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 | Hi-gMISnet | F1 | 93.25 | — | Unverified |
| 2 | MDM | F1 | 91.95 | — | Unverified |
| 3 | UCTransNet | F1 | 90.18 | — | Unverified |
| 4 | Trans2Unet | F1 | 89.84 | — | Unverified |
| 5 | U-Net++ | F1 | 87.56 | — | Unverified |
| 6 | U-Net | F1 | 85.45 | — | Unverified |
| 7 | MedT | F1 | 81.02 | — | Unverified |
| 8 | LoGo | F1 | 79.68 | — | Unverified |
| 9 | HistoSeg | IoU | 76.73 | — | Unverified |
| 10 | U-Net | F1 | 76.26 | — | Unverified |