SAMI3D-DW: Interactive Segmentation of Any 3D Medical Images
Interactive segmentation of 3D medical images supports quantitative analysis of anatomical structures and disease while allowing users to specify and refine their targets. Despite substantial progress by nnInteractive and VISTA3D, reliable segmentation across diverse clinical targets remains challenging, particularly for complex anatomical structures and the heterogeneous, long-tailed spectrum of pathology. We present SAMI3D-DW V1 (hereafter SAMI3D-DW), an interactive 3D segmentation model trained on Deepwise's large-scale proprietary medical image datasets. We evaluate the model under simulated user interactions on a CT/MR benchmark comprising 4,326 cases from 219 source datasets, spanni...
| Authors | Ping Gong, Shiyuan Su, Fandong Zhang et al. |
|---|---|
| Primary category | cs.CV |
| Published | 22 September 2026 |
| Last updated at source | 24 September 2026 |
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