activity
20232026
most citedHoloHisto: End-to-end Gigapixel WSI Segmentation with 4K Resolution Sequential Tokenization

4 citations · 12 across the 32 of their papers we have counts for

collaborators
Showing eess.IVShow all

14 papers · 1 filter

eess.IV2025

Quantitative Benchmarking of Anomaly Detection Methods in Digital Pathology

Can Cui, Xindong Zheng, Ruining Deng +8

Anomaly detection has been widely studied in the context of industrial defect inspection, with numerous methods developed to tackle a range of challenges. In digital pathology, ano…

eess.IV2025

IRS: Incremental Relationship-guided Segmentation for Digital Pathology

Ruining Deng, Junchao Zhu, Juming Xiong +14

Continual learning is rapidly emerging as a key focus in computer vision, aiming to develop AI systems capable of continuous improvement, thereby enhancing their value and practica…

eess.IV2025

PySpatial: A High-Speed Whole Slide Image Pathomics Toolkit

Yuechen Yang, Yu Wang, Tianyuan Yao +5

Whole Slide Image (WSI) analysis plays a crucial role in modern digital pathology, enabling large-scale feature extraction from tissue samples. However, traditional feature extract…

eess.IV2024

Glo-In-One-v2: Holistic Identification of Glomerular Cells, Tissues, and Lesions in Human and Mouse Histopathology

Lining Yu, Mengmeng Yin, Ruining Deng +9

Segmenting glomerular intraglomerular tissue and lesions traditionally depends on detailed morphological evaluations by expert nephropathologists, a labor-intensive process suscept…

eess.IV2024

Cross-Species Data Integration for Enhanced Layer Segmentation in Kidney Pathology

Junchao Zhu, Mengmeng Yin, Ruining Deng +6

Accurate delineation of the boundaries between the renal cortex and medulla is crucial for subsequent functional structural analysis and disease diagnosis. Training high-quality de…

eess.IV2024

Assessment of Cell Nuclei AI Foundation Models in Kidney Pathology

Junlin Guo, Siqi Lu, Can Cui +14

Cell nuclei instance segmentation is a crucial task in digital kidney pathology. Traditional automatic segmentation methods often lack generalizability when applied to unseen datas…