"]
-docs = ["furo", "myst-parser", "sphinx", "sphinx-notfound-page", "sphinxcontrib-towncrier", "towncrier", "zope-interface"]
-tests = ["attrs[tests-no-zope]", "zope-interface"]
-tests-mypy = ["mypy (>=1.6)", "pytest-mypy-plugins"]
-tests-no-zope = ["attrs[tests-mypy]", "cloudpickle", "hypothesis", "pympler", "pytest (>=4.3.0)", "pytest-xdist[psutil]"]
+benchmark = ["cloudpickle", "hypothesis", "mypy (>=1.11.1)", "pympler", "pytest (>=4.3.0)", "pytest-codspeed", "pytest-mypy-plugins", "pytest-xdist[psutil]"]
+cov = ["cloudpickle", "coverage[toml] (>=5.3)", "hypothesis", "mypy (>=1.11.1)", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins", "pytest-xdist[psutil]"]
+dev = ["cloudpickle", "hypothesis", "mypy (>=1.11.1)", "pre-commit", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins", "pytest-xdist[psutil]"]
+docs = ["cogapp", "furo", "myst-parser", "sphinx", "sphinx-notfound-page", "sphinxcontrib-towncrier", "towncrier (<24.7)"]
+tests = ["cloudpickle", "hypothesis", "mypy (>=1.11.1)", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins", "pytest-xdist[psutil]"]
+tests-mypy = ["mypy (>=1.11.1)", "pytest-mypy-plugins"]
 
 [[package]]
 name = "bids-validator"
-version = "1.14.6"
+version = "1.14.7.post0"
 description = "Validator for the Brain Imaging Data Structure"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "bids_validator-1.14.6-py3-none-any.whl", hash = "sha256:e7194193d97bedc6fb173b8606f6d3ed5a467c141f01bca11cd0f38ad1717941"},
-    {file = "bids_validator-1.14.6.tar.gz", hash = "sha256:df2b6b5d1aaad61d34ccad0494f2ed73ce3082825ada31954c4e14c2538d485c"},
+    {file = "bids_validator-1.14.7.post0-py3-none-any.whl", hash = "sha256:a1ee196eae8e5cf3b3fe9fd1985e03997e3e21a40ea3bcb494ff1e0dcec86a89"},
+    {file = "bids_validator-1.14.7.post0.tar.gz", hash = "sha256:e6005a500b75f8a961593fb67d46085107dadb116f59a5c3b524aa0697945b66"},
+]
+
+[package.dependencies]
+bidsschematools = ">=0.10"
+
+[[package]]
+name = "bidsschematools"
+version = "0.10.0"
+description = "Python tools for working with the BIDS schema."
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "bidsschematools-0.10.0-py3-none-any.whl", hash = "sha256:1165b1d3b1a19a38c73752c5cd6be7d439a0abbcaf417dbf7ef4ac1cf9308975"},
+    {file = "bidsschematools-0.10.0.tar.gz", hash = "sha256:689fd368b38703451efd76b7b95f1bce1c4c6392da851954078fc045a6679b1e"},
 ]
 
+[package.dependencies]
+click = "*"
+jsonschema = "*"
+pyyaml = "*"
+
+[package.extras]
+all = ["codecov", "coverage[toml]", "flake8", "flake8-black", "flake8-isort", "markdown-it-py", "pandas", "pyparsing", "pytest", "pytest-cov", "sphinx (>=1.5.3)", "sphinx-rtd-theme", "tabulate"]
+doc = ["sphinx (>=1.5.3)", "sphinx-rtd-theme"]
+expressions = ["pyparsing"]
+render = ["markdown-it-py", "pandas", "tabulate"]
+tests = ["codecov", "coverage[toml]", "flake8", "flake8-black", "flake8-isort", "pytest", "pytest-cov"]
+
 [[package]]
 name = "black"
-version = "24.4.2"
+version = "24.8.0"
 description = "The uncompromising code formatter."
 optional = false
 python-versions = ">=3.8"
 files = [
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+    {file = "black-24.8.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:9e84e33b37be070ba135176c123ae52a51f82306def9f7d063ee302ecab2cf47"},
+    {file = "black-24.8.0-cp39-cp39-win_amd64.whl", hash = "sha256:73bbf84ed136e45d451a260c6b73ed674652f90a2b3211d6a35e78054563a9bb"},
+    {file = "black-24.8.0-py3-none-any.whl", hash = "sha256:972085c618ee94f402da1af548a4f218c754ea7e5dc70acb168bfaca4c2542ed"},
+    {file = "black-24.8.0.tar.gz", hash = "sha256:2500945420b6784c38b9ee885af039f5e7471ef284ab03fa35ecdde4688cd83f"},
 ]
 
 [package.dependencies]
@@ -140,63 +180,78 @@ files = [
 
 [[package]]
 name = "cffi"
-version = "1.16.0"
+version = "1.17.0"
 description = "Foreign Function Interface for Python calling C code."
 optional = false
 python-versions = ">=3.8"
 files = [
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 [package.dependencies]
@@ -446,63 +501,83 @@ test-no-images = ["pytest", "pytest-cov", "pytest-xdist", "wurlitzer"]
 
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 [[package]]
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+description = "Deep Difference and Search of any Python object/data. Recreate objects by adding adding deltas to each other."
+optional = false
+python-versions = ">=3.8"
+files = [
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+]
+
+[package.dependencies]
+ordered-set = ">=4.1.0,<4.2.0"
+
+[package.extras]
+cli = ["click (==8.1.7)", "pyyaml (==6.0.1)"]
+optimize = ["orjson"]
+
+[[package]]
+name = "dipy"
+version = "1.9.0"
+description = "Diffusion MRI Imaging in Python"
+optional = false
+python-versions = ">=3.9"
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+
+[package.dependencies]
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+nibabel = ">=3.0.0"
+numpy = ">=1.22.4"
+packaging = ">=21"
+scipy = ">=1.8"
+tqdm = ">=4.30.0"
+trx-python = ">=0.2.9"
+
+[package.extras]
+all = ["dipy[dev,doc,extra,ml,style,test,viz]"]
+dev = ["Cython (>=0.29.35)", "build", "meson-python (>=0.13)", "ninja", "numpy (>=1.22)", "packaging (>=21)", "setuptools (>=67)", "spin (>=0.5)", "wheel"]
+doc = ["Jinja2", "grg-sphinx-theme (>=0.2.0)", "numpydoc", "sphinx (>=5.3,<6.0)", "sphinx-gallery (>=0.10.0)", "sphinx_design", "sphinxcontrib-bibtex", "texext", "tomli", "tomli (>=2.0.1)"]
+extra = ["boto3", "cvxpy", "dipy[ml,viz]", "scikit-image"]
+ml = ["pandas", "scikit_learn", "statsmodels (>=0.14.0)", "tables", "tensorflow"]
+style = ["flake8", "isort"]
+test = ["asv", "codecov", "coverage", "coveralls", "pytest"]
+viz = ["fury (>=0.10.0)", "matplotlib"]
+
 [[package]]
 name = "distlib"
 version = "0.3.8"
@@ -681,13 +831,13 @@ typing = ["typing-extensions (>=4.8)"]
 
 [[package]]
 name = "flake8"
-version = "7.1.0"
+version = "7.1.1"
 description = "the modular source code checker: pep8 pyflakes and co"
 optional = false
 python-versions = ">=3.8.1"
 files = [
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+    {file = "flake8-7.1.1.tar.gz", hash = "sha256:049d058491e228e03e67b390f311bbf88fce2dbaa8fa673e7aea87b7198b8d38"},
 ]
 
 [package.dependencies]
@@ -695,6 +845,23 @@ mccabe = ">=0.7.0,<0.8.0"
 pycodestyle = ">=2.12.0,<2.13.0"
 pyflakes = ">=3.2.0,<3.3.0"
 
+[[package]]
+name = "flake8-pyproject"
+version = "1.2.3"
+description = "Flake8 plug-in loading the configuration from pyproject.toml"
+optional = false
+python-versions = ">= 3.6"
+files = [
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+]
+
+[package.dependencies]
+Flake8 = ">=5"
+TOMLi = {version = "*", markers = "python_version < \"3.11\""}
+
+[package.extras]
+dev = ["pyTest", "pyTest-cov"]
+
 [[package]]
 name = "fonttools"
 version = "4.53.1"
@@ -784,6 +951,45 @@ wrapt = ">=1.0"
 arrow = ["pyarrow (>=1)"]
 calculus = ["sympy (>=1.3,<1.10)"]
 
+[[package]]
+name = "fsspec"
+version = "2024.6.1"
+description = "File-system specification"
+optional = false
+python-versions = ">=3.8"
+files = [
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+    {file = "fsspec-2024.6.1.tar.gz", hash = "sha256:fad7d7e209dd4c1208e3bbfda706620e0da5142bebbd9c384afb95b07e798e49"},
+]
+
+[package.extras]
+abfs = ["adlfs"]
+adl = ["adlfs"]
+arrow = ["pyarrow (>=1)"]
+dask = ["dask", "distributed"]
+dev = ["pre-commit", "ruff"]
+doc = ["numpydoc", "sphinx", "sphinx-design", "sphinx-rtd-theme", "yarl"]
+dropbox = ["dropbox", "dropboxdrivefs", "requests"]
+full = ["adlfs", "aiohttp (!=4.0.0a0,!=4.0.0a1)", "dask", "distributed", "dropbox", "dropboxdrivefs", "fusepy", "gcsfs", "libarchive-c", "ocifs", "panel", "paramiko", "pyarrow (>=1)", "pygit2", "requests", "s3fs", "smbprotocol", "tqdm"]
+fuse = ["fusepy"]
+gcs = ["gcsfs"]
+git = ["pygit2"]
+github = ["requests"]
+gs = ["gcsfs"]
+gui = ["panel"]
+hdfs = ["pyarrow (>=1)"]
+http = ["aiohttp (!=4.0.0a0,!=4.0.0a1)"]
+libarchive = ["libarchive-c"]
+oci = ["ocifs"]
+s3 = ["s3fs"]
+sftp = ["paramiko"]
+smb = ["smbprotocol"]
+ssh = ["paramiko"]
+test = ["aiohttp (!=4.0.0a0,!=4.0.0a1)", "numpy", "pytest", "pytest-asyncio (!=0.22.0)", "pytest-benchmark", "pytest-cov", "pytest-mock", "pytest-recording", "pytest-rerunfailures", "requests"]
+test-downstream = ["aiobotocore (>=2.5.4,<3.0.0)", "dask-expr", "dask[dataframe,test]", "moto[server] (>4,<5)", "pytest-timeout", "xarray"]
+test-full = ["adlfs", "aiohttp (!=4.0.0a0,!=4.0.0a1)", "cloudpickle", "dask", "distributed", "dropbox", "dropboxdrivefs", "fastparquet", "fusepy", "gcsfs", "jinja2", "kerchunk", "libarchive-c", "lz4", "notebook", "numpy", "ocifs", "pandas", "panel", "paramiko", "pyarrow", "pyarrow (>=1)", "pyftpdlib", "pygit2", "pytest", "pytest-asyncio (!=0.22.0)", "pytest-benchmark", "pytest-cov", "pytest-mock", "pytest-recording", "pytest-rerunfailures", "python-snappy", "requests", "smbprotocol", "tqdm", "urllib3", "zarr", "zstandard"]
+tqdm = ["tqdm"]
+
 [[package]]
 name = "greenlet"
 version = "3.0.3"
@@ -1205,6 +1411,41 @@ files = [
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 ]
 
+[[package]]
+name = "jsonschema"
+version = "4.23.0"
+description = "An implementation of JSON Schema validation for Python"
+optional = false
+python-versions = ">=3.8"
+files = [
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+]
+
+[package.dependencies]
+attrs = ">=22.2.0"
+jsonschema-specifications = ">=2023.03.6"
+referencing = ">=0.28.4"
+rpds-py = ">=0.7.1"
+
+[package.extras]
+format = ["fqdn", "idna", "isoduration", "jsonpointer (>1.13)", "rfc3339-validator", "rfc3987", "uri-template", "webcolors (>=1.11)"]
+format-nongpl = ["fqdn", "idna", "isoduration", "jsonpointer (>1.13)", "rfc3339-validator", "rfc3986-validator (>0.1.0)", "uri-template", "webcolors (>=24.6.0)"]
+
+[[package]]
+name = "jsonschema-specifications"
+version = "2023.12.1"
+description = "The JSON Schema meta-schemas and vocabularies, exposed as a Registry"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "jsonschema_specifications-2023.12.1-py3-none-any.whl", hash = "sha256:87e4fdf3a94858b8a2ba2778d9ba57d8a9cafca7c7489c46ba0d30a8bc6a9c3c"},
+    {file = "jsonschema_specifications-2023.12.1.tar.gz", hash = "sha256:48a76787b3e70f5ed53f1160d2b81f586e4ca6d1548c5de7085d1682674764cc"},
+]
+
+[package.dependencies]
+referencing = ">=0.31.0"
+
 [[package]]
 name = "jupyter-client"
 version = "8.6.2"
@@ -1630,40 +1871,40 @@ files = [
 
 [[package]]
 name = "matplotlib"
-version = "3.9.1"
+version = "3.9.1.post1"
 description = "Python plotting package"
 optional = false
 python-versions = ">=3.9"
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 ]
 
 [package.dependencies]
@@ -1912,6 +2153,61 @@ ssh = ["paramiko"]
 tests = ["codecov", "coverage (<5)", "pytest", "pytest-cov", "pytest-doctestplus", "pytest-env", "pytest-timeout", "sphinx"]
 xvfbwrapper = ["xvfbwrapper"]
 
+[[package]]
+name = "nireports"
+version = "23.2.1"
+description = "NiReports - The Visual Report System (VRS) of NiPreps"
+optional = false
+python-versions = ">=3.8"
+files = [
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+]
+
+[package.dependencies]
+importlib-resources = {version = ">=5.12", markers = "python_version < \"3.12\""}
+matplotlib = ">=3.4.2"
+nibabel = ">=3.0.1"
+nilearn = ">=0.5.2"
+nipype = "*"
+numpy = "*"
+pandas = "*"
+pybids = "*"
+pyyaml = "*"
+seaborn = "*"
+svgutils = ">=0.3.4"
+templateflow = "*"
+
+[package.extras]
+all = ["black (>=22.3.0,<22.4.0)", "coverage", "flake8-pyproject", "furo (>=2021.10.09,<2021.11.0)", "isort (>=5.10.1,<5.11.0)", "matplotlib", "pre-commit", "pydot (>=1.2.3)", "pydotplus", "pytest", "pytest-cov", "pytest-env", "pytest-xdist", "sphinx", "sphinx (>=4.0,<5.0)", "sphinxcontrib-apidoc", "sphinxcontrib-napoleon"]
+dev = ["black (>=22.3.0,<22.4.0)", "flake8-pyproject", "isort (>=5.10.1,<5.11.0)", "pre-commit"]
+doc = ["furo (>=2021.10.09,<2021.11.0)", "pydot (>=1.2.3)", "pydotplus", "sphinx (>=4.0,<5.0)", "sphinxcontrib-apidoc", "sphinxcontrib-napoleon"]
+docs = ["furo (>=2021.10.09,<2021.11.0)", "pydot (>=1.2.3)", "pydotplus", "sphinx (>=4.0,<5.0)", "sphinxcontrib-apidoc", "sphinxcontrib-napoleon"]
+test = ["coverage", "matplotlib", "pytest", "pytest-cov", "pytest-env", "pytest-xdist", "sphinx"]
+tests = ["coverage", "matplotlib", "pytest", "pytest-cov", "pytest-env", "pytest-xdist", "sphinx"]
+
+[[package]]
+name = "nitransforms"
+version = "21.0.0"
+description = "NiTransforms -- Neuroimaging spatial transforms in Python."
+optional = false
+python-versions = ">=3.7"
+files = [
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+]
+
+[package.dependencies]
+h5py = "*"
+nibabel = ">=3.0"
+numpy = "*"
+scipy = "*"
+
+[package.extras]
+all = ["codecov", "pytest", "pytest-cov"]
+test = ["codecov", "pytest", "pytest-cov"]
+tests = ["codecov", "pytest", "pytest-cov"]
+
 [[package]]
 name = "nitransforms"
 version = "23.0.1"
@@ -1938,16 +2234,17 @@ tests = ["codecov", "pytest", "pytest-cov"]
 
 [[package]]
 name = "niworkflows"
-version = "1.10.2"
+version = "1.11.0"
 description = "NeuroImaging Workflows provides processing tools for magnetic resonance images of the brain."
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
+acres = "*"
 attrs = "*"
 importlib-resources = {version = ">=5.7", markers = "python_version < \"3.11\""}
 jinja2 = "*"
@@ -2048,6 +2345,74 @@ files = [
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 ]
 
+[[package]]
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+description = "Fundamental package for array computing in Python"
+optional = false
+python-versions = ">=3.9"
+files = [
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+]
+
+[[package]]
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+version = "4.1.0"
+description = "An OrderedSet is a custom MutableSet that remembers its order, so that every"
+optional = false
+python-versions = ">=3.7"
+files = [
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+]
+
+[package.extras]
+dev = ["black", "mypy", "pytest"]
+
 [[package]]
 name = "packaging"
 version = "24.1"
@@ -2313,13 +2678,13 @@ testing = ["pytest", "pytest-benchmark"]
 
 [[package]]
 name = "pre-commit"
-version = "3.7.1"
+version = "3.8.0"
 description = "A framework for managing and maintaining multi-language pre-commit hooks."
 optional = false
 python-versions = ">=3.9"
 files = [
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 ]
 
 [package.dependencies]
@@ -2418,13 +2783,13 @@ tests = ["pytest"]
 
 [[package]]
 name = "pybids"
-version = "0.16.5"
+version = "0.17.0"
 description = "bids: interface with datasets conforming to BIDS"
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
@@ -2437,6 +2802,7 @@ numpy = ">=1.19"
 pandas = ">=0.25.2"
 scipy = ">=1.5"
 sqlalchemy = ">=1.3.16"
+universal-pathlib = ">=0.2.2"
 
 [package.extras]
 ci-tests = ["pybids[test]"]
@@ -2451,13 +2817,13 @@ tutorial = ["ipykernel", "jinja2", "jupyter-client", "markupsafe", "nbconvert"]
 
 [[package]]
 name = "pycodestyle"
-version = "2.12.0"
+version = "2.12.1"
 description = "Python style guide checker"
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [[package]]
@@ -2550,13 +2916,13 @@ testing = ["covdefaults (>=2.3)", "pytest (>=8.2.2)", "pytest-cov (>=5)", "pytes
 
 [[package]]
 name = "pytest"
-version = "8.3.1"
+version = "8.3.2"
 description = "pytest: simple powerful testing with Python"
 optional = false
 python-versions = ">=3.8"
 files = [
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 networkx = ["networkx (>=2.0.0,<3.0.0)"]
 
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 version = "2.32.3"
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@@ -3008,6 +3524,38 @@ dev = ["cython-lint (>=0.12.2)", "doit (>=0.36.0)", "mypy (==1.10.0)", "pycodest
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+[[package]]
+name = "sdcflows"
+version = "2.5.2"
+description = "Susceptibility Distortion Correction (SDC) workflows for EPI MR schemes."
+optional = false
+python-versions = ">=3.8"
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+traits = "<6.4"
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+tests = ["coverage", "pytest", "pytest-cov", "pytest-env", "pytest-xdist"]
+
 [[package]]
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 version = "2.10.0"
@@ -3064,6 +3612,43 @@ dev = ["flake8", "flit", "mypy", "pandas-stubs", "pre-commit", "pytest", "pytest
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 stats = ["scipy (>=1.7)", "statsmodels (>=0.12)"]
 
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+
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+rich = ["rich"]
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+
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 [package.dependencies]
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 [[package]]
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 python-versions = ">=3.8"
 files = [
-    {file = "tox-4.16.0-py3-none-any.whl", hash = "sha256:61e101061b977b46cf00093d4319438055290ad0009f84497a07bf2d2d7a06d0"},
-    {file = "tox-4.16.0.tar.gz", hash = "sha256:43499656f9949edb681c0f907f86fbfee98677af9919d8b11ae5ad77cb800748"},
+    {file = "tox-4.17.0-py3-none-any.whl", hash = "sha256:82ef41e7e54182e2143daf0b2920d9030c2e1c4291e12091ebad66860c7be7a4"},
+    {file = "tox-4.17.0.tar.gz", hash = "sha256:b1e2e1dfbfdc174d9be95ae78ec2c4d2cf4800d4c15571deddb197a2c90d2de6"},
 ]
 
 [package.dependencies]
-cachetools = ">=5.3.3"
+cachetools = ">=5.4"
 chardet = ">=5.2"
 colorama = ">=0.4.6"
 filelock = ">=3.15.4"
@@ -3486,18 +4071,18 @@ tomli = {version = ">=2.0.1", markers = "python_version < \"3.11\""}
 virtualenv = ">=20.26.3"
 
 [package.extras]
-docs = ["furo (>=2024.5.6)", "sphinx (>=7.3.7)", "sphinx-argparse-cli (>=1.16)", "sphinx-autodoc-typehints (>=2.2.2)", "sphinx-copybutton (>=0.5.2)", "sphinx-inline-tabs (>=2023.4.21)", "sphinxcontrib-towncrier (>=0.2.1a0)", "towncrier (>=23.11)"]
-testing = ["build[virtualenv] (>=1.2.1)", "covdefaults (>=2.3)", "detect-test-pollution (>=1.2)", "devpi-process (>=1)", "diff-cover (>=9.1)", "distlib (>=0.3.8)", "flaky (>=3.8.1)", "hatch-vcs (>=0.4)", "hatchling (>=1.25)", "psutil (>=6)", "pytest (>=8.2.2)", "pytest-cov (>=5)", "pytest-mock (>=3.14)", "pytest-xdist (>=3.6.1)", "re-assert (>=1.1)", "setuptools (>=70.2)", "time-machine (>=2.14.2)", "wheel (>=0.43)"]
+docs = ["furo (>=2024.7.18)", "sphinx (>=7.4.7)", "sphinx-argparse-cli (>=1.16)", "sphinx-autodoc-typehints (>=2.2.3)", "sphinx-copybutton (>=0.5.2)", "sphinx-inline-tabs (>=2023.4.21)", "sphinxcontrib-towncrier (>=0.2.1a0)", "towncrier (>=23.11)"]
+testing = ["build[virtualenv] (>=1.2.1)", "covdefaults (>=2.3)", "detect-test-pollution (>=1.2)", "devpi-process (>=1)", "diff-cover (>=9.1.1)", "distlib (>=0.3.8)", "flaky (>=3.8.1)", "hatch-vcs (>=0.4)", "hatchling (>=1.25)", "psutil (>=6)", "pytest (>=8.3.2)", "pytest-cov (>=5)", "pytest-mock (>=3.14)", "pytest-xdist (>=3.6.1)", "re-assert (>=1.1)", "setuptools (>=70.3)", "time-machine (>=2.14.2)", "wheel (>=0.43)"]
 
 [[package]]
 name = "tqdm"
-version = "4.66.4"
+version = "4.66.5"
 description = "Fast, Extensible Progress Meter"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "tqdm-4.66.4-py3-none-any.whl", hash = "sha256:b75ca56b413b030bc3f00af51fd2c1a1a5eac6a0c1cca83cbb37a5c52abce644"},
-    {file = "tqdm-4.66.4.tar.gz", hash = "sha256:e4d936c9de8727928f3be6079590e97d9abfe8d39a590be678eb5919ffc186bb"},
+    {file = "tqdm-4.66.5-py3-none-any.whl", hash = "sha256:90279a3770753eafc9194a0364852159802111925aa30eb3f9d85b0e805ac7cd"},
+    {file = "tqdm-4.66.5.tar.gz", hash = "sha256:e1020aef2e5096702d8a025ac7d16b1577279c9d63f8375b63083e9a5f0fcbad"},
 ]
 
 [package.dependencies]
@@ -3586,6 +4171,28 @@ files = [
 [package.dependencies]
 numpy = ">=1.15"
 
+[[package]]
+name = "trx-python"
+version = "0.3"
+description = "Experiments with new file format for tractography"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "trx_python-0.3-py3-none-any.whl", hash = "sha256:b00efb1024022a7835cc8b36e024a4ea575f19ce3fae81deb50b709fc8abcb49"},
+    {file = "trx_python-0.3.tar.gz", hash = "sha256:193e3282eaf03610c7e1b848aec04ddb9498fad3a7b684b30ca358e06751fbfd"},
+]
+
+[package.dependencies]
+deepdiff = "*"
+nibabel = ">=5"
+numpy = ">=1.22"
+setuptools-scm = "*"
+
+[package.extras]
+all = ["astroid (==2.15.8)", "flake8", "numpydoc", "psutil", "pydata-sphinx-theme", "pytest (>=7)", "pytest-console-scripts (>=0)", "sphinx", "sphinx-autoapi"]
+doc = ["astroid (==2.15.8)", "numpydoc", "pydata-sphinx-theme", "sphinx", "sphinx-autoapi"]
+test = ["flake8", "psutil", "pytest (>=7)", "pytest-console-scripts (>=0)"]
+
 [[package]]
 name = "typing-extensions"
 version = "4.12.2"
@@ -3608,6 +4215,24 @@ files = [
     {file = "tzdata-2024.1.tar.gz", hash = "sha256:2674120f8d891909751c38abcdfd386ac0a5a1127954fbc332af6b5ceae07efd"},
 ]
 
+[[package]]
+name = "universal-pathlib"
+version = "0.2.2"
+description = "pathlib api extended to use fsspec backends"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "universal_pathlib-0.2.2-py3-none-any.whl", hash = "sha256:9bc176112d593348bb29806a47e409eda78dff8d95391d66dd6f85e443aaa75d"},
+    {file = "universal_pathlib-0.2.2.tar.gz", hash = "sha256:6bc215548792ad5db3553708b1c19bafd9e2fa1667dc925ed404c95e52ae2f13"},
+]
+
+[package.dependencies]
+fsspec = ">=2022.1.0"
+
+[package.extras]
+dev = ["adlfs", "aiohttp", "cheroot", "gcsfs", "moto[s3,server] (<5)", "mypy (==1.8.0)", "packaging", "pydantic", "pydantic-settings", "pylint (==2.17.4)", "pytest (==8.0.0)", "pytest-cov (==4.1.0)", "pytest-mock (==3.12.0)", "pytest-sugar (==0.9.7)", "requests", "s3fs", "webdav4[fsspec]", "wsgidav"]
+tests = ["mypy (==1.8.0)", "packaging", "pylint (==2.17.4)", "pytest (==8.0.0)", "pytest-cov (==4.1.0)", "pytest-mock (==3.12.0)", "pytest-sugar (==0.9.7)"]
+
 [[package]]
 name = "urllib3"
 version = "2.2.2"
@@ -3738,4 +4363,4 @@ files = [
 [metadata]
 lock-version = "2.0"
 python-versions = "^3.10"
-content-hash = "6f951fb98e049f6c11d41d1124bf789e4fca3a3aedc48b025aafed203f815e27"
+content-hash = "7c861a626a96a6389deb9b46476278046beaa40bf2c38ae74c35597032b5c053"
diff --git a/pyproject.toml b/pyproject.toml
index 8e19557..b36000f 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -31,6 +31,11 @@ smriprep = "^0.12.1"
 sdcflows = "^2.5.1"
 tox = "^4.16.0"
 doc8 = "^1.1.1"
+flake8-pyproject = "^1.2.3"
+pytest = "^8.3.2"
+nireports = "^23.2.1"
+setuptools = "^72.1.0"
+dipy = "^1.9.0"
 
 [tool.poetry.dev-dependencies]
 coverage = "^7.5.4"  # testing
@@ -88,3 +93,7 @@ source = [
 omit = [
     "tests/*"
 ]
+
+[tool.flake8]
+max-line-length = 88
+per-file-ignores = ["src/keprep/config.py:E501", "src/keprep/workflows/dwi/descriptions/*.py:E501","src/keprep/interfaces/*.py:E501"]
diff --git a/src/keprep/config.py b/src/keprep/config.py
index 1e87c85..c87b186 100644
--- a/src/keprep/config.py
+++ b/src/keprep/config.py
@@ -254,7 +254,7 @@ class nipype(_Config):
     memory_gb = None
     """Estimation in GB of the RAM this workflow can allocate at any given time."""
     nprocs = os.cpu_count()
-    """Number of processes (compute tasks) that can be run in parallel (multiprocessing only)."""  # noqa: C0301
+    """Number of processes (compute tasks) that can be run in parallel (multiprocessing only)."""  # noqa: E501
     omp_nthreads = None
     """Number of CPUs a single process can access for multithreaded execution."""
     plugin = "MultiProc"
@@ -342,6 +342,8 @@ class execution(_Config):
     """FreeSurfer's subjects directory."""
     layout = None
     """A :py:class:`~keprep.bids.layout.QSIPrepLayout` object, see :py:func:`init`."""
+    reportlets_dir = None
+    """Path to a directory where reportlets will be stored."""
     log_dir = None
     """The path to a directory that contains execution logs."""
     log_level = 25
@@ -424,6 +426,9 @@ def init(cls):
             cls.participant_label = cls.layout.get_subjects()
         else:
             cls.participant_label = list(cls.participant_label)
+        if cls.reportlets_dir is None:
+            cls.reportlets_dir = Path(cls.work_dir) / "reportlets"
+        cls.reportlets_dir.mkdir(exist_ok=True, parents=True)  # type: ignore[union-attr]
 
 
 # These variables are not necessary anymore
@@ -442,6 +447,10 @@ class workflow(_Config):
 
     anat_only = False
     """Execute the anatomical preprocessing only."""
+    dwi2t1w_method = "epireg"
+    """
+    Method to use for DWI-to-T1w coregistration. Either "epireg" (default) or "flirt"
+    """
     dwi2t1w_dof = 6
     """Degrees of freedom of the DWI-to-T1w registration steps."""
     dwi2t1w_init = "register"
@@ -465,6 +474,19 @@ class workflow(_Config):
     skull_strip_t1w = "force"
     """Skip brain extraction of the T1w image (default is ``force``, meaning that
     *KePrep* will run brain extraction of the T1w)."""
+    denoise_method = "dwidenoise"
+    """Image-based denoising method. Either "dwidenoise" (MRtrix), "patch2self" (DIPY)
+    or "none"."""
+    dwi_denoise_window = "auto"
+    """Window size in voxels for image-based denoising, integer or "auto"."""
+    dwi_no_biascorr = False
+    """DEPRECATED: see --b1-biascorrect-stage."""
+    eddy_config = "--fwhm=0 --flm='quadratic' --repol"
+    """Configuration for running Eddy."""
+    hmc_model = "eddy"
+    """Model used to generate target images for hmc."""
+    b0_threshold = 100
+    """any value in the .bval file less than this will be considered a b=0 image."""
 
 
 class loggers:
diff --git a/src/keprep/data/__init__.py b/src/keprep/data/__init__.py
new file mode 100644
index 0000000..b1918c8
--- /dev/null
+++ b/src/keprep/data/__init__.py
@@ -0,0 +1,14 @@
+"""fMRIPrep data files
+
+.. autofunction:: load
+
+.. automethod:: load.readable
+
+.. automethod:: load.as_path
+
+.. automethod:: load.cached
+"""
+
+from acres import Loader
+
+load = Loader(__package__)
diff --git a/src/keprep/data/boilerplate.bib b/src/keprep/data/boilerplate.bib
new file mode 100644
index 0000000..7a236e9
--- /dev/null
+++ b/src/keprep/data/boilerplate.bib
@@ -0,0 +1,728 @@
+@article{fmriprep1,
+    author = {Esteban, Oscar and Markiewicz, Christopher and Blair, Ross W and Moodie, Craig and Isik, Ayse Ilkay and Erramuzpe Aliaga, Asier and Kent, James and Goncalves, Mathias and DuPre, Elizabeth and Snyder, Madeleine and Oya, Hiroyuki and Ghosh, Satrajit and Wright, Jessey and Durnez, Joke and Poldrack, Russell and Gorgolewski, Krzysztof Jacek},
+    title = {fmriprep: a robust preprocessing pipeline for functional {MRI}},
+    year = {2018},
+    doi = {10.1101/306951},
+    journal = {bioRxiv}
+}
+
+@article{fmriprep2,
+    author = {Esteban, Oscar and Blair, Ross and Markiewicz, Christopher J. and Berleant, Shoshana L. and Moodie, Craig and Ma, Feilong and Isik, Ayse Ilkay and Erramuzpe, Asier and Kent, James D. andGoncalves, Mathias and DuPre, Elizabeth and Sitek, Kevin R. and Gomez, Daniel E. P. and Lurie, Daniel J. and Ye, Zhifang and Poldrack, Russell A. and Gorgolewski, Krzysztof J.},
+    title = {fmriprep},
+    year = 2018,
+    doi = {10.5281/zenodo.852659},
+    publisher = {Zenodo},
+    journal = {Software}
+}
+
+@article{dipy,
+  title={Dipy, a library for the analysis of diffusion MRI data},
+  author={Garyfallidis, Eleftherios and Brett, Matthew and Amirbekian, Bagrat and Rokem, Ariel and Van Der Walt, Stefan and Descoteaux, Maxime and Nimmo-Smith, Ian},
+  journal={Frontiers in neuroinformatics},
+  volume={8},
+  pages={8},
+  year={2014},
+  publisher={Frontiers}
+}
+
+
+@article{pyafq,
+  title = {Evaluating the reliability of human brain white matter tractometry},
+  author = {Kruper, J. and Yeatman, J.D. and Richie-Halford, A. and Bloom, D. and Grotheer, M. and Caffarra, S. and Kiar, G. and Karipidis, I.I. and Roy, E. and Chandio, B.Q. and Garyfallidis, E. and Rokem, A.},
+  journal = {Aperture Neuro},
+  volume = {1},
+  pages = {1-25},
+  year = {2021},
+}
+
+@article{pyafq2,
+  title = {Tract profiles of White Matter Properties: Automating fiber-tract quantification},
+  volume = {7},
+  doi = {10.1371/journal.pone.0049790},
+  number = {11},
+  journal = {PLoS ONE},
+  author = {Yeatman, Jason D. and Dougherty, Robert F. and Myall, Nathaniel J. and Wandell, Brian A. and Feldman, Heidi M.},
+  year = {2012}
+}
+
+@article{nipype1,
+    author = {Gorgolewski, K. and Burns, C. D. and Madison, C. and Clark, D. and Halchenko, Y. O. and Waskom, M. L. and Ghosh, S.},
+    doi = {10.3389/fninf.2011.00013},
+    journal = {Frontiers in Neuroinformatics},
+    pages = 13,
+    shorttitle = {Nipype},
+    title = {Nipype: a flexible, lightweight and extensible neuroimaging data processing framework in Python},
+    volume = 5,
+    year = 2011
+}
+
+@article{nipype2,
+    author = {Gorgolewski, Krzysztof J. and Esteban, Oscar and Markiewicz, Christopher J. and Ziegler, Erik and Ellis, David Gage and Notter, Michael Philipp and Jarecka, Dorota and Johnson, Hans and Burns, Christopher and Manhães-Savio, Alexandre and Hamalainen, Carlo and Yvernault, Benjamin and Salo, Taylor and Jordan, Kesshi and Goncalves, Mathias and Waskom, Michael and Clark, Daniel and Wong, Jason and Loney, Fred and Modat, Marc and Dewey, Blake E and Madison, Cindee and Visconti di Oleggio Castello, Matteo and Clark, Michael G. and Dayan, Michael and Clark, Dav and Keshavan, Anisha and Pinsard, Basile and Gramfort, Alexandre and Berleant, Shoshana and Nielson, Dylan M. and Bougacha, Salma and Varoquaux, Gael and Cipollini, Ben and Markello, Ross and Rokem, Ariel and Moloney, Brendan and Halchenko, Yaroslav O. and Wassermann , Demian and Hanke, Michael and Horea, Christian and Kaczmarzyk, Jakub and Gilles de Hollander and DuPre, Elizabeth and Gillman, Ashley and Mordom, David and Buchanan, Colin and Tungaraza, Rosalia and Pauli, Wolfgang M. and Iqbal, Shariq and Sikka, Sharad and Mancini, Matteo and Schwartz, Yannick and Malone, Ian B. and Dubois, Mathieu and Frohlich, Caroline and Welch, David and Forbes, Jessica and Kent, James and Watanabe, Aimi and Cumba, Chad and Huntenburg, Julia M. and Kastman, Erik and Nichols, B. Nolan and Eshaghi, Arman and Ginsburg, Daniel and Schaefer, Alexander and Acland, Benjamin and Giavasis, Steven and Kleesiek, Jens and Erickson, Drew and Küttner, René and Haselgrove, Christian and Correa, Carlos and Ghayoor, Ali and Liem, Franz and Millman, Jarrod and Haehn, Daniel and Lai, Jeff and Zhou, Dale and Blair, Ross and Glatard, Tristan and Renfro, Mandy and Liu, Siqi and Kahn, Ari E. and Pérez-García, Fernando and Triplett, William and Lampe, Leonie and Stadler, Jörg and Kong, Xiang-Zhen and Hallquist, Michael and Chetverikov, Andrey and Salvatore, John and Park, Anne and Poldrack, Russell and Craddock, R. Cameron and Inati, Souheil and Hinds, Oliver and Cooper, Gavin and Perkins, L. Nathan and Marina, Ana and Mattfeld, Aaron and Noel, Maxime and Lukas Snoek and Matsubara, K and Cheung, Brian and Rothmei, Simon and Urchs, Sebastian and Durnez, Joke and Mertz, Fred and Geisler, Daniel and Floren, Andrew and Gerhard, Stephan and Sharp, Paul and Molina-Romero, Miguel and Weinstein, Alejandro and Broderick, William and Saase, Victor and Andberg, Sami Kristian and Harms, Robbert and Schlamp, Kai and Arias, Jaime and Papadopoulos Orfanos, Dimitri and Tarbert, Claire and Tambini, Arielle and De La Vega, Alejandro and Nickson, Thomas and Brett, Matthew and Falkiewicz, Marcel and Podranski, Kornelius and Linkersdörfer, Janosch and Flandin, Guillaume and Ort, Eduard and Shachnev, Dmitry and McNamee, Daniel and Davison, Andrew and Varada, Jan and Schwabacher, Isaac and Pellman, John and Perez-Guevara, Martin and Khanuja, Ranjeet and Pannetier, Nicolas and McDermottroe, Conor and Ghosh, Satrajit},
+    title = {Nipype},
+    year = 2018,
+    doi = {10.5281/zenodo.596855},
+    publisher = {Zenodo},
+    journal = {Software}
+}
+
+@article{n4,
+    author = {Tustison, N. J. and Avants, B. B. and Cook, P. A. and Zheng, Y. and Egan, A. and Yushkevich, P. A. and Gee, J. C.},
+    doi = {10.1109/TMI.2010.2046908},
+    issn = {0278-0062},
+    journal = {IEEE Transactions on Medical Imaging},
+    number = 6,
+    pages = {1310-1320},
+    shorttitle = {N4ITK},
+    title = {N4ITK: Improved N3 Bias Correction},
+    volume = 29,
+    year = 2010
+}
+
+@article{fs_reconall,
+    author = {Dale, Anders M. and Fischl, Bruce and Sereno, Martin I.},
+    doi = {10.1006/nimg.1998.0395},
+    issn = {1053-8119},
+    journal = {NeuroImage},
+    number = 2,
+    pages = {179-194},
+    shorttitle = {Cortical Surface-Based Analysis},
+    title = {Cortical Surface-Based Analysis: I. Segmentation and Surface Reconstruction},
+    url = {http://www.sciencedirect.com/science/article/pii/S1053811998903950},
+    volume = 9,
+    year = 1999
+}
+
+@article{mindboggle,
+    author = {Klein, Arno and Ghosh, Satrajit S. and Bao, Forrest S. and Giard, Joachim and Häme, Yrjö and Stavsky, Eliezer and Lee, Noah and Rossa, Brian and Reuter, Martin and Neto, Elias Chaibub and Keshavan, Anisha},
+    doi = {10.1371/journal.pcbi.1005350},
+    issn = {1553-7358},
+    journal = {PLOS Computational Biology},
+    number = 2,
+    pages = {e1005350},
+    title = {Mindboggling morphometry of human brains},
+    url = {http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1005350},
+    volume = 13,
+    year = 2017
+}
+
+@article{mni,
+    author = {Fonov, VS and Evans, AC and McKinstry, RC and Almli, CR and Collins, DL},
+    doi = {10.1016/S1053-8119(09)70884-5},
+    issn = {1053-8119},
+    journal = {NeuroImage},
+    pages = {S102},
+    series = {Organization for Human Brain Mapping 2009 Annual Meeting},
+    title = {Unbiased nonlinear average age-appropriate brain templates from birth to adulthood},
+    url = {http://www.sciencedirect.com/science/article/pii/S1053811909708845},
+    volume = {47, Supplement 1},
+    year = 2009
+}
+
+@article{ants,
+    author = {Avants, B.B. and Epstein, C.L. and Grossman, M. and Gee, J.C.},
+    doi = {10.1016/j.media.2007.06.004},
+    issn = {1361-8415},
+    journal = {Medical Image Analysis},
+    number = 1,
+    pages = {26-41},
+    shorttitle = {Symmetric diffeomorphic image registration with cross-correlation},
+    title = {Symmetric diffeomorphic image registration with cross-correlation: Evaluating automated labeling of elderly and neurodegenerative brain},
+    url = {http://www.sciencedirect.com/science/article/pii/S1361841507000606},
+    volume = 12,
+    year = 2008
+}
+
+@article{fsl_fast,
+    author = {Zhang, Y. and Brady, M. and Smith, S.},
+    doi = {10.1109/42.906424},
+    issn = {0278-0062},
+    journal = {IEEE Transactions on Medical Imaging},
+    number = 1,
+    pages = {45-57},
+    title = {Segmentation of brain {MR} images through a hidden Markov random field model and the expectation-maximization algorithm},
+    volume = 20,
+    year = 2001
+}
+
+@article{fieldmapless1,
+    author = {Wang, Sijia and Peterson, Daniel J. and Gatenby, J. C. and Li, Wenbin and Grabowski, Thomas J. and Madhyastha, Tara M.},
+    doi = {10.3389/fninf.2017.00017},
+    issn = {1662-5196},
+    journal = {Frontiers in Neuroinformatics},
+    language = {English},
+    title = {Evaluation of Field Map and Nonlinear Registration Methods for Correction of Susceptibility Artifacts in Diffusion {MRI}},
+    url = {http://journal.frontiersin.org/article/10.3389/fninf.2017.00017/full},
+    volume = 11,
+    year = 2017
+}
+
+@phdthesis{fieldmapless2,
+    address = {Berlin},
+    author = {Huntenburg, Julia M.},
+    language = {eng},
+    school = {Freie Universität},
+    title = {Evaluating nonlinear coregistration of {BOLD} {EPI} and T1w images},
+    type = {Master's Thesis},
+    url = {http://hdl.handle.net/11858/00-001M-0000-002B-1CB5-A},
+    year = 2014
+}
+
+@article{fieldmapless3,
+    author = {Treiber, Jeffrey Mark and White, Nathan S. and Steed, Tyler Christian and Bartsch, Hauke and Holland, Dominic and Farid, Nikdokht and McDonald, Carrie R. and Carter, Bob S. and Dale, Anders Martin and Chen, Clark C.},
+    doi = {10.1371/journal.pone.0152472},
+    issn = {1932-6203},
+    journal = {PLOS ONE},
+    number = 3,
+    pages = {e0152472},
+    title = {Characterization and Correction of Geometric Distortions in 814 Diffusion Weighted Images},
+    url = {http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0152472},
+    volume = 11,
+    year = 2016
+}
+
+@article{flirt,
+    title = {A global optimisation method for robust affine registration of brain images},
+    volume = {5},
+    issn = {1361-8415},
+    url = {http://www.sciencedirect.com/science/article/pii/S1361841501000366},
+    doi = {10.1016/S1361-8415(01)00036-6},
+    number = {2},
+    urldate = {2018-07-27},
+    journal = {Medical Image Analysis},
+    author = {Jenkinson, Mark and Smith, Stephen},
+    year = {2001},
+    keywords = {Affine transformation, flirt, fsl, Global optimisation, Multi-resolution search, Multimodal registration, Robustness},
+    pages = {143--156}
+}
+
+@article{mcflirt,
+    author = {Jenkinson, Mark and Bannister, Peter and Brady, Michael and Smith, Stephen},
+    doi = {10.1006/nimg.2002.1132},
+    issn = {1053-8119},
+    journal = {NeuroImage},
+    number = 2,
+    pages = {825-841},
+    title = {Improved Optimization for the Robust and Accurate Linear Registration and Motion Correction of Brain Images},
+    url = {http://www.sciencedirect.com/science/article/pii/S1053811902911328},
+    volume = 17,
+    year = 2002
+}
+
+@article{bbr,
+    author = {Greve, Douglas N and Fischl, Bruce},
+    doi = {10.1016/j.neuroimage.2009.06.060},
+    issn = {1095-9572},
+    journal = {NeuroImage},
+    number = 1,
+    pages = {63-72},
+    title = {Accurate and robust brain image alignment using boundary-based registration},
+    volume = 48,
+    year = 2009
+}
+
+@article{aroma,
+    author = {Pruim, Raimon H. R. and Mennes, Maarten and van Rooij, Daan and Llera, Alberto and Buitelaar, Jan K. and Beckmann, Christian F.},
+    doi = {10.1016/j.neuroimage.2015.02.064},
+    issn = {1053-8119},
+    journal = {NeuroImage},
+    number = {Supplement C},
+    pages = {267-277},
+    shorttitle = {ICA-AROMA},
+    title = {ICA-{AROMA}: A robust {ICA}-based strategy for removing motion artifacts from fMRI data},
+    url = {http://www.sciencedirect.com/science/article/pii/S1053811915001822},
+    volume = 112,
+    year = 2015
+}
+
+@article{power_fd_dvars,
+    author = {Power, Jonathan D. and Mitra, Anish and Laumann, Timothy O. and Snyder, Abraham Z. and Schlaggar, Bradley L. and Petersen, Steven E.},
+    doi = {10.1016/j.neuroimage.2013.08.048},
+    issn = {1053-8119},
+    journal = {NeuroImage},
+    number = {Supplement C},
+    pages = {320-341},
+    title = {Methods to detect, characterize, and remove motion artifact in resting state fMRI},
+    url = {http://www.sciencedirect.com/science/article/pii/S1053811913009117},
+    volume = 84,
+    year = 2014
+}
+
+@article{nilearn,
+    author = {Abraham, Alexandre and Pedregosa, Fabian and Eickenberg, Michael and Gervais, Philippe and Mueller, Andreas and Kossaifi, Jean and Gramfort, Alexandre and Thirion, Bertrand and Varoquaux, Gael},
+    doi = {10.3389/fninf.2014.00014},
+    issn = {1662-5196},
+    journal = {Frontiers in Neuroinformatics},
+    language = {English},
+    title = {Machine learning for neuroimaging with scikit-learn},
+    url = {https://www.frontiersin.org/articles/10.3389/fninf.2014.00014/full},
+    volume = 8,
+    year = 2014
+}
+
+@article{lanczos,
+    author = {Lanczos, C.},
+    doi = {10.1137/0701007},
+    issn = {0887-459X},
+    journal = {Journal of the Society for Industrial and Applied Mathematics Series B Numerical Analysis},
+    number = 1,
+    pages = {76-85},
+    title = {Evaluation of Noisy Data},
+    url = {http://epubs.siam.org/doi/10.1137/0701007},
+    volume = 1,
+    year = 1964
+}
+
+@article{compcor,
+    author = {Behzadi, Yashar and Restom, Khaled and Liau, Joy and Liu, Thomas T.},
+    doi = {10.1016/j.neuroimage.2007.04.042},
+    issn = {1053-8119},
+    journal = {NeuroImage},
+    number = 1,
+    pages = {90-101},
+    title = {A component based noise correction method ({CompCor}) for {BOLD} and perfusion based fMRI},
+    url = {http://www.sciencedirect.com/science/article/pii/S1053811907003837},
+    volume = 37,
+    year = 2007
+}
+
+@article{hcppipelines,
+    author = {Glasser, Matthew F. and Sotiropoulos, Stamatios N. and Wilson, J. Anthony and Coalson, Timothy S. and Fischl, Bruce and Andersson, Jesper L. and Xu, Junqian and Jbabdi, Saad and Webster, Matthew and Polimeni, Jonathan R. and Van Essen, David C. and Jenkinson, Mark},
+    doi = {10.1016/j.neuroimage.2013.04.127},
+    issn = {1053-8119},
+    journal = {NeuroImage},
+    pages = {105-124},
+    series = {Mapping the Connectome},
+    title = {The minimal preprocessing pipelines for the Human Connectome Project},
+    url = {http://www.sciencedirect.com/science/article/pii/S1053811913005053},
+    volume = 80,
+    year = 2013
+}
+
+@article{fs_template,
+    author = {Reuter, Martin and Rosas, Herminia Diana and Fischl, Bruce},
+    doi = {10.1016/j.neuroimage.2010.07.020},
+    journal = {NeuroImage},
+    number = 4,
+    pages = {1181-1196},
+    title = {Highly accurate inverse consistent registration: A robust approach},
+    volume = 53,
+    year = 2010
+}
+
+@article{afni,
+    author = {Cox, Robert W. and Hyde, James S.},
+    doi = {10.1002/(SICI)1099-1492(199706/08)10:4/5<171::AID-NBM453>3.0.CO;2-L},
+    journal = {NMR in Biomedicine},
+    number = {4-5},
+    pages = {171-178},
+    title = {Software tools for analysis and visualization of fMRI data},
+    volume = 10,
+    year = 1997
+}
+
+@article{posse_t2s,
+    author = {Posse, Stefan and Wiese, Stefan and Gembris, Daniel and Mathiak, Klaus and Kessler, Christoph and Grosse-Ruyken, Maria-Liisa and Elghahwagi, Barbara and Richards, Todd and Dager, Stephen R. and Kiselev, Valerij G.},
+    doi = {10.1002/(SICI)1522-2594(199907)42:1<87::AID-MRM13>3.0.CO;2-O},
+    journal = {Magnetic Resonance in Medicine},
+    number = 1,
+    pages = {87-97},
+    title = {Enhancement of {BOLD}-contrast sensitivity by single-shot multi-echo functional {MR} imaging},
+    volume = 42,
+    year = 1999
+}
+
+@article{dwidenoise1,
+  title={Denoising of diffusion MRI using random matrix theory},
+  author={Veraart, Jelle and Novikov, Dmitry S and Christiaens, Daan and Ades-Aron, Benjamin and Sijbers, Jan and Fieremans, Els},
+  journal={NeuroImage},
+  volume={142},
+  pages={394--406},
+  year={2016},
+  publisher={Elsevier}
+}
+
+@article{dwidenoise2,
+  title={Diffusion MRI noise mapping using random matrix theory},
+  author={Veraart, Jelle and Fieremans, Els and Novikov, Dmitry S},
+  journal={Magnetic resonance in medicine},
+  volume={76},
+  number={5},
+  pages={1582--1593},
+  year={2016},
+  publisher={Wiley Online Library}
+}
+
+@article{merlet3dshore,
+  title={Continuous diffusion signal, EAP and ODF estimation via compressive sensing in diffusion MRI},
+  author={Merlet, Sylvain L and Deriche, Rachid},
+  journal={Medical image analysis},
+  volume={17},
+  number={5},
+  pages={556--572},
+  year={2013},
+  publisher={Elsevier}
+}
+
+@article{pncprocessing,
+  title={Neuroimaging of the Philadelphia neurodevelopmental cohort},
+  author={Satterthwaite, Theodore D and Elliott, Mark A and Ruparel, Kosha and Loughead, James and Prabhakaran, Karthik and Calkins, Monica E and Hopson, Ryan and Jackson, Chad and Keefe, Jack and Riley, Marisa and others},
+  journal={Neuroimage},
+  volume={86},
+  pages={544--553},
+  year={2014},
+  publisher={Elsevier}
+}
+
+@inproceedings{dhollander2019response,
+  title={Improved white matter response function estimation for 3-tissue constrained spherical deconvolution},
+  author={Dhollander, T and Mito, R and Raffelt, D and Connelly, A},
+  booktitle={Proc. Intl. Soc. Mag. Reson. Med},
+  pages={555},
+  year={2019}
+}
+
+@inproceedings{dhollander2016unsupervised,
+  title={Unsupervised 3-tissue response function estimation from single-shell or multi-shell diffusion MR data without a co-registered T1 image},
+  author={Dhollander, Thijs and Raffelt, David and Connelly, Alan},
+  booktitle={ISMRM Workshop on Breaking the Barriers of Diffusion MRI},
+  volume={5},
+  pages={5},
+  year={2016}
+}
+
+@article{msmt5tt,
+  title={Multi-tissue constrained spherical deconvolution for improved analysis of multi-shell diffusion MRI data},
+  author={Jeurissen, Ben and Tournier, Jacques-Donald and Dhollander, Thijs and Connelly, Alan and Sijbers, Jan},
+  journal={NeuroImage},
+  volume={103},
+  pages={411--426},
+  year={2014},
+  publisher={Elsevier}
+}
+
+@article{mrtrix3,
+  title = {MRtrix3: A fast, flexible and open software framework for medical image processing and visualisation},
+  author = {J-Donald and Smith, Robert and Raffelt, David and Tabbara, Rami and Dhollander, Thijs and Pietsch, Maximilian and Christiaens, Daan and Jeurissen, Ben and Yeh, Chun-Hung and Connelly, Alan"},
+  journal = {NeuroImage},
+  volume = {202},
+  pages = {116137},
+  year = {2019},
+  issn={1053-8119},
+}
+
+@article{originalcsd,
+  title={Direct estimation of the fiber orientation density function from diffusion-weighted MRI data using spherical deconvolution},
+  author={Tournier, J-Donald and Calamante, Fernando and Gadian, David G and Connelly, Alan},
+  journal={NeuroImage},
+  volume={23},
+  number={3},
+  pages={1176--1185},
+  year={2004},
+  publisher={Elsevier}
+}
+
+@article{tournier2007robust,
+  title={Robust determination of the fibre orientation distribution in diffusion MRI: non-negativity constrained super-resolved spherical deconvolution},
+  author={Tournier, J-Donald and Calamante, Fernando and Connelly, Alan},
+  journal={Neuroimage},
+  volume={35},
+  number={4},
+  pages={1459--1472},
+  year={2007},
+  publisher={Elsevier}
+}
+
+@article{tournier2008csd,
+  title={Resolving crossing fibres using constrained spherical deconvolution: validation using diffusion-weighted imaging phantom data},
+  author={Tournier, J-Donald and Yeh, Chun-Hung and Calamante, Fernando and Cho, Kuan-Hung and Connelly, Alan and Lin, Ching-Po},
+  journal={Neuroimage},
+  volume={42},
+  number={2},
+  pages={617--625},
+  year={2008},
+  publisher={Elsevier}
+}
+
+@inproceedings{mtnormalize,
+  title={Bias field correction and intensity normalisation for quantitative analysis of apparent fibre density},
+  author={Raffelt, David and Dhollander, Thijs and Tournier, J-Donald and Tabbara, Rami and Smith, Robert E and Pierre, Eric and Connelly, Alan},
+  booktitle={Proc. Intl. Soc. Mag. Reson. Med},
+  volume={25},
+  pages={3541},
+  year={2017}
+}
+
+@article{yeh2010gqi,
+  title={Generalized $q$-sampling imaging},
+  author={Yeh, Fang-Cheng and Wedeen, Van Jay and Tseng, Wen-Yih Isaac},
+  journal={IEEE transactions on medical imaging},
+  volume={29},
+  number={9},
+  pages={1626--1635},
+  year={2010},
+  publisher={IEEE}
+}
+
+@article{anderssoneddy,
+  title={An integrated approach to correction for off-resonance effects and subject movement in diffusion MR imaging},
+  author={Andersson, Jesper LR and Sotiropoulos, Stamatios N},
+  journal={Neuroimage},
+  volume={125},
+  pages={1063--1078},
+  year={2016},
+  publisher={Elsevier}
+}
+
+@article{eddyrepol,
+  title={Incorporating outlier detection and replacement into a non-parametric framework for movement and distortion correction of diffusion MR images},
+  author={Andersson, Jesper LR and Graham, Mark S and Zsoldos, Enik{\H{o}} and Sotiropoulos, Stamatios N},
+  journal={Neuroimage},
+  volume={141},
+  pages={556--572},
+  year={2016},
+  publisher={Elsevier}
+}
+
+@article{fsllsr,
+  title={How to correct susceptibility distortions in spin-echo echo-planar images: application to diffusion tensor imaging},
+  author={Andersson, Jesper LR and Skare, Stefan and Ashburner, John},
+  journal={Neuroimage},
+  volume={20},
+  number={2},
+  pages={870--888},
+  year={2003},
+  publisher={Elsevier}
+}
+
+
+@article{eddysus,
+  title={Susceptibility-induced distortion that varies due to motion: correction in diffusion MR without acquiring additional data},
+  author={Andersson, Jesper LR and Graham, Mark S and Drobnjak, Ivana and Zhang, Hui and Campbell, Jon},
+  journal={Neuroimage},
+  volume={171},
+  pages={277--295},
+  year={2018},
+  publisher={Elsevier}
+}
+
+@article{eddys2v,
+  title={Towards a comprehensive framework for movement and distortion correction of diffusion MR images: Within volume movement},
+  author={Andersson, Jesper LR and Graham, Mark S and Drobnjak, Ivana and Zhang, Hui and Filippini, Nicola and Bastiani, Matteo},
+  journal={Neuroimage},
+  volume={152},
+  pages={450--466},
+  year={2017},
+  publisher={Elsevier}
+}
+
+@article{topup,
+  title={How to correct susceptibility distortions in spin-echo echo-planar images: application to diffusion tensor imaging},
+  author={Andersson, Jesper LR and Skare, Stefan and Ashburner, John},
+  journal={Neuroimage},
+  volume={20},
+  number={2},
+  pages={870--888},
+  year={2003},
+  publisher={Elsevier}
+}
+
+@article{mrdegibbs,
+  title={Gibbs-ringing artifact removal based on local subvoxel-shifts},
+  author={Kellner, Elias and Dhital, Bibek and Kiselev, Valerij G and Reisert, Marco},
+  journal={Magnetic resonance in medicine},
+  volume={76},
+  number={5},
+  pages={1574--1581},
+  year={2016},
+  publisher={Wiley Online Library}
+}
+
+@article{patch2self,
+  title={Patch2Self: Denoising Diffusion MRI with Self-Supervised Learning​},
+  author={Fadnavis, Shreyas and Batson, Joshua and Garyfallidis, Eleftherios},
+  journal={Advances in Neural Information Processing Systems},
+  volume={33},
+  year={2020}
+}
+
+@article{noddi,
+  title={NODDI: practical in vivo neurite orientation dispersion and density imaging of the human brain},
+  author={Zhang, Hui and Schneider, Torben and Wheeler-Kingshott, Claudia A and Alexander, Daniel C},
+  journal={Neuroimage},
+  volume={61},
+  number={4},
+  pages={1000--1016},
+  year={2012},
+  publisher={Elsevier}
+}
+
+@article{amico,
+  title={Accelerated microstructure imaging via convex optimization (AMICO) from diffusion MRI data},
+  author={Daducci, Alessandro and Canales-Rodr{\'\i}guez, Erick J and Zhang, Hui and Dyrby, Tim B and Alexander, Daniel C and Thiran, Jean-Philippe},
+  journal={NeuroImage},
+  volume={105},
+  pages={32--44},
+  year={2015},
+  publisher={Elsevier}
+}
+
+@article{drbuddi,
+  title={DR-BUDDI (Diffeomorphic Registration for Blip-Up blip-Down Diffusion Imaging) method for correcting echo planar imaging distortions},
+  author={Irfanoglu, M Okan and Modi, Pooja and Nayak, Amritha and Hutchinson, Elizabeth B and Sarlls, Joelle and Pierpaoli, Carlo},
+  journal={Neuroimage},
+  volume={106},
+  pages={284--299},
+  year={2015},
+  publisher={Elsevier}
+}
+
+@inproceedings{tortoisev3,
+  title={TORTOISE v3: Improvements and new features of the NIH diffusion MRI processing pipeline},
+  author={Irfanoglu, Mustafa Okan and Nayak, Amritha and Jenkins, Jeffrey and Pierpaoli, Carlo},
+  booktitle={Program and proceedings of the ISMRM 25th annual meeting and exhibition, Honolulu, HI, USA},
+  year={2017}
+}
+
+@article{pfgibbs,
+  title={Removal of partial Fourier-induced Gibbs (RPG) ringing artifacts in MRI},
+  author={Lee, Hong-Hsi and Novikov, Dmitry S and Fieremans, Els},
+  journal={Magnetic Resonance in Medicine},
+  volume={86},
+  number={5},
+  pages={2733--2750},
+  year={2021},
+  publisher={Wiley Online Library}
+}
+
+@article{synthstrip,
+  title={SynthStrip: skull-stripping for any brain image},
+  author={Hoopes, Andrew and Mora, Jocelyn S and Dalca, Adrian V and Fischl, Bruce and Hoffmann, Malte},
+  journal={NeuroImage},
+  volume={260},
+  pages={119474},
+  year={2022},
+  publisher={Elsevier}
+}
+
+@article{synthseg1,
+  title={SynthSeg: Segmentation of brain MRI scans of any contrast and resolution without retraining},
+  author={Billot, Benjamin and Greve, Douglas N and Puonti, Oula and Thielscher, Axel and Van Leemput, Koen and Fischl, Bruce and Dalca, Adrian V and Iglesias, Juan Eugenio and others},
+  journal={Medical image analysis},
+  volume={86},
+  pages={102789},
+  year={2023},
+  publisher={Elsevier}
+}
+
+@article{synthseg2,
+  title={Robust machine learning segmentation for large-scale analysis of heterogeneous clinical brain MRI datasets},
+  author={Billot, Benjamin and Magdamo, Colin and Cheng, You and Arnold, Steven E and Das, Sudeshna and Iglesias, Juan Eugenio},
+  journal={Proceedings of the National Academy of Sciences},
+  volume={120},
+  number={9},
+  pages={e2216399120},
+  year={2023},
+  publisher={National Acad Sciences}
+}
+
+@article{yeh2013deterministic,
+  title={Deterministic diffusion fiber tracking improved by quantitative anisotropy},
+  author={Yeh, Fang-Cheng and Verstynen, Timothy D and Wang, Yibao and Fern{\'a}ndez-Miranda, Juan C and Tseng, Wen-Yih Isaac},
+  journal={PloS one},
+  volume={8},
+  number={11},
+  pages={e80713},
+  year={2013},
+  publisher={Public Library of Science San Francisco, USA}
+}
+
+@article{autotrack,
+  title={Shape analysis of the human association pathways},
+  author={Yeh, Fang-Cheng},
+  journal={Neuroimage},
+  volume={223},
+  pages={117329},
+  year={2020},
+  publisher={Elsevier}
+}
+
+@article{fsl,
+	series = {20 {YEARS} {OF} {fMRI}},
+	title = {{FSL}},
+	volume = {62},
+	issn = {1053-8119},
+	url = {https://www.sciencedirect.com/science/article/pii/S1053811911010603},
+	doi = {10.1016/j.neuroimage.2011.09.015},
+	abstract = {FSL (the FMRIB Software Library) is a comprehensive library of analysis tools for functional, structural and diffusion MRI brain imaging data, written mainly by members of the Analysis Group, FMRIB, Oxford. For this NeuroImage special issue on “20 years of fMRI” we have been asked to write about the history, developments and current status of FSL. We also include some descriptions of parts of FSL that are not well covered in the existing literature. We hope that some of this content might be of interest to users of FSL, and also maybe to new research groups considering creating, releasing and supporting new software packages for brain image analysis.},
+	number = {2},
+	urldate = {2024-08-06},
+	journal = {NeuroImage},
+	author = {Jenkinson, Mark and Beckmann, Christian F. and Behrens, Timothy E. J. and Woolrich, Mark W. and Smith, Stephen M.},
+	month = aug,
+	year = {2012},
+	keywords = {FSL, Software},
+	pages = {782--790},
+	file = {ScienceDirect Snapshot:/home/galkepler/Zotero/storage/AKPNE6UP/S1053811911010603.html:text/html;Submitted Version:/home/galkepler/Zotero/storage/WSMH855W/Jenkinson et al. - 2012 - FSL.pdf:application/pdf},
+}
+
+@article{eddyqc,
+	title = {Automated quality control for within and between studies diffusion {MRI} data using a non-parametric framework for movement and distortion correction},
+	volume = {184},
+	issn = {1095-9572},
+	doi = {10.1016/j.neuroimage.2018.09.073},
+	abstract = {Diffusion MRI data can be affected by hardware and subject-related artefacts that can adversely affect downstream analyses. Therefore, automated quality control (QC) is of great importance, especially in large population studies where visual QC is not practical. In this work, we introduce an automated diffusion MRI QC framework for single subject and group studies. The QC is based on a comprehensive, non-parametric approach for movement and distortion correction: FSL EDDY, which allows us to extract a rich set of QC metrics that are both sensitive and specific to different types of artefacts. Two different tools are presented: QUAD (QUality Assessment for DMRI), for single subject QC and SQUAD (Study-wise QUality Assessment for DMRI), which is designed to enable group QC and facilitate cross-studies harmonisation efforts.},
+	language = {eng},
+	journal = {Neuroimage},
+	author = {Bastiani, Matteo and Cottaar, Michiel and Fitzgibbon, Sean P. and Suri, Sana and Alfaro-Almagro, Fidel and Sotiropoulos, Stamatios N. and Jbabdi, Saad and Andersson, Jesper L. R.},
+	month = jan,
+	year = {2019},
+	pmid = {30267859},
+	pmcid = {PMC6264528},
+	keywords = {Artifacts, Brain, Brain Mapping, Diffusion Magnetic Resonance Imaging, Diffusion MRI, Diffusion Tensor Imaging, Eddy current, Female, Humans, Image Processing, Computer-Assisted, Male, Movement, Quality control, Quality Control, Reproducibility of Results, Signal-To-Noise Ratio, Susceptibility},
+	pages = {801--812},
+	file = {Full Text:/home/galkepler/Zotero/storage/7CKISWDD/Bastiani et al. - 2019 - Automated quality control for within and between s.pdf:application/pdf},
+}
+
+@article{templateflow,
+    author = {Ciric, R. and Thompson, William H. and Lorenz, R. and Goncalves, M. and MacNicol, E. and Markiewicz, C. J. and Halchenko, Y. O. and Ghosh, S. S. and Gorgolewski, K. J. and Poldrack, R. A. and Esteban, O.},
+    title = {{TemplateFlow}: {FAIR}-sharing of multi-scale, multi-species brain models},
+    volume = {19},
+    pages = {1568--1571},
+    year = {2022},
+    doi = {10.1038/s41592-022-01681-2},
+    journal = {Nature Methods}
+}
+
+@article{mni152lin,
+    title = {A {Probabilistic} {Atlas} of the {Human} {Brain}: {Theory} and {Rationale} for {Its} {Development}: {The} {International} {Consortium} for {Brain} {Mapping} ({ICBM})},
+    author = {Mazziotta, John C. and Toga, Arthur W. and Evans, Alan and Fox, Peter and Lancaster, Jack},
+    volume = {2},
+    issn = {1053-8119},
+    shorttitle = {A {Probabilistic} {Atlas} of the {Human} {Brain}},
+    doi = {10.1006/nimg.1995.1012},
+    number = {2, Part A},
+    journal = {NeuroImage},
+    year = {1995},
+    pages = {89--101}
+}
+
+@article{mni152nlin2009casym,
+    title = {Unbiased nonlinear average age-appropriate brain templates from birth to adulthood},
+    author = {Fonov, VS and Evans, AC and McKinstry, RC and Almli, CR and Collins, DL},
+    doi = {10.1016/S1053-8119(09)70884-5},
+    journal = {NeuroImage},
+    pages = {S102},
+    volume = {47, Supplement 1},
+    year = 2009
+}
+
+@article{mni152nlin6asym,
+    author = {Evans, AC and Janke, AL and Collins, DL and Baillet, S},
+    title = {Brain templates and atlases},
+    doi = {10.1016/j.neuroimage.2012.01.024},
+    journal = {NeuroImage},
+    volume = {62},
+    number = {2},
+    pages = {911--922},
+    year = 2012
+}
diff --git a/src/keprep/interfaces/data/keprep.json b/src/keprep/data/keprep.json
similarity index 99%
rename from src/keprep/interfaces/data/keprep.json
rename to src/keprep/data/keprep.json
index 43a0075..a86ceb1 100644
--- a/src/keprep/interfaces/data/keprep.json
+++ b/src/keprep/data/keprep.json
@@ -182,4 +182,4 @@
     "sub-{subject}/{datatype<figures>}/sub-{subject}[_ses-{session}][_acq-{acquisition}][_ce-{ceagent}][_rec-{reconstruction}][_dir-{direction}][_run-{run}][_echo-{echo}][_part-{part}][_space-{space}][_cohort-{cohort}][_desc-{desc}]_{suffix<dwi|epi|epiref>}{extension<.html|.svg>|.svg}",
     "sub-{subject}/{datatype<figures>}/sub-{subject}[_ses-{session}]_task-{task}[_acq-{acquisition}][_ce-{ceagent}][_rec-{reconstruction}][_dir-{direction}][_run-{run}][_echo-{echo}][_part-{part}][_space-{space}][_cohort-{cohort}][_desc-{desc}]_{suffix<bold>}{extension<.html|.svg>|.svg}"
   ]
-}
\ No newline at end of file
+}
diff --git a/src/keprep/data/quality_assurance/__init__.py b/src/keprep/data/quality_assurance/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/src/keprep/data/quality_assurance/reports.py b/src/keprep/data/quality_assurance/reports.py
new file mode 100644
index 0000000..8505a61
--- /dev/null
+++ b/src/keprep/data/quality_assurance/reports.py
@@ -0,0 +1,233 @@
+# emacs: -*- mode: python; py-indent-offset: 4; indent-tabs-mode: nil -*-
+# vi: set ft=python sts=4 ts=4 sw=4 et:
+#
+# Copyright The NiPreps Developers <nipreps@gmail.com>
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+# We support and encourage derived works from this project, please read
+# about our expectations at
+#
+#     https://www.nipreps.org/community/licensing/
+#
+from pathlib import Path
+
+from nipype.pipeline import engine as pe
+from nireports.assembler.report import Report
+
+from keprep import config, data
+
+
+def build_boilerplate(config_file: dict | str | Path, workflow: pe.Workflow):
+    """Write boilerplate in an isolated process."""
+    from keprep import config
+
+    if isinstance(config_file, str) or isinstance(config_file, Path):
+        config.load(config_file)
+    elif isinstance(config_file, dict):
+        config.from_dict(config_file)
+    logs_path = config.execution.keprep_dir / "logs"  # type: ignore[attr-defined]
+    logs_path.mkdir(parents=True, exist_ok=True)
+    boilerplate = workflow.visit_desc()
+    citation_files = {
+        ext: logs_path / f"CITATION.{ext}" for ext in ("bib", "tex", "md", "html")
+    }
+
+    if boilerplate:
+        # To please git-annex users and also to guarantee consistency
+        # among different renderings of the same file, first remove any
+        # existing one
+        for citation_file in citation_files.values():
+            try:
+                citation_file.unlink()
+            except FileNotFoundError:
+                pass
+
+    citation_files["md"].write_text(boilerplate)
+
+    if citation_files["md"].exists():
+        from subprocess import CalledProcessError, TimeoutExpired, check_call
+
+        from keprep import data
+
+        bib_text = data.load.readable("boilerplate.bib").read_text()
+        citation_files["bib"].write_text(
+            bib_text.replace("KePrep <version>", f"KePrep {config.environment.version}")
+        )
+
+        # Generate HTML file resolving citations
+        cmd = [
+            "pandoc",
+            "-s",
+            "--bibliography",
+            str(citation_files["bib"]),
+            "--citeproc",
+            "--metadata",
+            'pagetitle="fMRIPrep citation boilerplate"',
+            str(citation_files["md"]),
+            "-o",
+            str(citation_files["html"]),
+        ]
+
+        config.loggers.cli.info(
+            "Generating an HTML version of the citation boilerplate..."
+        )
+        try:
+            check_call(cmd, timeout=10)
+        except (FileNotFoundError, CalledProcessError, TimeoutExpired):
+            config.loggers.cli.warning(
+                "Could not generate CITATION.html file:\n%s", " ".join(cmd)
+            )
+
+        # Generate LaTex file resolving citations
+        cmd = [
+            "pandoc",
+            "-s",
+            "--bibliography",
+            str(citation_files["bib"]),
+            "--natbib",
+            str(citation_files["md"]),
+            "-o",
+            str(citation_files["tex"]),
+        ]
+        config.loggers.cli.info(
+            "Generating a LaTeX version of the citation boilerplate..."
+        )
+        try:
+            check_call(cmd, timeout=10)
+        except (FileNotFoundError, CalledProcessError, TimeoutExpired):
+            config.loggers.cli.warning(
+                "Could not generate CITATION.tex file:\n%s", " ".join(cmd)
+            )
+
+
+def run_reports(
+    output_dir,
+    subject_label,
+    run_uuid,
+    bootstrap_file=None,
+    out_filename="report.html",
+    reportlets_dir=None,
+    errorname="report.err",
+    **entities,
+):
+    """
+    Run the reports.
+    """
+    robj = Report(
+        output_dir,
+        run_uuid,
+        bootstrap_file=bootstrap_file,
+        out_filename=out_filename,
+        reportlets_dir=reportlets_dir,
+        plugins=None,
+        plugin_meta=None,
+        metadata=None,
+        **entities,
+    )
+
+    # Count nbr of subject for which report generation failed
+    try:
+        robj.generate_report()
+    except:  # noqa: E722
+        import sys
+        import traceback
+
+        # Store the list of subjects for which report generation failed
+        traceback.print_exception(
+            *sys.exc_info(), file=str(Path(output_dir) / "logs" / errorname)
+        )
+        return subject_label
+
+    return None
+
+
+def generate_reports(
+    subject_list,
+    output_dir,
+    run_uuid,
+    session_list=None,
+    bootstrap_file=None,
+    work_dir=None,
+):
+    """Generate reports for a list of subjects."""
+    reportlets_dir = None
+    if work_dir is not None:
+        reportlets_dir = Path(work_dir) / "reportlets"
+
+    if isinstance(subject_list, str):
+        subject_list = [subject_list]
+
+    errors = []
+    for subject_label in subject_list:
+        # The number of sessions is intentionally not based on session_list but
+        # on the total number of sessions, because I want the final derivatives
+        # folder to be the same whether sessions were run one at a time or all-together.
+        n_ses = len(config.execution.layout.get_sessions(subject=subject_label))
+        html_report = "report.html"
+
+        bootstrap_file = data.load("quality_assurance/templates/reports-spec.yml")
+        html_report = "report.html"
+
+        report_error = run_reports(
+            output_dir,
+            subject_label,
+            run_uuid,
+            bootstrap_file=bootstrap_file,
+            out_filename=html_report,
+            reportlets_dir=reportlets_dir,
+            errorname=f"report-{run_uuid}-{subject_label}.err",
+            subject=subject_label,
+        )
+        # If the report generation failed, append the subject label for which it failed
+        if report_error is not None:
+            errors.append(report_error)
+
+        if n_ses > config.execution.aggr_ses_reports:
+            # Beyond a certain number of sessions per subject,
+            # we separate the functional reports per session
+            if session_list is None:
+                all_filters = config.execution.bids_filters or {}
+                filters = all_filters.get("bold", {})
+                session_list = config.execution.layout.get_sessions(
+                    subject=subject_label, **filters
+                )
+
+            # Drop ses- prefixes
+            session_list = [
+                ses[4:] if ses.startswith("ses-") else ses for ses in session_list
+            ]
+
+            for session_label in session_list:
+                bootstrap_file = data.load("reports-spec-func.yml")
+                html_report = (
+                    f'sub-{subject_label.lstrip("sub-")}_ses-{session_label}_func.html'
+                )
+
+                report_error = run_reports(
+                    output_dir,
+                    subject_label,
+                    run_uuid,
+                    bootstrap_file=bootstrap_file,
+                    out_filename=html_report,
+                    reportlets_dir=reportlets_dir,
+                    errorname=f"report-{run_uuid}-{subject_label}-func.err",
+                    subject=subject_label,
+                    session=session_label,
+                )
+                # If the report generation failed,
+                # append the subject label for which it failed
+                if report_error is not None:
+                    errors.append(report_error)
+
+    return errors
diff --git a/src/keprep/data/quality_assurance/templates/__init__.py b/src/keprep/data/quality_assurance/templates/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/src/keprep/data/quality_assurance/templates/reports-spec.yml b/src/keprep/data/quality_assurance/templates/reports-spec.yml
new file mode 100644
index 0000000..9e333f6
--- /dev/null
+++ b/src/keprep/data/quality_assurance/templates/reports-spec.yml
@@ -0,0 +1,70 @@
+package: keprep
+title: Visual report for participant '{subject}' - KePrep
+sections:
+- name: Summary
+  reportlets:
+  - bids: {datatype: figures, desc: summary, suffix: T1w}
+- name: Anatomical
+  reportlets:
+  - bids:
+      datatype: figures
+      desc: conform
+      extension: [.html]
+      suffix: T1w
+  - bids: {datatype: figures, suffix: dseg}
+    caption: This panel shows the final, preprocessed T1-weighted image,
+      with contours delineating the detected brain mask and brain tissue segmentations.
+    subtitle: Brain mask and brain tissue segmentation of the T1w
+  - bids: {datatype: figures, space: .*, suffix: T1w, regex_search: True}
+    caption: Spatial normalization of the T1w image to the <code>{space}</code> template.
+    description: Results of nonlinear alignment of the T1w reference one or more template
+      space(s). Hover on the panels with the mouse pointer to transition between both
+      spaces.
+    static: false
+    subtitle: Spatial normalization of the anatomical T1w reference
+  - bids: {datatype: figures, desc: reconall, suffix: T1w}
+    caption: Surfaces (white and pial) reconstructed with FreeSurfer (<code>recon-all</code>)
+      overlaid on the participant's T1w template.
+    subtitle: Surface reconstruction
+
+
+- name: Diffusion
+  ordering: session
+  reportlets:
+  - bids: {datatype: figures, suffix: dwi, extension: [.html]}
+    caption: This panel shows the final, preprocessed diffusion-weighted image.
+    subtitle: Diffusion-weighted image (DWI)
+  - bids: {datatype: figures, desc: sdc, suffix: dwi}
+    caption: Susceptibility distortion correction (TOPUP) applied to the DWI.
+    subtitle: Susceptibility distortion correction (TOPUP).
+    static: false
+  - bids: {datatype: figures, desc: coreg, suffix: dwi}
+    caption: b=0 to anatomical reference registration
+    subtitle: Coregistration of the DWI to the anatomical T1w image using FSL's <code>FLIRT</code>.
+    static: false
+  - bids: {datatype: figures, desc: eddyqc, suffix: dwi}
+    caption: EDDY Quality Control
+    subtitle: QC for head motion correction as conducted by FSL's <code>EDDY</code>.
+
+
+- name: About
+  nested: true
+  reportlets:
+  - bids: {datatype: figures, desc: about, suffix: T1w}
+  - custom: boilerplate
+    path: '{out_dir}/logs'
+    bibfile: ['keprep', 'data/boilerplate.bib']
+    caption: |
+      <p>We kindly ask to report results preprocessed with this tool using the following boilerplate.</p>
+      <p class="alert alert-info" role="alert">
+      <strong>Copyright Waiver</strong>.
+      The boilerplate text was automatically generated by <em>NiReports</em> with the
+      express intention that users should copy and paste this text into their manuscripts <em>unchanged</em>.
+      It is released under the
+      <a href="https://creativecommons.org/publicdomain/zero/1.0/" target="_blank">CC0 license</a>.
+      </p>
+    title: Methods
+  - custom: errors
+    path: '{out_dir}/sub-{subject}/log/{run_uuid}'
+    captions: <em>NiReports</em> may have recorded failure conditions.
+    title: Errors
diff --git a/src/keprep/interfaces/bids/__init__.py b/src/keprep/interfaces/bids/__init__.py
new file mode 100644
index 0000000..d4e95fc
--- /dev/null
+++ b/src/keprep/interfaces/bids/__init__.py
@@ -0,0 +1,10 @@
+from keprep.interfaces.bids.bids import (  # noqa: F401
+    BIDSDataGrabber,
+    DerivativesDataSink,
+)
+from keprep.interfaces.bids.utils import (  # noqa: F401
+    collect_data,
+    get_fieldmap,
+    write_bidsignore,
+    write_derivative_description,
+)
diff --git a/src/keprep/interfaces/bids/bids.py b/src/keprep/interfaces/bids/bids.py
new file mode 100644
index 0000000..1735d30
--- /dev/null
+++ b/src/keprep/interfaces/bids/bids.py
@@ -0,0 +1,103 @@
+# emacs: -*- mode: python; py-indent-offset: 4; indent-tabs-mode: nil -*-
+# vi: set ft=python sts=4 ts=4 sw=4 et:
+
+from nipype import logging
+from nipype.interfaces.base import (
+    BaseInterfaceInputSpec,
+    OutputMultiObject,
+    SimpleInterface,
+    Str,
+    TraitedSpec,
+    traits,
+)
+from niworkflows.interfaces.bids import DerivativesDataSink as _DDSink
+
+LOGGER = logging.getLogger("nipype.interface")
+
+CUSTOM_PATH_PATTERNS = [
+    "sub-{subject}[/ses-{session}]/{datatype<dwi>|dwi}/sub-{subject}[_ses-{session}][_acq-{acquisition}][_rec-{reconstruction}][_dir-{direction}][_run-{run}][_space-{space}][_cohort-{cohort}][_res-{resolution}][_desc-{desc}]_{suffix<dwi|dwiref|epiref|lowb|dseg|streamlines>}{extension<.json|.nii.gz|.nii|.tck|.trk>|.nii.gz}",  # pylint: disable=line-too-long
+    "sub-{subject}[/ses-{session}]/{datatype<dwi>|dwi}/{desc}",
+]
+
+
+class DerivativesDataSink(_DDSink):
+    out_path_base = ""
+    _file_patterns = tuple(list(_DDSink._file_patterns) + CUSTOM_PATH_PATTERNS)
+
+
+__all__ = ("DerivativesDataSink",)
+
+
+class _BIDSDataGrabberInputSpec(BaseInterfaceInputSpec):
+    subject_data = traits.Dict(Str, traits.Any)
+    subject_id = Str()
+
+
+class _BIDSDataGrabberOutputSpec(TraitedSpec):
+    out_dict = traits.Dict(desc="output data structure")
+    fmap = OutputMultiObject(desc="output fieldmaps")
+    bold = OutputMultiObject(desc="output functional images")
+    sbref = OutputMultiObject(desc="output sbrefs")
+    t1w = OutputMultiObject(desc="output T1w images")
+    roi = OutputMultiObject(desc="output ROI images")
+    t2w = OutputMultiObject(desc="output T2w images")
+    flair = OutputMultiObject(desc="output FLAIR images")
+    dwi = OutputMultiObject(desc="output DWI images")
+
+
+class BIDSDataGrabber(SimpleInterface):
+    """
+    Collect files from a BIDS directory structure.
+
+    .. testsetup::
+
+        >>> data_dir_canary()
+
+    >>> bids_src = BIDSDataGrabber(anat_only=False)
+    >>> bids_src.inputs.subject_data = bids_collect_data(
+    ...     str(datadir / 'ds114'), '01', bids_validate=False)[0]
+    >>> bids_src.inputs.subject_id = '01'
+    >>> res = bids_src.run()
+    >>> res.outputs.t1w  # doctest: +ELLIPSIS +NORMALIZE_WHITESPACE
+    ['.../ds114/sub-01/ses-retest/anat/sub-01_ses-retest_T1w.nii.gz',
+     '.../ds114/sub-01/ses-test/anat/sub-01_ses-test_T1w.nii.gz']
+
+    """
+
+    input_spec = _BIDSDataGrabberInputSpec
+    output_spec = _BIDSDataGrabberOutputSpec
+    _require_dwis = True
+
+    def __init__(self, *args, **kwargs):
+        anat_only = kwargs.pop("anat_only")
+        anat_derivatives = kwargs.pop("anat_derivatives", None)
+        super().__init__(*args, **kwargs)
+        if anat_only is not None:
+            self._require_dwis = not anat_only
+        self._require_t1w = anat_derivatives is None
+
+    def _run_interface(self, runtime):
+        bids_dict = self.inputs.subject_data
+
+        self._results["out_dict"] = bids_dict
+        self._results.update(bids_dict)
+
+        if self._require_t1w and not bids_dict["t1w"]:
+            raise FileNotFoundError(
+                f"No T1w images found for subject sub-{self.inputs.subject_id}"
+            )
+
+        if self._require_dwis and not bids_dict["dwi"]:
+            raise FileNotFoundError(
+                f"No DWI images found for subject sub-{self.inputs.subject_id}"
+            )
+
+        for imtype in ["bold", "t2w", "flair", "fmap", "sbref", "roi", "dwi"]:
+            if not bids_dict.get(imtype):
+                LOGGER.info(
+                    'No "%s" images found for sub-%s',
+                    imtype,
+                    self.inputs.subject_id,
+                )
+
+        return runtime
diff --git a/src/keprep/interfaces/bids.py b/src/keprep/interfaces/bids/utils.py
similarity index 59%
rename from src/keprep/interfaces/bids.py
rename to src/keprep/interfaces/bids/utils.py
index d21e06a..a499509 100644
--- a/src/keprep/interfaces/bids.py
+++ b/src/keprep/interfaces/bids/utils.py
@@ -1,34 +1,9 @@
-# emacs: -*- mode: python; py-indent-offset: 4; indent-tabs-mode: nil -*-
-# vi: set ft=python sts=4 ts=4 sw=4 et:
+import json
+import os
 from pathlib import Path
 
 from bids import BIDSLayout
 from bids.layout import Query, parse_file_entities
-from nipype import logging
-from nipype.interfaces.base import (
-    BaseInterfaceInputSpec,
-    OutputMultiObject,
-    SimpleInterface,
-    Str,
-    TraitedSpec,
-    traits,
-)
-from niworkflows.interfaces.bids import DerivativesDataSink as _DDSink
-
-LOGGER = logging.getLogger("nipype.interface")
-
-CUSTOM_PATH_PATTERNS = [
-    "sub-{subject}[/ses-{session}]/{datatype<dwi>|dwi}/sub-{subject}[_ses-{session}][_acq-{acquisition}][_rec-{reconstruction}][_dir-{direction}][_run-{run}][_space-{space}][_cohort-{cohort}][_res-{resolution}][_desc-{desc}]_{suffix<dwi|dwiref|epiref|lowb|dseg|streamlines>}{extension<.json|.nii.gz|.nii|.tck|.trk>|.nii.gz}",  # pylint: disable=line-too-long
-    "sub-{subject}[/ses-{session}]/{datatype<dwi>|dwi}/{desc}",
-]
-
-
-class DerivativesDataSink(_DDSink):
-    out_path_base = ""
-    _file_patterns = tuple(list(_DDSink._file_patterns) + CUSTOM_PATH_PATTERNS)
-
-
-__all__ = ("DerivativesDataSink",)
 
 
 def collect_data(
@@ -138,81 +113,6 @@ def collect_data(
     return subj_data, layout
 
 
-class _BIDSDataGrabberInputSpec(BaseInterfaceInputSpec):
-    subject_data = traits.Dict(Str, traits.Any)
-    subject_id = Str()
-
-
-class _BIDSDataGrabberOutputSpec(TraitedSpec):
-    out_dict = traits.Dict(desc="output data structure")
-    fmap = OutputMultiObject(desc="output fieldmaps")
-    bold = OutputMultiObject(desc="output functional images")
-    sbref = OutputMultiObject(desc="output sbrefs")
-    t1w = OutputMultiObject(desc="output T1w images")
-    roi = OutputMultiObject(desc="output ROI images")
-    t2w = OutputMultiObject(desc="output T2w images")
-    flair = OutputMultiObject(desc="output FLAIR images")
-    dwi = OutputMultiObject(desc="output DWI images")
-
-
-class BIDSDataGrabber(SimpleInterface):
-    """
-    Collect files from a BIDS directory structure.
-
-    .. testsetup::
-
-        >>> data_dir_canary()
-
-    >>> bids_src = BIDSDataGrabber(anat_only=False)
-    >>> bids_src.inputs.subject_data = bids_collect_data(
-    ...     str(datadir / 'ds114'), '01', bids_validate=False)[0]
-    >>> bids_src.inputs.subject_id = '01'
-    >>> res = bids_src.run()
-    >>> res.outputs.t1w  # doctest: +ELLIPSIS +NORMALIZE_WHITESPACE
-    ['.../ds114/sub-01/ses-retest/anat/sub-01_ses-retest_T1w.nii.gz',
-     '.../ds114/sub-01/ses-test/anat/sub-01_ses-test_T1w.nii.gz']
-
-    """
-
-    input_spec = _BIDSDataGrabberInputSpec
-    output_spec = _BIDSDataGrabberOutputSpec
-    _require_dwis = True
-
-    def __init__(self, *args, **kwargs):
-        anat_only = kwargs.pop("anat_only")
-        anat_derivatives = kwargs.pop("anat_derivatives", None)
-        super().__init__(*args, **kwargs)
-        if anat_only is not None:
-            self._require_dwis = not anat_only
-        self._require_t1w = anat_derivatives is None
-
-    def _run_interface(self, runtime):
-        bids_dict = self.inputs.subject_data
-
-        self._results["out_dict"] = bids_dict
-        self._results.update(bids_dict)
-
-        if self._require_t1w and not bids_dict["t1w"]:
-            raise FileNotFoundError(
-                f"No T1w images found for subject sub-{self.inputs.subject_id}"
-            )
-
-        if self._require_dwis and not bids_dict["dwi"]:
-            raise FileNotFoundError(
-                f"No DWI images found for subject sub-{self.inputs.subject_id}"
-            )
-
-        for imtype in ["bold", "t2w", "flair", "fmap", "sbref", "roi", "dwi"]:
-            if not bids_dict.get(imtype):
-                LOGGER.info(
-                    'No "%s" images found for sub-%s',
-                    imtype,
-                    self.inputs.subject_id,
-                )
-
-        return runtime
-
-
 def get_fieldmap(dwi_file: str | Path, subject_data: dict) -> str | None:
     """
     Locate the fieldmap (dir-PA) associated with the dwi file of the session.
@@ -243,3 +143,68 @@ def get_fieldmap(dwi_file: str | Path, subject_data: dict) -> str | None:
         ):
             return fmap
     return None
+
+
+def write_derivative_description(bids_dir, deriv_dir):
+    from keprep import __version__
+
+    DOWNLOAD_URL = (
+        f"https://github.com/GalKepler/keprep/archive/refs/tags/v{__version__}.tar.gz"
+    )
+
+    desc = {
+        "Name": "KePrep output",
+        "BIDSVersion": "1.9.0",
+        "PipelineDescription": {
+            "Name": "keprep",
+            "Version": __version__,
+            "CodeURL": DOWNLOAD_URL,
+        },
+        "GeneratedBy": [
+            {
+                "Name": "keprep",
+                "Version": __version__,
+                "CodeURL": DOWNLOAD_URL,
+            }
+        ],
+        "CodeURL": "https://github.com/GalKepler/keprep",
+        "HowToAcknowledge": "Please cite our paper and "
+        "include the generated citation boilerplate within the Methods "
+        "section of the text.",
+    }
+
+    # Keys deriving from source dataset
+    fname = os.path.join(bids_dir, "dataset_description.json")
+    if os.path.exists(fname):
+        with open(fname) as fobj:
+            orig_desc = json.load(fobj)
+    else:
+        orig_desc = {}
+
+    if "DatasetDOI" in orig_desc:
+        desc["SourceDatasetsURLs"] = [
+            "https://doi.org/{}".format(orig_desc["DatasetDOI"])
+        ]
+    if "License" in orig_desc:
+        desc["License"] = orig_desc["License"]
+
+    with open(os.path.join(deriv_dir, "dataset_description.json"), "w") as fobj:
+        json.dump(desc, fobj, indent=4)
+
+
+def write_bidsignore(deriv_dir):
+    bids_ignore = (
+        "*.html",
+        "logs/",
+        "figures/",  # Reports
+        "*_xfm.*",  # Unspecified transform files
+        "*.surf.gii",  # Unspecified structural outputs
+        # Unspecified functional outputs
+        "*_boldref.nii.gz",
+        "*_bold.func.gii",
+        "*_mixing.tsv",
+        "*_timeseries.tsv",
+    )
+    ignore_file = Path(deriv_dir) / ".bidsignore"
+
+    ignore_file.write_text("\n".join(bids_ignore) + "\n")
diff --git a/src/keprep/interfaces/reports/__init__.py b/src/keprep/interfaces/reports/__init__.py
new file mode 100644
index 0000000..d531c92
--- /dev/null
+++ b/src/keprep/interfaces/reports/__init__.py
@@ -0,0 +1,5 @@
+from keprep.interfaces.reports.reports import (  # noqa: F401
+    AboutSummary,
+    DiffusionSummary,
+    SubjectSummary,
+)
diff --git a/src/keprep/interfaces/reports/reports.py b/src/keprep/interfaces/reports/reports.py
new file mode 100644
index 0000000..85ed3db
--- /dev/null
+++ b/src/keprep/interfaces/reports/reports.py
@@ -0,0 +1,230 @@
+# emacs: -*- mode: python; py-indent-offset: 4; indent-tabs-mode: nil -*-
+# vi: set ft=python sts=4 ts=4 sw=4 et:
+#
+# Copyright 2021 The NiPreps Developers <nipreps@gmail.com>
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+# We support and encourage derived works from this project, please read
+# about our expectations at
+#
+#     https://www.nipreps.org/community/licensing/
+#
+"""Interfaces to generate reportlets."""
+
+import os
+import time
+
+from nipype.interfaces import freesurfer as fs
+from nipype.interfaces.base import (
+    BaseInterfaceInputSpec,
+    Directory,
+    File,
+    InputMultiObject,
+    SimpleInterface,
+    Str,
+    TraitedSpec,
+    isdefined,
+    traits,
+)
+
+SUBJECT_TEMPLATE = """\
+\t<ul class="elem-desc">
+\t\t<li>Subject ID: {subject_id}</li>
+\t\t<li>Structural images: {n_t1s:d} T1-weighted {t2w}</li>
+\t\t<li>Diffusion Weighted Images: {n_dwi:d}</li>
+\t\t<li>Standard output spaces: {std_spaces}</li>
+\t\t<li>Non-standard output spaces: {nstd_spaces}</li>
+\t\t<li>FreeSurfer reconstruction: {freesurfer_status}</li>
+\t</ul>
+"""
+
+DIFFUSION_TEMPLATE = """\t\t<h3 class="elem-title">Summary</h3>
+\t\t<ul class="elem-desc">
+\t\t\t<li>Phase-encoding (PE) direction: {pedir}</li>
+\t\t\t<li>Susceptibility distortion correction: {sdc}</li>
+\t\t\t<li>Coregistration Transform: {coregistration}</li>
+\t\t\t<li>Denoising Method: {denoise_method}</li>
+\t\t\t<li>Denoising Window: {denoise_window}</li>
+\t\t\t<li>HMC Model: {hmc_model}</li>
+\t\t</ul>
+"""
+# {validation_reports}
+
+ABOUT_TEMPLATE = """\t<ul>
+\t\t<li>KePrep version: {version}</li>
+\t\t<li>KePrep command: <code>{command}</code></li>
+\t\t<li>Date preprocessed: {date}</li>
+\t</ul>
+</div>
+"""
+
+
+class SummaryOutputSpec(TraitedSpec):
+    out_report = File(exists=True, desc="HTML segment containing summary")
+
+
+class SummaryInterface(SimpleInterface):
+    output_spec = SummaryOutputSpec
+
+    def _run_interface(self, runtime):
+        segment = self._generate_segment()
+        fname = os.path.join(runtime.cwd, "report.html")
+        with open(fname, "w") as fobj:
+            fobj.write(segment)
+        self._results["out_report"] = fname
+        return runtime
+
+    def _generate_segment(self):
+        raise NotImplementedError
+
+
+class SubjectSummaryInputSpec(BaseInterfaceInputSpec):
+    t1w = InputMultiObject(File(exists=True), desc="T1w structural images")
+    t2w = InputMultiObject(File(exists=True), desc="T2w structural images")
+    subjects_dir = Directory(desc="FreeSurfer subjects directory")
+    subject_id = Str(desc="Subject ID")
+    dwi = InputMultiObject(
+        traits.Either(File(exists=True), traits.List(File(exists=True))),
+        desc="DWI files",
+    )
+    std_spaces = traits.List(Str, desc="list of standard spaces")
+    nstd_spaces = traits.List(Str, desc="list of non-standard spaces")
+
+
+class SubjectSummaryOutputSpec(SummaryOutputSpec):
+    # This exists to ensure that the summary is run prior to the first ReconAll
+    # call, allowing a determination whether there is a pre-existing directory
+    subject_id = Str(desc="FreeSurfer subject ID")
+
+
+class SubjectSummary(SummaryInterface):
+    input_spec = SubjectSummaryInputSpec
+    output_spec = SubjectSummaryOutputSpec
+
+    def _run_interface(self, runtime):
+        if isdefined(self.inputs.subject_id):
+            self._results["subject_id"] = self.inputs.subject_id
+        return super(SubjectSummary, self)._run_interface(runtime)
+
+    def _generate_segment(self):
+        if not isdefined(self.inputs.subjects_dir):
+            freesurfer_status = "Not run"
+        else:
+            recon = fs.ReconAll(
+                subjects_dir=self.inputs.subjects_dir,
+                subject_id=self.inputs.subject_id,
+                T1_files=self.inputs.t1w,
+                flags="-noskullstrip",
+            )
+            if recon.cmdline.startswith("echo"):
+                freesurfer_status = "Pre-existing directory"
+            else:
+                freesurfer_status = "Run by KePrep"
+
+        t2w_seg = ""
+        if self.inputs.t2w:
+            t2w_seg = "(+ {:d} T2-weighted)".format(len(self.inputs.t2w))
+
+        dwi_files = self.inputs.dwi if isdefined(self.inputs.dwi) else []
+        dwi_files = [s[0] if isinstance(s, list) else s for s in dwi_files]
+
+        return SUBJECT_TEMPLATE.format(
+            subject_id=self.inputs.subject_id,
+            n_t1s=len(self.inputs.t1w),
+            t2w=t2w_seg,
+            n_dwi=len(dwi_files),
+            std_spaces=", ".join(self.inputs.std_spaces),
+            nstd_spaces=", ".join(self.inputs.nstd_spaces),
+            freesurfer_status=freesurfer_status,
+        )
+
+
+class AboutSummaryInputSpec(BaseInterfaceInputSpec):
+    version = Str(desc="KePrep version")
+    command = Str(desc="KePrep command")
+    # Date not included - update timestamp only if version or command changes
+
+
+class AboutSummary(SummaryInterface):
+    input_spec = AboutSummaryInputSpec
+
+    def _generate_segment(self):
+        return ABOUT_TEMPLATE.format(
+            version=self.inputs.version,
+            command=self.inputs.command,
+            date=time.strftime("%Y-%m-%d %H:%M:%S %z"),
+        )
+
+
+class DiffusionSummaryInputSpec(BaseInterfaceInputSpec):
+    distortion_correction = traits.Str(
+        default_value="TOPUP",
+        desc="Susceptibility distortion correction method",
+        mandatory=False,
+    )
+    pe_direction = traits.Enum(
+        None,
+        "i",
+        "i-",
+        "j",
+        "j-",
+        mandatory=True,
+        desc="Phase-encoding direction detected",
+    )
+    impute_slice_threshold = traits.CFloat(desc="threshold for imputing a slice")
+    hmc_model = traits.Str(desc="model used for hmc")
+    b0_to_t1w_transform = traits.Enum(
+        "Rigid", "Affine", desc="Transform type for coregistration"
+    )
+    denoise_method = traits.Str(desc="method used for image denoising")
+    dwi_denoise_window = traits.Either(
+        traits.Int(), traits.Str(), desc="window size for dwidenoise"
+    )
+    output_spaces = traits.List(desc="Target spaces")
+    confounds_file = File(exists=True, desc="Confounds file")
+    validation_reports = InputMultiObject(File(exists=True))
+
+
+class DiffusionSummary(SummaryInterface):
+    input_spec = DiffusionSummaryInputSpec
+
+    def _generate_segment(self):
+        if self.inputs.pe_direction is None:
+            pedir = "MISSING - Assuming Anterior-Posterior"
+        else:
+            pedir = {"i": "Left-Right", "j": "Anterior-Posterior"}[
+                self.inputs.pe_direction[0]
+            ]
+
+        if isdefined(self.inputs.confounds_file):
+            with open(self.inputs.confounds_file) as cfh:
+                conflist = cfh.readline().strip("\n").strip()  # noqa: F841
+        else:
+            conflist = ""  # noqa: F841
+
+        validation_summaries = []  # noqa: F841
+        # for summary in self.inputs.validation_reports:
+        #     with open(summary, "r") as summary_f:
+        #         validation_summaries.extend(summary_f.readlines())
+        # validation_summary = "\n".join(validation_summaries)
+
+        return DIFFUSION_TEMPLATE.format(
+            pedir=pedir,
+            sdc=self.inputs.distortion_correction,
+            coregistration=self.inputs.b0_to_t1w_transform,
+            hmc_model=self.inputs.hmc_model,
+            denoise_method=self.inputs.denoise_method,
+            denoise_window=self.inputs.dwi_denoise_window,
+            # validation_reports=validation_summary,
+        )
diff --git a/src/keprep/workflows/base/messages.py b/src/keprep/workflows/base/messages.py
index be20a42..f3c847f 100644
--- a/src/keprep/workflows/base/messages.py
+++ b/src/keprep/workflows/base/messages.py
@@ -13,18 +13,17 @@
 """
 
 BASE_POSTDESC = """
-Many internal operations of *fMRIPrep* use
-*Nilearn* {nilearn_ver} [@nilearn, RRID:SCR_001362],
-mostly within the functional processing workflow.
+Many internal operations of *KePrep* use
+*Nilearn* {nilearn_ver} [@nilearn, RRID:SCR_001362] and *MRtrix* [@mrtrix3, SCR_006971].
 For more details of the pipeline, see [the section corresponding
-to workflows in *fMRIPrep*'s documentation]\
-(https://fmriprep.readthedocs.io/en/latest/workflows.html \
-"FMRIPrep's documentation").
+to workflows in *KePrep*'s documentation]\
+(https://keprep.readthedocs.io/en/latest/workflows.html \
+"KePrep's documentation").
 
 
 ### Copyright Waiver
 
-The above boilerplate text was automatically generated by fMRIPrep
+The above boilerplate text was automatically generated by KePrep
 with the express intention that users should copy and paste this
 text into their manuscripts *unchanged*.
 It is released under the [CC0]\
diff --git a/src/keprep/workflows/base/workflow.py b/src/keprep/workflows/base/workflow.py
index af4aa02..96fc5f1 100644
--- a/src/keprep/workflows/base/workflow.py
+++ b/src/keprep/workflows/base/workflow.py
@@ -1,4 +1,5 @@
 import os
+import sys
 import warnings
 from copy import deepcopy
 from pathlib import Path
@@ -8,6 +9,12 @@
 from packaging.version import Version
 
 from keprep import config
+from keprep.interfaces.bids import (
+    DerivativesDataSink,
+    write_bidsignore,
+    write_derivative_description,
+)
+from keprep.interfaces.reports import AboutSummary, SubjectSummary
 from keprep.workflows.base.messages import (
     ANAT_DERIVATIVES_FAILED,
     BASE_POSTDESC,
@@ -48,22 +55,29 @@ def init_keprep_wf():
     keprep_wf = Workflow(name=f"keprep_{ver.major}_{ver.minor}_{ver.micro}_wf")
     keprep_wf.base_dir = config.execution.work_dir
 
+    # Write BIDS-required files (dataset_description.json, ...)
+    write_derivative_description(
+        config.execution.bids_dir,
+        config.execution.keprep_dir,
+    )
+    write_bidsignore(config.execution.keprep_dir)
+
     freesurfer = config.workflow.do_reconall
     if freesurfer:
         fsdir = pe.Node(
             BIDSFreeSurferDir(
                 derivatives=config.execution.output_dir,
                 freesurfer_home=os.getenv("FREESURFER_HOME"),
-                spaces=config.workflow.spaces.get_fs_spaces(),  # type: ignore[attr-defined]
+                spaces=config.workflow.spaces.get_fs_spaces(),  # type: ignore[attr-defined] # noqa: E501
                 minimum_fs_version="7.0.0",
             ),
             name=f"fsdir_run_{config.execution.run_uuid.replace('-', '_')}",
             run_without_submitting=True,
         )
         if config.execution.fs_subjects_dir is not None:
-            fsdir.inputs.subjects_dir = str(config.execution.fs_subjects_dir.absolute())  # type: ignore[unreachable]
+            fsdir.inputs.subjects_dir = str(config.execution.fs_subjects_dir.absolute())  # type: ignore[unreachable] # noqa: E501
 
-    participants: list = config.execution.participant_label  # type: ignore[assignment]  # pylint: disable=not-an-iterable
+    participants: list = config.execution.participant_label  # type: ignore[assignment]  # pylint: disable=not-an-iterable # noqa: E501
     for subject_id in list(participants):
         single_subject_wf = init_single_subject_wf(subject_id)  # type: ignore[operator]
 
@@ -94,7 +108,6 @@ def init_keprep_wf():
         )
         log_dir.mkdir(exist_ok=True, parents=True)
         config.to_filename(log_dir / "keprep.toml")
-
     return keprep_wf
 
 
@@ -159,7 +172,7 @@ def init_single_subject_wf(subject_id: str):
         )
 
     if anat_derivatives:
-        from smriprep.utils.bids import (  # type: ignore[unreachable] # pylint: disable=import-outside-toplevel,import-error
+        from smriprep.utils.bids import (  # type: ignore[unreachable] # pylint: disable=import-outside-toplevel,import-error # noqa: E501
             collect_derivatives,
         )
 
@@ -220,6 +233,41 @@ def init_single_subject_wf(subject_id: str):
         name="bids_info",
     )
 
+    summary = pe.Node(
+        SubjectSummary(
+            std_spaces=spaces.get_spaces(nonstandard=False),  # type: ignore[attr-defined] # noqa: E501
+            nstd_spaces=spaces.get_spaces(standard=False),  # type: ignore[attr-defined] # noqa: E501
+        ),
+        name="summary",
+        run_without_submitting=True,
+    )
+
+    about = pe.Node(
+        AboutSummary(version=config.environment.version, command=" ".join(sys.argv)),
+        name="about",
+        run_without_submitting=True,
+    )
+
+    ds_report_summary = pe.Node(
+        DerivativesDataSink(
+            base_directory=str(config.execution.keprep_dir),  # type: ignore[attr-defined] # noqa: E501
+            desc="summary",
+            datatype="figures",
+        ),
+        name="ds_report_summary",
+        run_without_submitting=True,
+    )
+
+    ds_report_about = pe.Node(
+        DerivativesDataSink(
+            base_directory=str(config.execution.keprep_dir),  # type: ignore[attr-defined] # noqa: E501
+            desc="about",
+            datatype="figures",
+        ),
+        name="ds_report_about",
+        run_without_submitting=True,
+    )
+
     # Preprocessing of T1w (includes registration to MNI)
     anat_preproc_wf = init_anat_preproc_wf(
         bids_root=str(config.execution.bids_dir),
@@ -240,6 +288,7 @@ def init_single_subject_wf(subject_id: str):
         t2w=subject_data["t2w"],
         cifti_output=config.workflow.cifti_output,
     )
+    anat_preproc_wf.__desc__ = f"\n\n{anat_preproc_wf.__desc__}"
     # fmt:off
     workflow.connect([
         (inputnode, anat_preproc_wf, [('subjects_dir', 'inputnode.subjects_dir')]),
@@ -248,17 +297,22 @@ def init_single_subject_wf(subject_id: str):
                                     ('t2w', 'inputnode.t2w'),
                                     ('roi', 'inputnode.roi'),
                                     ('flair', 'inputnode.flair')]),
+        (bidssrc, bids_info, [(('t1w', fix_multi_T1w_source_name), 'in_file')]),
+        (inputnode, summary, [('subjects_dir', 'subjects_dir')]),
+        (bids_info, summary, [('subject', 'subject_id')]),
+        (bidssrc, summary, [('t1w', 't1w'),
+                            ('t2w', 't2w'),
+                            ('dwi', 'dwi')]),
+        (bidssrc, ds_report_summary, [
+            (("t1w", fix_multi_T1w_source_name), "source_file"),
+        ]),
+        (summary, ds_report_summary, [("out_report", "in_file")]),
+        (bidssrc, ds_report_about, [
+            (("t1w", fix_multi_T1w_source_name), "source_file")
+        ]),
+        (about, ds_report_about, [("out_report", "in_file")]),
     ])
 
-    if not anat_derivatives:
-        workflow.connect([
-            (bidssrc, bids_info, [(('t1w', fix_multi_T1w_source_name), 'in_file')]),
-        ])
-    else:
-        workflow.connect([ # type: ignore[unreachable]
-            (bidssrc, bids_info, [(('dwi', fix_multi_T1w_source_name), 'in_file')]),
-        ])
-
     # Overwrite ``out_path_base`` of smriprep's DataSinks
     for node in workflow.list_node_names():
         if node.split(".")[-1].startswith("ds_"):
diff --git a/src/keprep/workflows/dwi/descriptions/base.py b/src/keprep/workflows/dwi/descriptions/base.py
new file mode 100644
index 0000000..eb31bbd
--- /dev/null
+++ b/src/keprep/workflows/dwi/descriptions/base.py
@@ -0,0 +1,19 @@
+DIFFUSION_WORKFLOW_DESCRIPTION_MULTI_SESSIONS = """
+**Diffusion data preprocessing**
+
+: For each of the {n_dwi} DWI scans found (across all sessions),
+the following preprocessing was performed.
+
+"""
+
+
+DIFFUSION_WORKFLOW_DESCRIPTION_SINGLE_SESSION = """
+**Diffusion data preprocessing**
+
+The following preprocessing procedures were applied to the DWI scan.
+"""
+
+DENOISING = """Any images with a b-value less than {b0_threshold} s/mm^2 were treated as a b=0 image.
+
+MP-PCA denoising as implemented in MRtrix3's `dwidenoise` [@dwidenoise1] was applied with a {denoise_window}-voxel window.
+"""
diff --git a/src/keprep/workflows/dwi/descriptions/coregister.py b/src/keprep/workflows/dwi/descriptions/coregister.py
new file mode 100644
index 0000000..fd150bd
--- /dev/null
+++ b/src/keprep/workflows/dwi/descriptions/coregister.py
@@ -0,0 +1,19 @@
+COREG_EPIREG = """
+Once previously described confounds were removed,
+a reference mean b=0 image was estimated from the preprocessed DWI series
+to use for co-registration purposes:
+EPI-to-T1w co-registration was performed using Boundary-Based Registration technique,
+as implemented in FSL’s `epi_reg` [@flirt].
+While the resulting transformation matrix was not applied to the DWI series (which was kept in its original space),
+it was inversed and the two matrices are provided for further applications.
+"""
+
+COREG_FLIRT = """
+Once previously described confounds were removed,
+a reference mean b=0 image was estimated from the preprocessed DWI series
+to use for co-registration purposes:
+EPI-to-T1w co-registration was performed using FSL`s `FLIRT` [@flirt], configured with
+{dof} Degrees of Freedom (DOF).
+While the resulting transformation matrix was not applied to the DWI series (which was kept in its original space),
+it was inversed and the two matrices are provided for further applications.
+"""
diff --git a/src/keprep/workflows/dwi/descriptions/eddy.py b/src/keprep/workflows/dwi/descriptions/eddy.py
new file mode 100644
index 0000000..b08c37e
--- /dev/null
+++ b/src/keprep/workflows/dwi/descriptions/eddy.py
@@ -0,0 +1,17 @@
+RPE_DESCRIPTION = """
+Data was collected with reversed phase-encoded directions,
+resulting in pairs of images with distortions going in opposite directions.
+"""
+
+RPE_DWIFSLPREPROC = """Here, the mean b=0 reference image with reversed phase encoding directions was
+used along with a corresponding mean b=0 image extracted from the DWI scans.
+The susceptibility-induced off-resonance field was estimated based on this pair
+using a method similar to that described in [@topup], as implemented in FSL’s [@fsl, RRID:SCR_002823] `topup` [@topup].
+The fieldmaps were ultimately incorporated into the Eddy current and head motion correction conducted using FSL’s `eddy` [@anderssoneddy],
+configured with a no q-space smoothing factor (FWHM = 0), a total of 5 iterations, and 1000 voxels used to estimate hyperparameters.
+A quadratic first level model was used to characterize Eddy current-related spatial distortion.
+Outlier slices were defined as such whose average intensity is at least 4 standard deviations lower than expected intensity,
+where the expectation is given by a Gaussian Process prediction.
+Slices that were deemed as outliers were replaced with predictions made by the Gaussian Process [@eddyrepol].
+Quality control metrices were estimated for this process using eddy QC tools as implemented in `eddy_quad` [@eddyqc].
+"""
diff --git a/src/keprep/workflows/dwi/descriptions/post_eddy.py b/src/keprep/workflows/dwi/descriptions/post_eddy.py
new file mode 100644
index 0000000..ae1c728
--- /dev/null
+++ b/src/keprep/workflows/dwi/descriptions/post_eddy.py
@@ -0,0 +1,4 @@
+DWIBIASCORRECT = """Following the Susceptibility Distortion Correction (SDC),
+B1 field inhomogeneity was corrected using `dwibiascorrect`
+from MRtrix3 with the N4 algorithm [@n4].
+"""
diff --git a/src/keprep/workflows/dwi/stages/coregister.py b/src/keprep/workflows/dwi/stages/coregister.py
index e6d9679..6aaaf44 100644
--- a/src/keprep/workflows/dwi/stages/coregister.py
+++ b/src/keprep/workflows/dwi/stages/coregister.py
@@ -2,8 +2,10 @@
 from nipype.interfaces import fsl
 from nipype.interfaces import mrtrix3 as mrt
 from nipype.interfaces import utility as niu
+from niworkflows.engine.workflows import LiterateWorkflow as Workflow
 
 from keprep import config
+from keprep.workflows.dwi.descriptions.coregister import COREG_EPIREG, COREG_FLIRT
 
 
 def init_dwi_coregister_wf(name: str = "dwi_coregister_wf") -> pe.Workflow:
@@ -20,7 +22,7 @@ def init_dwi_coregister_wf(name: str = "dwi_coregister_wf") -> pe.Workflow:
     pe.Workflow
         the workflow
     """
-    workflow = pe.Workflow(name=name)
+    workflow = Workflow(name=name)
     inputnode = pe.Node(
         niu.IdentityInterface(
             fields=[
@@ -54,20 +56,6 @@ def init_dwi_coregister_wf(name: str = "dwi_coregister_wf") -> pe.Workflow:
         name="apply_mask",
     )
 
-    filrt_node = pe.Node(
-        fsl.FLIRT(
-            dof=config.workflow.dwi2t1w_dof,
-            out_file="dwi2t1w.nii.gz",
-            out_matrix_file="dwi2t1w.mat",
-            searchr_x=[-90, 90],
-            searchr_y=[-90, 90],
-            searchr_z=[-90, 90],
-            cost="normmi",
-            bins=256,
-        ),
-        name="filrt_node",
-    )
-
     convert_xfm = pe.Node(
         fsl.ConvertXFM(
             invert_xfm=True,
@@ -84,45 +72,119 @@ def init_dwi_coregister_wf(name: str = "dwi_coregister_wf") -> pe.Workflow:
         ),
         name="apply_xfm",
     )
+    if config.workflow.dwi2t1w_method == "epireg":
+        coreg_node = pe.Node(fsl.EpiReg(), name="epireg_node")
+        workflow.__desc__ = COREG_EPIREG
+        workflow.connect(
+            [
+                (
+                    inputnode,
+                    apply_mask,
+                    [
+                        ("t1w_preproc", "in_file"),
+                        ("t1w_mask", "mask_file"),
+                    ],
+                ),
+                (
+                    inputnode,
+                    coreg_node,
+                    [("dwi_reference", "epi"), ("t1w_preproc", "t1_head")],
+                ),
+                (
+                    coreg_node,
+                    outputnode,
+                    [
+                        ("out_file", "dwi_in_t1w"),
+                    ],
+                ),
+                (
+                    apply_mask,
+                    coreg_node,
+                    [
+                        ("out_file", "t1_brain"),
+                    ],
+                ),
+                (
+                    coreg_node,
+                    convert_xfm,
+                    [
+                        ("epi2str_mat", "in_file"),
+                    ],
+                ),
+                (
+                    coreg_node,
+                    outputnode,
+                    [
+                        ("epi2str_mat", "dwi2t1w_aff"),
+                    ],
+                ),
+            ]
+        )
+    elif config.workflow.dwi2t1w_method == "flirt":
+        coreg_node = pe.Node(
+            fsl.FLIRT(
+                dof=config.workflow.dwi2t1w_dof,
+                out_file="dwi2t1w.nii.gz",
+                out_matrix_file="dwi2t1w.mat",
+                searchr_x=[-90, 90],
+                searchr_y=[-90, 90],
+                searchr_z=[-90, 90],
+                cost="normmi",
+                bins=256,
+            ),
+            name="flirt_node",
+        )
+        workflow.__desc__ = COREG_FLIRT.format(dof=config.workflow.dwi2t1w_dof)
+        workflow.connect(
+            [
+                (
+                    inputnode,
+                    apply_mask,
+                    [
+                        ("t1w_preproc", "in_file"),
+                        ("t1w_mask", "mask_file"),
+                    ],
+                ),
+                (
+                    inputnode,
+                    coreg_node,
+                    [
+                        ("dwi_reference", "in_file"),
+                    ],
+                ),
+                (
+                    coreg_node,
+                    outputnode,
+                    [
+                        ("out_file", "dwi_in_t1w"),
+                    ],
+                ),
+                (
+                    apply_mask,
+                    coreg_node,
+                    [
+                        ("out_file", "reference"),
+                    ],
+                ),
+                (
+                    coreg_node,
+                    convert_xfm,
+                    [
+                        ("out_matrix_file", "in_file"),
+                    ],
+                ),
+                (
+                    coreg_node,
+                    outputnode,
+                    [
+                        ("out_matrix_file", "dwi2t1w_aff"),
+                    ],
+                ),
+            ]
+        )
 
     workflow.connect(
         [
-            (
-                inputnode,
-                apply_mask,
-                [
-                    ("t1w_preproc", "in_file"),
-                    ("t1w_mask", "mask_file"),
-                ],
-            ),
-            (
-                inputnode,
-                filrt_node,
-                [
-                    ("dwi_reference", "in_file"),
-                ],
-            ),
-            (
-                filrt_node,
-                outputnode,
-                [
-                    ("out_file", "dwi_in_t1w"),
-                ],
-            ),
-            (
-                apply_mask,
-                filrt_node,
-                [
-                    ("out_file", "reference"),
-                ],
-            ),
-            (
-                filrt_node,
-                convert_xfm,
-                [
-                    ("out_matrix_file", "in_file"),
-                ],
-            ),
             (
                 convert_xfm,
                 outputnode,
@@ -130,13 +192,6 @@ def init_dwi_coregister_wf(name: str = "dwi_coregister_wf") -> pe.Workflow:
                     ("out_file", "t1w2dwi_aff"),
                 ],
             ),
-            (
-                filrt_node,
-                outputnode,
-                [
-                    ("out_matrix_file", "dwi2t1w_aff"),
-                ],
-            ),
             (
                 apply_mask,
                 outputnode,
diff --git a/src/keprep/workflows/dwi/stages/derivatives.py b/src/keprep/workflows/dwi/stages/derivatives.py
index 15ec323..85f3291 100644
--- a/src/keprep/workflows/dwi/stages/derivatives.py
+++ b/src/keprep/workflows/dwi/stages/derivatives.py
@@ -54,6 +54,7 @@ def init_derivatives_wf(name: str = "derivatives_wf") -> pe.Workflow:
                 "coreg_report",
                 "unsifted_tck",
                 "sifted_tck",
+                "eddy_qc_plot",
             ]
         ),
         name="inputnode",
@@ -69,6 +70,18 @@ def init_derivatives_wf(name: str = "derivatives_wf") -> pe.Workflow:
         run_without_submitting=True,
     )
 
+    ds_eddy_qc_plot = pe.Node(
+        DerivativesDataSink(
+            base_directory=output_dir,
+            desc="eddyqc",
+            suffix="dwi",
+            datatype="figures",
+            dismiss_entities=["direction"],
+        ),
+        name="ds_eddy_qc_plot",
+        run_without_submitting=True,
+    )
+
     ds_sdc_report = pe.Node(
         DerivativesDataSink(
             base_directory=output_dir,
@@ -189,30 +202,6 @@ def init_derivatives_wf(name: str = "derivatives_wf") -> pe.Workflow:
         run_without_submitting=True,
     )
 
-    ds_unsifted_tck = pe.Node(
-        DerivativesDataSink(
-            base_directory=output_dir,
-            suffix="streamlines",
-            desc="unsifted",
-            extension=".tck",
-            dismiss_entities=["direction"],
-        ),
-        name="ds_unsifted_tck",
-        run_without_submitting=True,
-    )
-
-    ds_sifted_tck = pe.Node(
-        DerivativesDataSink(
-            base_directory=output_dir,
-            suffix="streamlines",
-            desc="sifted",
-            extension=".tck",
-            dismiss_entities=["direction"],
-        ),
-        name="ds_sifted_tck",
-        run_without_submitting=True,
-    )
-
     workflow.connect(
         [
             (
@@ -225,6 +214,11 @@ def init_derivatives_wf(name: str = "derivatives_wf") -> pe.Workflow:
                 ds_eddy_qc,
                 [("out_file", "source_file")],
             ),
+            (
+                inputnode,
+                ds_eddy_qc_plot,
+                [("eddy_qc_plot", "in_file"), ("source_file", "source_file")],
+            ),
             (
                 inputnode,
                 ds_sdc_report,
@@ -291,16 +285,6 @@ def init_derivatives_wf(name: str = "derivatives_wf") -> pe.Workflow:
                 ds_t1w2dwi_aff,
                 [("t1w2dwi_aff", "in_file"), ("source_file", "source_file")],
             ),
-            (
-                inputnode,
-                ds_unsifted_tck,
-                [("unsifted_tck", "in_file"), ("source_file", "source_file")],
-            ),
-            (
-                inputnode,
-                ds_sifted_tck,
-                [("sifted_tck", "in_file"), ("source_file", "source_file")],
-            ),
         ]
     )
 
diff --git a/src/keprep/workflows/dwi/stages/eddy.py b/src/keprep/workflows/dwi/stages/eddy.py
index ce0db9e..5a922b7 100644
--- a/src/keprep/workflows/dwi/stages/eddy.py
+++ b/src/keprep/workflows/dwi/stages/eddy.py
@@ -1,10 +1,13 @@
 import nipype.pipeline.engine as pe
 from nipype.interfaces import mrtrix3 as mrt
 from nipype.interfaces import utility as niu
+from niworkflows.engine.workflows import LiterateWorkflow as Workflow
 
 from keprep import config
 from keprep.interfaces.mrtrix3 import DWIPreproc
+from keprep.workflows.dwi.descriptions.eddy import RPE_DESCRIPTION, RPE_DWIFSLPREPROC
 from keprep.workflows.dwi.stages.extract_b0 import init_extract_b0_wf
+from keprep.workflows.dwi.utils import read_field_from_json
 
 
 def init_eddy_wf(name: str = "eddy_wf") -> pe.Workflow:
@@ -21,8 +24,8 @@ def init_eddy_wf(name: str = "eddy_wf") -> pe.Workflow:
     pe.Workflow
         the workflow
     """
-    workflow = pe.Workflow(name=name)
-
+    workflow = Workflow(name=name)
+    workflow.__desc__ = RPE_DESCRIPTION + RPE_DWIFSLPREPROC
     inputnode = pe.Node(
         niu.IdentityInterface(
             fields=[
@@ -110,16 +113,17 @@ def init_eddy_wf(name: str = "eddy_wf") -> pe.Workflow:
 
     query_pe_dir = pe.Node(
         niu.Function(
-            input_names=["json_file"],
+            input_names=["json_file", "field"],
             output_names=["pe_dir"],
-            function=get_pe_from_json,
+            function=read_field_from_json,
         ),
         name="query_pe_dir",
     )
+    query_pe_dir.inputs.field = "PhaseEncodingDirection"
 
     dwifslpreproc = pe.Node(
         DWIPreproc(
-            eddy_options=" --fwhm=0 --flm='quadratic'",
+            eddy_options=f" {config.workflow.eddy_config}",
             rpe_options="pair",
             align_seepi=True,
             nthreads=config.nipype.omp_nthreads,
@@ -164,24 +168,3 @@ def init_eddy_wf(name: str = "eddy_wf") -> pe.Workflow:
         ]
     )
     return workflow
-
-
-def get_pe_from_json(json_file: str) -> str:
-    """
-    Query the phase encoding direction from a json file.
-
-    Parameters
-    ----------
-    json_file : str
-        path to json file
-
-    Returns
-    -------
-    str
-        phase encoding direction
-    """
-    import json
-
-    with open(json_file) as f:
-        data = json.load(f)
-    return data["PhaseEncodingDirection"]
diff --git a/src/keprep/workflows/dwi/stages/post_eddy.py b/src/keprep/workflows/dwi/stages/post_eddy.py
index e9e79b9..7c01d82 100644
--- a/src/keprep/workflows/dwi/stages/post_eddy.py
+++ b/src/keprep/workflows/dwi/stages/post_eddy.py
@@ -1,10 +1,13 @@
 import nipype.pipeline.engine as pe
 from nipype.interfaces import mrtrix3 as mrt
 from nipype.interfaces import utility as niu
+from niworkflows.engine.workflows import LiterateWorkflow as Workflow
 
 from keprep import config
 from keprep.interfaces.mrtrix3 import MRConvert
+from keprep.workflows.dwi.descriptions.post_eddy import DWIBIASCORRECT
 from keprep.workflows.dwi.stages.extract_b0 import init_extract_b0_wf
+from keprep.workflows.dwi.utils import plot_eddy_qc
 
 
 def init_post_eddy_wf(name: str = "post_eddy_wf") -> pe.Workflow:
@@ -21,12 +24,13 @@ def init_post_eddy_wf(name: str = "post_eddy_wf") -> pe.Workflow:
     pe.Workflow
         the workflow
     """
-    workflow = pe.Workflow(name=name)
-
+    workflow = Workflow(name=name)
+    workflow.__desc__ = DWIBIASCORRECT
     inputnode = pe.Node(
         niu.IdentityInterface(
             fields=[
                 "dwi_preproc",
+                "eddy_qc",
             ]
         ),
         name="inputnode",
@@ -43,18 +47,38 @@ def init_post_eddy_wf(name: str = "post_eddy_wf") -> pe.Workflow:
                 "dwi_json",
                 "dwi_reference",
                 "dwi_reference_json",
+                "eddy_qc_plot",
             ]
         ),
         name="outputnode",
     )
 
-    bias_correct = pe.Node(
-        mrt.DWIBiasCorrect(
-            out_file="bias_corrected.mif",
-            use_ants=True,
-            nthreads=config.nipype.omp_nthreads,
+    plot_eddy_qc_node = pe.Node(
+        niu.Function(
+            input_names=["eddy_qc", "out_file"],
+            output_names=["out_file"],
+            function=plot_eddy_qc,
         ),
-        name="bias_correct",
+        name="plot_eddy_qc",
+    )
+    plot_eddy_qc_node.inputs.out_file = "eddy_qc_plot.svg"
+    workflow.connect(
+        [
+            (
+                inputnode,
+                plot_eddy_qc_node,
+                [
+                    ("eddy_qc", "eddy_qc"),
+                ],
+            ),
+            (
+                plot_eddy_qc_node,
+                outputnode,
+                [
+                    ("out_file", "eddy_qc_plot"),
+                ],
+            ),
+        ]
     )
 
     mrconvert_dwi = pe.Node(
@@ -68,30 +92,60 @@ def init_post_eddy_wf(name: str = "post_eddy_wf") -> pe.Workflow:
         ),
         name="mrconvert_dwi",
     )
+    if config.workflow.dwi_no_biascorr:
+        workflow.connect(
+            [
+                (
+                    inputnode,
+                    mrconvert_dwi,
+                    [
+                        ("dwi_preproc", "in_file"),
+                    ],
+                ),
+                (
+                    inputnode,
+                    outputnode,
+                    [("dwi_preproc", "dwi_mif")],
+                ),
+            ]
+        )
+    else:
+        bias_correct = pe.Node(
+            mrt.DWIBiasCorrect(
+                out_file="bias_corrected.mif",
+                use_ants=True,
+                nthreads=config.nipype.omp_nthreads,
+            ),
+            name="bias_correct",
+        )
+        workflow.connect(
+            [
+                (
+                    inputnode,
+                    bias_correct,
+                    [
+                        ("dwi_preproc", "in_file"),
+                    ],
+                ),
+                (
+                    bias_correct,
+                    mrconvert_dwi,
+                    [
+                        ("out_file", "in_file"),
+                    ],
+                ),
+                (
+                    bias_correct,
+                    outputnode,
+                    [
+                        ("out_file", "dwi_mif"),
+                    ],
+                ),
+            ]
+        )
 
     workflow.connect(
         [
-            (
-                inputnode,
-                bias_correct,
-                [
-                    ("dwi_preproc", "in_file"),
-                ],
-            ),
-            (
-                bias_correct,
-                mrconvert_dwi,
-                [
-                    ("out_file", "in_file"),
-                ],
-            ),
-            (
-                bias_correct,
-                outputnode,
-                [
-                    ("out_file", "dwi_mif"),
-                ],
-            ),
             (
                 mrconvert_dwi,
                 outputnode,
diff --git a/src/keprep/workflows/dwi/utils.py b/src/keprep/workflows/dwi/utils.py
new file mode 100644
index 0000000..902d53e
--- /dev/null
+++ b/src/keprep/workflows/dwi/utils.py
@@ -0,0 +1,157 @@
+def read_field_from_json(json_file, field):
+    """Read a field from a JSON file."""
+    import json
+
+    with open(json_file, "r") as f:
+        data = json.load(f)
+    return data[field]
+
+
+def calculate_denoise_window(dwi_file: str) -> int:
+    """
+    select the smallest isotropic patch size that exceeds the number of
+    DW images in the input data, e.g., 5x5x5 for data with <= 125 DWI volumes,
+    7x7x7 for data with <= 343 DWI volumes, etc. Must be an odd number.
+
+    Parameters
+    ----------
+    dwi_file : str
+        path to dwi file
+
+    Returns
+    -------
+    int
+        window size for dwidenoise
+    """
+    import nibabel as nib
+    import numpy as np
+
+    img = nib.load(dwi_file)
+    n_volumes = img.shape[-1]  # type: ignore[attr-defined]
+    window_size = int(np.ceil(n_volumes ** (1 / 3)))
+    if window_size % 2 == 0:
+        window_size += 1
+    return window_size
+
+
+def plot_eddy_qc(
+    eddy_qc: str,
+    out_file: str,
+    dpi: int = 300,
+):
+    """
+    Plot the eddy QC.
+
+    Parameters
+    ----------
+    eddy_qc : str
+        path to the eddy qc file
+    out_file : str
+        path to the output file
+    title : str, optional
+        title of the plot (default: "Eddy QC")
+    dpi : int, optional
+        dpi of the plot (default: 300)
+    """
+    import os
+    from pathlib import Path
+
+    import matplotlib.pyplot as plt
+    import numpy as np
+    import pandas as pd
+    import seaborn as sns
+
+    sns.set_style("whitegrid")
+    sns.set_context("paper", font_scale=1.5)
+    sns.set_palette("bright")
+
+    eddy_qc = Path(eddy_qc)  # type: ignore[assignment]
+    params = np.genfromtxt(eddy_qc / "eddy_parameters", dtype=float)  # type: ignore[type-var, operator] # noqa: E501
+    motion = np.genfromtxt(eddy_qc / "eddy_movement_rms", dtype=float)  # type: ignore[type-var, operator] # noqa: E501
+
+    df_params = pd.DataFrame(
+        {
+            "x": params[:, 0],
+            "y": params[:, 1],
+            "z": params[:, 2],
+        }
+    )
+    df_params["type"] = "absolute"
+    df_params["volume"] = np.arange(df_params.shape[0])
+    # add relative motion from columns 3 to 5 as new lines
+    df_params = pd.concat(
+        [
+            df_params,
+            pd.DataFrame(
+                {
+                    "x": params[:, 3],
+                    "y": params[:, 4],
+                    "z": params[:, 5],
+                    "type": "relative",
+                    "volume": np.arange(df_params.shape[0]),
+                }
+            ),
+        ]
+    )
+    df_params = df_params.melt(
+        id_vars=["volume", "type"],
+        value_vars=["x", "y", "z"],
+        var_name="direction",
+        value_name="displacement",
+    )
+
+    fig_props = {
+        "absolute": {
+            "title": "Eddy estimated translations (mm)",
+            "ylabel": "Translation [mm]",
+        },
+        "relative": {
+            "title": "Eddy estimated rotations (deg)",
+            "ylabel": "Rotation [deg]",
+        },
+    }
+
+    fig, axes = plt.subplots(3, 1, figsize=(10, 15))
+    for i, movement_type in enumerate(["absolute", "relative"]):
+        _ = sns.lineplot(
+            data=df_params[df_params["type"] == movement_type],
+            x="volume",
+            y="displacement",
+            hue="direction",
+            ax=axes[i],  # type: ignore[index]
+            palette={"x": "r", "y": "g", "z": "b"},
+            linewidth=2,
+        )
+        axes[i].set_xlabel("Volume")  # type: ignore[index]
+        axes[i].set_ylabel(fig_props[movement_type]["ylabel"])  # type: ignore[index]
+        axes[i].set_title(  # type: ignore[index]
+            fig_props[movement_type]["title"], fontweight="bold", fontsize=20
+        )
+
+    df_motion = pd.DataFrame(motion, columns=["Absolute", "Relative"])
+    df_motion["Volume"] = np.arange(df_motion.shape[0])
+    df_motion = df_motion.melt(
+        id_vars=["Volume"], var_name="Type", value_name="Displacement"
+    )
+    _ = sns.lineplot(
+        data=df_motion,
+        x="Volume",
+        y="Displacement",
+        hue="Type",
+        ax=axes[2],  # type: ignore[index]
+        linewidth=2,
+        palette={"Absolute": "r", "Relative": "b"},
+    )
+    axes[2].set_xlabel("Volume")  # type: ignore[index]
+    axes[2].set_ylabel("Displacement [mm]")  # type: ignore[index]
+    axes[2].set_title("Estimated mean displacement", fontweight="bold", fontsize=20)  # type: ignore[index] # noqa: E501
+    axes[2].legend(loc="best", frameon=True, framealpha=0.5)  # type: ignore[index]
+    axes[2].set_ylim(0, 0.5 + np.max(df_motion["Displacement"]))  # type: ignore[index]
+    plt.tight_layout()
+
+    # save the plot with transparent background
+    out_file = os.getcwd() + "/" + out_file
+    plt.savefig(out_file, dpi=dpi, bbox_inches="tight", transparent=True)
+    plt.close()
+
+    return out_file
diff --git a/src/keprep/workflows/dwi/workflow.py b/src/keprep/workflows/dwi/workflow.py
index d841323..addf42e 100644
--- a/src/keprep/workflows/dwi/workflow.py
+++ b/src/keprep/workflows/dwi/workflow.py
@@ -3,13 +3,22 @@
 from bids import BIDSLayout
 from nipype.interfaces import utility as niu
 from nipype.pipeline import engine as pe
+from niworkflows.engine.workflows import LiterateWorkflow as Workflow
 
 from keprep import config
 from keprep.interfaces.bids import get_fieldmap
+from keprep.interfaces.bids.bids import DerivativesDataSink
+from keprep.interfaces.reports.reports import DiffusionSummary
+from keprep.workflows.dwi.descriptions.base import (
+    DENOISING,
+    DIFFUSION_WORKFLOW_DESCRIPTION_MULTI_SESSIONS,
+    DIFFUSION_WORKFLOW_DESCRIPTION_SINGLE_SESSION,
+)
 from keprep.workflows.dwi.stages.coregister import init_dwi_coregister_wf
 from keprep.workflows.dwi.stages.derivatives import init_derivatives_wf
 from keprep.workflows.dwi.stages.eddy import init_eddy_wf
 from keprep.workflows.dwi.stages.post_eddy import init_post_eddy_wf
+from keprep.workflows.dwi.utils import calculate_denoise_window, read_field_from_json
 
 
 def init_dwi_preproc_wf(dwi_file: str | Path, subject_data: dict):
@@ -35,7 +44,7 @@ def init_dwi_preproc_wf(dwi_file: str | Path, subject_data: dict):
         raise FileNotFoundError(f"No fieldmap found for <{dwi_file}>")
 
     # Build workflow
-    workflow = pe.Workflow(name=_get_wf_name(dwi_file))
+    workflow = Workflow(name=_get_wf_name(dwi_file))
 
     inputnode = pe.Node(
         niu.IdentityInterface(
@@ -67,13 +76,84 @@ def init_dwi_preproc_wf(dwi_file: str | Path, subject_data: dict):
     inputnode.inputs.fmap_bvec = Path(layout.get_bvec(fieldmap))
     inputnode.inputs.fmap_bval = Path(layout.get_bval(fieldmap))
     inputnode.inputs.fmap_json = Path(layout.get_nearest(fieldmap, extension="json"))
-
     outputnode = pe.Node(  # noqa: F841
         niu.IdentityInterface(
             fields=["dwi_preproc", "dwi_reference", "dwi_mask"],
         ),
         name="outputnode",
     )
+
+    if (
+        config.workflow.denoise_method == "dwidenoise"
+        and config.workflow.dwi_denoise_window == "auto"
+    ):
+        dwi_denoise_window = calculate_denoise_window(dwi_file)  # type: ignore[arg-type] # noqa: E501
+    n_dwis = len(subject_data["dwi"])
+    desc = (
+        DIFFUSION_WORKFLOW_DESCRIPTION_MULTI_SESSIONS
+        if n_dwis > 1
+        else DIFFUSION_WORKFLOW_DESCRIPTION_SINGLE_SESSION
+    )
+    workflow.__desc__ = desc.format(n_dwi=n_dwis) + DENOISING.format(
+        b0_threshold=config.workflow.b0_threshold, denoise_window=dwi_denoise_window
+    )
+
+    bo_to_t1w = "Rigid" if config.workflow.dwi2t1w_dof == 6 else "Affine"
+    summary = pe.Node(
+        DiffusionSummary(
+            distortion_correction="TOPUP",
+            hmc_model=config.workflow.hmc_model,
+            b0_to_t1w_transform=bo_to_t1w,
+            denoise_method=config.workflow.denoise_method,
+            dwi_denoise_window=dwi_denoise_window,
+        ),
+        name="summary",
+        run_without_submitting=True,
+    )
+
+    read_pe_direction = pe.Node(
+        niu.Function(
+            input_names=["json_file", "field"],
+            output_names=["pe_dir"],
+            function=read_field_from_json,
+        ),
+        name="read_pe_direction",
+    )
+    read_pe_direction.inputs.field = "PhaseEncodingDirection"
+
+    # Reporting
+    ds_report_summary = pe.Node(
+        DerivativesDataSink(
+            base_directory=str(config.execution.keprep_dir),  # type: ignore[attr-defined] # noqa: E501
+            datatype="figures",
+            suffix="dwi",
+            desc="summary",
+            source_file=dwi_file,
+            dismiss_entities=["direction"],
+        ),
+        name="ds_report_summary",
+        run_without_submitting=True,
+    )
+    workflow.connect(
+        [
+            (
+                inputnode,
+                read_pe_direction,
+                [("dwi_json", "json_file")],
+            ),
+            (
+                read_pe_direction,
+                summary,
+                [("pe_dir", "pe_direction")],
+            ),
+            (
+                summary,
+                ds_report_summary,
+                [("out_report", "in_file")],
+            ),
+        ]
+    )
+
     dwi_conversion_to_mif_node = pe.Node(
         interface=mrt.MRConvert(
             out_file="dwi.mif", nthreads=config.nipype.omp_nthreads
@@ -86,6 +166,7 @@ def init_dwi_preproc_wf(dwi_file: str | Path, subject_data: dict):
         ),
         name="fmap_mifconv",
     )
+
     workflow.connect(
         [
             (
@@ -115,7 +196,8 @@ def init_dwi_preproc_wf(dwi_file: str | Path, subject_data: dict):
     dwi_denoise_node = pe.Node(
         interface=mrt.DWIDenoise(
             out_file="dwi_denoised.mif",
-            noise="noise.mif",
+            extent=(dwi_denoise_window, dwi_denoise_window, dwi_denoise_window),
+            noise="noise.nii.gz",
             nthreads=config.nipype.omp_nthreads,
         ),
         name="dwi_denoise",
@@ -160,6 +242,7 @@ def init_dwi_preproc_wf(dwi_file: str | Path, subject_data: dict):
                 post_eddy,
                 [
                     ("outputnode.dwi_preproc", "inputnode.dwi_preproc"),
+                    ("outputnode.eddy_qc", "inputnode.eddy_qc"),
                 ],
             ),
         ]
@@ -270,6 +353,7 @@ def init_dwi_preproc_wf(dwi_file: str | Path, subject_data: dict):
                         "outputnode.dwi_reference_json",
                         "inputnode.dwi_reference_json",
                     ),
+                    ("outputnode.eddy_qc_plot", "inputnode.eddy_qc_plot"),
                 ],
             ),
             (
@@ -314,4 +398,4 @@ def _get_wf_name(filename):
 
     fname = Path(filename).name.rpartition(".nii")[0].replace("_dwi", "_wf")
     fname_nosub = "_".join(fname.split("_")[1:])
-    return f"dwi_preproc_{fname_nosub.replace('.', '_').replace(' ', '').replace('-', '_')}"
+    return f"dwi_preproc_{fname_nosub.replace('.', '_').replace(' ', '').replace('-', '_')}"  # noqa: E501
diff --git a/tox.ini b/tox.ini
index ffb8409..0d793c0 100644
--- a/tox.ini
+++ b/tox.ini
@@ -46,8 +46,12 @@ commands =
     sphinx-build -b html docs docs/build
 
 [testenv:report]
-deps = coverage
+deps =
+    coverage
+    pytest
+    .
 skip_install = true
 commands =
-    coverage report
+    coverage run --source keprep -m pytest
+    coverage report -m
     coverage html