NeuroKit2: The Python Toolbox for Neurophysiological Signal Processing

Koma is a Pulseq-compatible framework to efficiently simulate Magnetic Resonance Imaging (MRI) acquisitions. The main focus of this package is to simulate general scenarios that could arise in 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.

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

Exercise Physiology Equations

A library to calculate parametric maps in MRI. For details see https://doi.org/10.1016/j.softx.2019.100369

[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

This is an implementation of unsupervised multiple kernel learning (U-MKL) for dimensionality reduction, which builds upon a supervised MKL technique by Lin et al (10.1109/TPAMI.2010.183).

Source code for Aladdin, a complete workflow for 3D MRI left atrium motion analysis

Cardiac Action Potential Prediction (ApPredict) under drug-induced block of ion channels. This is a Chaste extension/bolt-on project.

Next generation cardiac mechanics solver based on FEniCSx

Tool for creating idealised cardiac geometries and microstructure

Free-breathing myocardial T1 mapping with Physically-Constrained Motion Correction

GPU implementation of a Full Search Block Matching Motion Estimation Algorithm

Project to study sound stimulus synchronous, asynchronous and isochronous with the heartbeat during sleep.

Sussex Psychophysiology Research Protocol (SuPREP)