The MAMA-MIA Dataset: A Multi-Center Breast Cancer DCE-MRI Public Dataset with Expert Segmentations

Temporal-spatial Feature Learning of DCE-MR Images via 3DCNN

DCE MRI analysis in Julia

Official repository for "Pre- to Post-Contrast Breast MRI Synthesis for Enhanced Tumour Segmentation"

Simple Linear Iterative Clustering adapted for 4D DCE-MRI or other perfusion imaging

Official repository of "Towards Learning Contrast Kinetics with Multi-Condition Latent Diffusion Models"

BreastDCEDL Pretreatment MRI scans of 2070 Breast cancer patients. A Deep Learning-Ready DCE-MRI Breast Cancer Dataset from I-SPY2 and I-SPY1 trials (1,2 and DUKE.

Code for Reference Region and Input Function Tail method for DCE-MRI (MRM 27913)

Code for the Extended Reference Region Model for DCE-MRI (NBM 3924)

Various functions for processing DCE-MRI data and performing simulations.

Estimation of bolus arrival times for DCE-MRI signals

Code for Constrained Reference Region Models for DCE-MRI (MRM 26530)

Computational modeling of convection enhanced delivery in heterogeneous vasculature of human brain tumors to maximize drug efficacy and select best combination of drugs for specific patient using CFD simulation in OpenFOAM

A comprehensive pipeline for the analysis of dynamic contrast-enhanced MRI (DCE-MRI) data from the MAMA-MIA public dataset. Includes biomarker extraction, pseudo-color map generation, and multicenter signal harmonization using ComBat. Developed for educational purposes at the Hellenic Mediterranean University by Kalaitzakis Nikolaos.

General utility functions written in MATLAB as part of a software toolkit for analyzing dynamic contrast-enhanced magnetic resonance imaging (dce-mri) data.