Collection of code for detection and modeling of jumps (WIP)

A python code to convert microstructure meshes to voxel grids.

A collection of functions work together to analyze, visualize, and save data about particles in segmented images, including their statistics, identifying clusters, and connection pathways and providing associated stats.

Running SPPARKS (Stochastic Parallel Particle Kinetic Simulator) on HPC system

A code that analyses grains from microstructure images, providing informations such as number of grains and grain size

This project is about generating 3D microstructure images with specified porosity and surface area values.

Generative model variational autoencoder (VAE) implementation for the predictions of phase separation in binary alloys

A Python class for computing Wicksell's transforms of continuous distributions

Optimising microstructures numerically (OMicroN). Full field physics-based simulation package for metallic microstructure during treatments. The package includes solid state transformations (phase transformations, recrystallization, grain growth) as well as solute redistribution (carbon partitioning / diffusion / trapping to defects).

Generate random ellipses that cover an area

Uses a convolution neural network to classify titanium microstructures

This code allows combining the spatial distribution coming from multiple secondary ions maps obtained through time-of-flight secondary ion mass spectrometry (ToF-SIMS) into a single image and segmenting it (i.e., every pixel is assigned to one SI/phase only).

Microstructure vision-based porosity analysis

Computing (optimal) anisotropic power diagrams using GPU acceleration

Predictions of fabric descriptors in dual phase cements

An Intelligence Device Used to Detect and Autofocus 3D Microstructures from Ordinary Optical Microscope

[Siggraph Asia 2024] Optimized shock-protecting microstructures

Stimulated echo diffusion weighted data in fixed pig spinal cord

This software package processes segmented cross-sectional scanning electron microscopy (SEM) images to estimate features observed by a photomultiplier tube (PMT). The primary goal is to analyze large microstructure images by superimposing randomly placed rectangular fields of observation and computing statistics on the features within these fields.

Folder containing all implemented or developed quantitative spinal cord imaging pipelines and data analyses