690 citations · 937 across the 17 of their papers we have counts for
5 papers · 1 filter
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…
Omni-Seg: A Scale-aware Dynamic Network for Renal Pathological Image Segmentation
Ruining Deng, Quan Liu, Can Cui +9
Comprehensive semantic segmentation on renal pathological images is challenging due to the heterogeneous scales of the objects. For example, on a whole slide image (WSI), the cross…
Holistic Fine-grained GGS Characterization: From Detection to Unbalanced Classification
Yuzhe Lu, Haichun Yang, Zuhayr Asad +5
Recent studies have demonstrated the diagnostic and prognostic values of global glomerulosclerosis (GGS) in IgA nephropathy, aging, and end-stage renal disease. However, the fine-g…
EasierPath: An Open-source Tool for Human-in-the-loop Deep Learning of Renal Pathology
Zheyu Zhu, Yuzhe Lu, Ruining Deng +3
Considerable morphological phenotyping studies in nephrology have emerged in the past few years, aiming to discover hidden regularities between clinical and imaging phenotypes. Suc…
Instance Segmentation for Whole Slide Imaging: End-to-End or Detect-Then-Segment
Aadarsh Jha, Haichun Yang, Ruining Deng +3
Automatic instance segmentation of glomeruli within kidney Whole Slide Imaging (WSI) is essential for clinical research in renal pathology. In computer vision, the end-to-end insta…