most citedNuclei Grading of Clear Cell Renal Cell Carcinoma in Histopathological Image by Composite High-Resolution Network

5 citations · 7 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV20211 cited

A Personalized Diagnostic Generation Framework Based on Multi-source Heterogeneous Data

Jialun Wu, Zeyu Gao, Haichuan Zhang +4

Personalized diagnoses have not been possible due to sear amount of data pathologists have to bear during the day-to-day routine. This lead to the current generalized standards tha…

eess.IV20211 cited

A Precision Diagnostic Framework of Renal Cell Carcinoma on Whole-Slide Images using Deep Learning

Jialun Wu, Haichuan Zhang, Zeyu Gao +4

Diagnostic pathology, which is the basis and gold standard of cancer diagnosis, provides essential information on the prognosis of the disease and vital evidence for clinical treat…

eess.IV20215 cited

Nuclei Grading of Clear Cell Renal Cell Carcinoma in Histopathological Image by Composite High-Resolution Network

Zeyu Gao, Jiangbo Shi, Xianli Zhang +6

The grade of clear cell renal cell carcinoma (ccRCC) is a critical prognostic factor, making ccRCC nuclei grading a crucial task in RCC pathology analysis. Computer-aided nuclei gr…

q-bio.QM2020

OpenHI2 -- Open source histopathological image platform

Pargorn Puttapirat, Haichuan Zhang, Jingyi Deng +7

Transition from conventional to digital pathology requires a new category of biomedical informatic infrastructure which could facilitate delicate pathological routine. Pathological…

eess.IV2020

Effects of annotation granularity in deep learning models for histopathological images

Jiangbo Shi, Zeyu Gao, Haichuan Zhang +4

Pathological is crucial to cancer diagnosis. Usually, Pathologists draw their conclusion based on observed cell and tissue structure on histology slides. Rapid development in machi…