97 citations · 211 across the 77 of their papers we have counts for
6 papers · 1 filter
ASIST: Annotation-free synthetic instance segmentation and tracking for microscope video analysis
Quan Liu, Isabella M. Gaeta, Mengyang Zhao +6
Instance object segmentation and tracking provide comprehensive quantification of objects across microscope videos. The recent single-stage pixel-embedding based deep learning appr…
CaCL: Class-aware Codebook Learning for Weakly Supervised Segmentation on Diffuse Image Patterns
Ruining Deng, Quan Liu, Shunxing Bao +5
Weakly supervised learning has been rapidly advanced in biomedical image analysis to achieve pixel-wise labels (segmentation) from image-wise annotations (classification), as biome…
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…
CircleNet: Anchor-free Detection with Circle Representation
Haichun Yang, Ruining Deng, Yuzhe Lu +7
Object detection networks are powerful in computer vision, but not necessarily optimized for biomedical object detection. In this work, we propose CircleNet, a simple anchor-free d…
Map3D: Registration Based Multi-Object Tracking on 3D Serial Whole Slide Images
Ruining Deng, Haichun Yang, Aadarsh Jha +4
There has been a long pursuit for precise and reproducible glomerular quantification on renal pathology to leverage both research and practice. When digitizing the biopsy tissue sa…