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 | MERIT | Avg DSC | 84.9 | — | Unverified |
| 2 | MERIT-GCASCADE | Avg DSC | 84.54 | — | Unverified |
| 3 | RWKV-UNet | Avg DSC | 84.02 | — | Unverified |
| 4 | EMCAD | Avg DSC | 83.63 | — | Unverified |
| 5 | PVT-GCASCADE | Avg DSC | 83.28 | — | Unverified |
| 6 | TransCASCADE | Avg DSC | 82.68 | — | Unverified |
| 7 | 3D Att-UNet-MTL-TSOL | Avg DSC | 82 | — | Unverified |
| 8 | PVT-CASCADE | Avg DSC | 81.06 | — | Unverified |