MID: Mask-Image Distributional Divergence for Evaluating Medical Image Segmentation
cs.CV, cs.AI
Submitted: 2026-10-12
Updated: 2026-10-15
Code: https://github.com/erc-caravel/pytorch-mid
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Sources
- On the Evaluation of Conditional GANs
- A2V: A Semi-Supervised Domain Adaptation Framework for Brain Vessel Segmentation via Two-Phase Training Angiography-to-Venography Translation
- nnInteractive: Redefining 3D Promptable Segmentation
- UniMed-CLIP: Towards a Unified Image-Text Pretraining Paradigm for Diverse Medical Imaging Modalities
- MedSAM2: Segment Anything in 3D Medical Images and Videos
- SPOCKMIP: Segmentation of Vessels in MRAs with Enhanced Continuity using Maximum Intensity Projection as Loss
- MedGemma Technical Report
- SAM-Med3D: Towards General-purpose Segmentation Models for Volumetric Medical Images
- BiomedCLIP: a multimodal biomedical foundation model pretrained from fifteen million scientific image-text pairs
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