97 citations · 97 across the 1 of their papers we have counts for
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HoloHisto: End-to-end Gigapixel WSI Segmentation with 4K Resolution Sequential Tokenization
Yucheng Tang, Yufan He, Vishwesh Nath +11
In digital pathology, the traditional method for deep learning-based image segmentation typically involves a two-stage process: initially segmenting high-resolution whole slide ima…
Leverage Weakly Annotation to Pixel-wise Annotation via Zero-shot Segment Anything Model for Molecular-empowered Learning
Xueyuan Li, Ruining Deng, Yucheng Tang +3
Precise identification of multiple cell classes in high-resolution Giga-pixel whole slide imaging (WSI) is critical for various clinical scenarios. Building an AI model for this pu…
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…
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…