PrPSeg: Universal Proposition Learning for Panoramic Renal Pathology Segmentation

Understanding the anatomy of renal pathology is crucial for advancing disease diagnostics, treatment evaluation, and clinical research. The complex kidney system comprises various components across multiple levels, including regions (cortex, medulla), functional units (glomeruli, tubules), and cells...

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Bibliographic Details

Published in:	Proceedings (IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Online) Vol. 2024; pp. 11736 - 11746
Main Authors:	Deng, Ruining, Liu, Quan, Cui, Can, Yao, Tianyuan, Yue, Jialin, Xiong, Juming, Yu, Lining, Wu, Yifei, Yin, Mengmeng, Wang, Yu, Zhao, Shilin, Tang, Yucheng, Yang, Haichun, Huo, Yuankai
Format:	Conference Proceeding Journal Article
Language:	English
Published:	United States IEEE 01.06.2024
Subjects:	Computational modeling digital pathology dynamic network Head hierarchical taxonomy Image segmentation Pathology segmentation semi-supervised learning Semisupervised learning Training Transforms
ISSN:	1063-6919, 1063-6919
Online Access:	Get full text
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