Medical Image Segmentation
Medical Image Segmentation is a computer vision task that involves dividing an medical image into multiple segments, where each segment represents a different object or structure of interest in the image. The goal of medical image segmentation is to provide a precise and accurate representation of the objects of interest within the image, typically for the purpose of diagnosis, treatment planning, and quantitative analysis.
( Image credit: IVD-Net )
Papers
Showing 1–10 of 2089 papers
All datasetsKvasir-SEGCVC-ClinicDBCVC-ColonDBETIS-LARIBPOLYPDBSynapse multi-organ CTAutomatic Cardiac Diagnosis Challenge (ACDC)MoNuSeg2018 Data Science BowlGlaSBKAI-IGH NeoPolyp-SmallMICCAI 2015 Multi-Atlas Abdomen Labeling ChallengeACDC
Benchmark Results
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | Interactive AI-SAM gt box | Avg DSC | 90.66 | — | Unverified |
| 2 | Medical SAM Adapter | Avg DSC | 89.8 | — | Unverified |
| 3 | MedSegDiff-v2 | Avg DSC | 89.5 | — | Unverified |
| 4 | nnUNet | Avg DSC | 88.8 | — | Unverified |
| 5 | MedNeXt-L (5x5x5) | Avg DSC | 88.76 | — | Unverified |
| 6 | MIST | Avg DSC | 86.92 | — | Unverified |
| 7 | nnFormer | Avg DSC | 86.57 | — | Unverified |
| 8 | AgileFormer | Avg DSC | 86.11 | — | Unverified |
| 9 | MERIT | Avg DSC | 84.9 | — | Unverified |
| 10 | Automatic AI-SAM | Avg DSC | 84.21 | — | Unverified |