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eess.IV2023
Democratizing Pathological Image Segmentation with Lay Annotators via Molecular-empowered Learning
Ruining Deng, Yanwei Li, Peize Li +11
Multi-class cell segmentation in high-resolution Giga-pixel whole slide images (WSI) is critical for various clinical applications. Training such an AI model typically requires lab…
eess.IV2023★ 97 cited
Segment Anything Model (SAM) for Digital Pathology: Assess Zero-shot Segmentation on Whole Slide Imaging
Ruining Deng, Can Cui, Quan Liu +13
The segment anything model (SAM) was released as a foundation model for image segmentation. The promptable segmentation model was trained by over 1 billion masks on 11M licensed an…