NeuroKit2: The Python Toolbox for Neurophysiological Signal Processing
Koma is a GPU-accelerated, Pulseq-compatible framework for simulating Magnetic Resonance Imaging (MRI) acquisitions. The primary focus of this package is to simulate the wide range of scenarios encountered during pulse sequence development.
Segment Source Distribution
MICCAI 2023 code for the paper: Feature-Conditioned Cascaded Video Diffusion Models for Precise Echocardiogram Synthesis. EchoDiffusion is a collection of video diffusion models trained from scratch on the EchoNet-Dynamic dataset with the imagen-pytorch repo.
A Vision Foundation Model for Cine Cardiac Magnetic Resonance Imaging
Python Cardioception Package - Measuring interoceptive performance with Psychopy
Code for the analysis of cardiac motion and cardiac pathology classification
Machine Learning project to predict heart diseases
[STACOM-MICCAI 2019] Deep Learning Registration for Cardiac Motion Tracking
Learned Half-Quadratic Splitting Network for Magnetic Resonance Image Reconstruction
[Robust cardiac MR image segmentation foundation model] This code contains the most powerful cardiac segmentation model trained from UK biobank dataset with superior performance on out-of-domain datasets. This model can be used out-of-box, and serve as a foundation model for further finetuning
A Python package for AI-based comprehensive analysis of sarcomere structure and function in cardiomyocytes
Cardiac Electrophysiology solver in FEniCSx
Exercise Physiology Equations
Source code for Aladdin, a complete workflow for 3D MRI left atrium motion analysis
[MICCAI 2025] CardiacCLIP: Video-based CLIP Adaptation for LVEF Prediction in a Few-shot Manner
A library to calculate parametric maps in MRI. For details see https://doi.org/10.1016/j.softx.2019.100369
INDI is a command line tool to process in-vivo cardiac diffusion tensor imaging.
Cardiac Action Potential Prediction (ApPredict) under drug-induced block of ion channels. This is a Chaste extension/bolt-on project.