Deep learning quantifies pathologists' visual patterns for whole slide image diagnosis.

ABSTRACT: Based on the expertise of pathologists, the pixelwise manual annotation has provided substantial support for training deep learning models of whole slide images (WSI)-assisted diagnostic. However, the collection of pixelwise annotation demands massive annotation time from pathologists, leading to a high burden of medical manpower resources, hindering to construct larger datasets and more precise diagnostic models. To obtain pathologists' expertise with minimal pathologist workloads then achieve precise diagnostics, we collect the image review patterns of pathologists by eye-tracking devices. Simultaneously, we design a deep learning system: Pathology Expertise Acquisition Network (PEAN), based on the collected visual patterns, which can decode pathologists' expertise and then diagnose WSIs

SUBMITTER: Nan T 

PROVIDER: S-EPMC12214614 | biostudies-literature | 2025 Jul

REPOSITORIES: biostudies-literature