Hugging Face Trending Papers
Continual pretraining Prostate MRI ViT Encoder for task alignment
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arXiv Machine Learning
Oct 15
Continual pretraining Prostate MRI ViT Encoder for task alignment
arXiv:2610.20217v1 Announce Type: cross Abstract: Building foundation models for MRI has emerged as a promising direction for advancing medical image analysis and improving accessibility of task spec...
arXiv Computer Vision
Oct 27
Masked and Predictive Self-Supervised Pretraining for Brain MRI: Effects of Objective Design on Disease Detection
arXiv:2606.13315v2 Announce Type: replace Abstract: MRI self-supervised learning (SSL) has largely emphasized segmentation and dense prediction, while controlled studies of how alternative pretrainin...
arXiv AI
Sep 1
MR-JEPA: A General Purpose Video Foundation Model for Cardiac MRI
arXiv:2608.30975v1 Announce Type: cross Abstract: Cardiac magnetic resonance imaging (CMR) produces rich sequential data such as temporal cine videos and spatial LGE/mapping stacks, yet most deep lea...
arXiv AI
Aug 21
MambaX-Net: Dual-Input Mamba-Enhanced Cross-Attention Network for Longitudinal Prostate MRI Segmentation
arXiv:2510. 17529v3 Announce Type: replace-cross Abstract: Active Surveillance (AS) is a treatment option for managing low and intermediate-risk prostate cancer (PCa), aiming to avoid overtreatment while monitoring disease progression through serial MRI and clinical follow-up.
arXiv AI
Jul 21
BrainNext: A General-Purpose Self-Supervised Foundation Model for Brain MRI Analysis
arXiv:2607. 17782v1 Announce Type: cross Abstract: Foundation models pretrained using self-supervised learning have transformed computer vision by learning transferable representations from large-scale unlabeled data.
arXiv Computer Vision
Aug 25
Tumor-aware augmentation with task-guided attention analysis improves rectal cancer segmentation from magnetic resonance images
arXiv:2605.05522v3 Announce Type: replace-cross Abstract: Although self-supervised pretraining is expected to learn broadly transferable representations, its effectiveness across imaging modalities s...