Article

A Deep Learning-Based Tool for Segmentation and Quantification of i-IFTA, Focal Infiltrates, and Tubular Dilation in Haematoxylin-Eosin Stained Renal Whole-Slide Images

2026-07-13

Abstract excerpt

Simultaneous evaluation of acute and chronic lesions is critical for staging renal disease, yet manual assessment suffers from high inter-observer variability and heavy workloads. While deep learning models excel at structural segmentation, none currently consolidate the concurrent quantification of key AKI-to-CKD transition markers in standard stains. We developed a modified U-Net convolutional neural network for...

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Literature Corpus work: 1ea497bd-722b-5999-bd4a-8bba6d72befa
DOI: 10.20944/preprints202607.0831.v1

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