The MAMA-MIA Dataset: A Multi-Center Breast Cancer DCE-MRI Public Dataset with Expert Segmentations
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Apr 16, 2025 - Jupyter Notebook
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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
Code for the Extended Reference Region Model for DCE-MRI (NBM 3924)
Code for Reference Region and Input Function Tail method for DCE-MRI (MRM 27913)
Official repository of "Towards Learning Contrast Kinetics with Multi-Condition Latent Diffusion Models"
Various functions for processing DCE-MRI data and performing simulations.
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.
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
General utility functions written in MATLAB as part of a software toolkit for analyzing dynamic contrast-enhanced magnetic resonance imaging (dce-mri) data.
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