arXiv Computer Vision
Zero-Shot Brain MRI Inpainting with 2.5D Unconditional Flow Priors
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RARF: Region-Aware Rectified Flows for 3D Brain MRI Inpainting
RARF is a task‑agnostic, region‑aware rectified flow framework designed for 3D brain MRI inpainting. It limits stochastic interpolation to the inpainting region while keeping observed voxels fixed, using a 3D neural network that processes a partially voided image, Gaussian noise, a mask, and a timestep. The model is trained with masked flow‑matching and reconstruction‑consistency objectives, and during inference it transports noise toward a plausible reconstruction that preserves anatomical consistency, achieving competitive results on the BraTS Inpainting Challenge 2026.
arXiv Machine Learning
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Lesion-DDPM: Lesion-Enhanced 3D Diffusion for MS MRI Synthesis
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arXiv Computer Vision
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UniPro: Unified Multi-Mode Medical Image Segmentation from 2D Images to 3D Volumes via Propagation
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CIRSeg: Coarse-to-Fine Intensity-Robust Liver Segmentation with Source-Free Continual Test-Time Adaptation
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arXiv AI
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Longitudinal Lesion Inpainting in Brain MRI via 3D Region Aware Diffusion
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Hugging Face Trending Papers
Jul 20
SAMRI-3D: Adapting SAM2 for 3D MRI Segmentation with Global Volume Tokens
Foundation models such as Segment Anything Model 2 (SAM2) have transformed natural-image and video segmentation, and recent work has begun adapting them to medical imaging. These adaptations, however, are largely general-purpose models that treat MRI as one modality among many; large-scale, MRI-specific modelling and benchmarking remain limited, even though MRI's low soft-tissue contrast leaves many boundaries effectively invisible on individual slices.