48 citations · 60 across the 7 of their papers we have counts for
7 papers
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…
Glo-In-One: Holistic Glomerular Detection, Segmentation, and Lesion Characterization with Large-scale Web Image Mining
Tianyuan Yao, Yuzhe Lu, Jun Long +6
The quantitative detection, segmentation, and characterization of glomeruli from high-resolution whole slide imaging (WSI) play essential roles in the computer-assisted diagnosis a…
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…
Circle Representation for Medical Object Detection
Ethan H. Nguyen, Haichun Yang, Ruining Deng +7
Box representation has been extensively used for object detection in computer vision. Such representation is efficacious but not necessarily optimized for biomedical objects (e.g.,…
Improve Global Glomerulosclerosis Classification with Imbalanced Data using CircleMix Augmentation
Yuzhe Lu, Haichun Yang, Zheyu Zhu +3
The classification of glomerular lesions is a routine and essential task in renal pathology. Recently, machine learning approaches, especially deep learning algorithms, have been u…
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…