The MAMA-MIA Challenge: Advancing Generalizability and Fairness in Breast MRI Tumor Segmentation and Treatment Response Prediction
cs.CV, cs.AI
Submitted: 2026-03-01
Updated: 2026-09-18
Code: https://github.com/jojoka-234/mama-mia-challenge
Project page: https://www.ub.edu/mama-mia
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Terminology
Sources
- Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge
- An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
- Decoupled Weight Decay Regularization
- A generalizable 3D framework and model for self-supervised learning in medical imaging
- Deep Residual Learning for Image Recognition
- A Closer Look at Spatiotemporal Convolutions for Action Recognition
- Adam: A Method for Stochastic Optimization
- A Simple Framework for Contrastive Learning of Visual Representations
- Tune: A Research Platform for Distributed Model Selection and Training
- Mamba: Linear-Time Sequence Modeling with Selective State Spaces
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