Transformer-based multiclass segmentation pipeline for basic kidney histology

Current applications of deep learning in renal pathology focused on anatomical structures with morphology, yet little research has focused on the performance of models, such as versatility, in regions with severe kidney damage. In this study, we explored the difference in modal/domain shift capabili...

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Bibliographic Details
Published in:	Scientific reports Vol. 15; no. 1; pp. 38957 - 14
Main Authors:	He, Junling, Valkema, Pieter A., Long, Jingmin, Li, Jia, Florquin, Sandrine, Naesens, Maarten, Koshy, Priyanka, Nguyen, Tri Q., Meziyerh, Soufian, de Vries, Aiko P. J., De Boer, Onno J., Verbeek, Fons J., Xiong, Zhan, Kers, Jesper
Format:	Journal Article
Language:	English
Published:	London Nature Publishing Group UK 06.11.2025 Nature Publishing Group Nature Portfolio
Subjects:	639/166 692/699/1585 Architecture Arteries Artificial intelligence Biopsy Classification Deep Learning Fibrosis Histology Humanities and Social Sciences Humans Image Processing, Computer-Assisted - methods Inflammation Innovations Kidney - diagnostic imaging Kidney - pathology Kidney diseases Kidney histology Kidneys Lesions Medical imaging Multiclass segmentation multidisciplinary Neural Networks, Computer Pathology Science Science (multidisciplinary) Segmentation Semantic segmentation Semantics Sensitivity analysis Splitting Transformer Deep learning Kidney histology Transformer Semantic segmentation Multiclass segmentation
ISSN:	2045-2322, 2045-2322
Online Access:	Get full text
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