Federated learning with homomorphic encryption enables multiple parties to securely co-train artificial intelligence models in pathology and radiology, reaching state-of-the-art performance with privacy guarantees.

The following is a new architecture for robust segmentation. It may perform better than a U-Net :) for binary segmentation. I will update the code when I have some spare time within the next month. However you can simply read this one and will soon notice the pattern after a bit

Transformer-based Models for Unsupervised Anomaly Segmentation in Brain MR Images

Neural network-based preprocessing of MRI data: Prepping brain images in seconds 🔥

Codebase for Conditioned Diffusion Models for Unsupervised Anomaly Detection

mrQA: tools for quality assurance in medical imaging datasets, including protocol compliance

A brain MRI segmentation tool that provides accurate robust segmentation of problematic brain regions across the neurodegenerative spectrum. The methodology is generalisable to perform well with the typical variance in MRI acquisition parameters and other factors that influence image contrast.

Official implementation of the paper "Challenging Current Semi-Supervised Anomaly Segmentation Methods for Brain MRI" accepted to the MICCAI 2021 BrainLes workshop

Non-parametric T2 relaxometry methods for myelin water quantification

Synthetic FLAIR generation software

Codebase for Unsupervised Anomaly Detection using Aggregated Normative Diffusion (ANDi)

This is my Master thesis work at TU Delft, to longitudinally segment the MRI brain image series by 4D network.

[WACV'25] Official implementation of "PK-YOLO: Pretrained Knowledge Guided YOLO for Brain Tumor Detection in Multiplane MRI Slices".

This is the repository that accompanies the manuscript "Deep Learning of MRI Contrast Enhancement for Mapping Cerebral Blood Volume from Single-Modal Non-Contrast Scans of Aging and Alzheimer's Disease Brains" accepted for publication in Frontiers in Aging Neuroscience, section Neurocognitive Aging and Behavior (July-18-2022).

This repository aims to present a general, customazible pipeline for MRI images based on a single configuration file (in .json format) that has different flags and according to them, a certain pre-processing procedure with desired steps is performed.

An application to visualize 3D medical images, including MRI and PET scans, with dynamic enhancement features to improve visual analysis​.

Federated implementation of a CNN to predict brain age from MRI-derived gray matter

Pre-clinical DSC-MRI perfusion map generator written in Python

This is a repository hosting all models detailed in the article Brain tumour segmentation with incomplete imaging data.

A python wrapper for FLIRT MRI registration