Deep Learning-Based Recognition of Different Thyroid Cancer Categories Using Whole Frozen-Slide Images.

ABSTRACT: Introduction: The pathological rare category of thyroid is a type of lesion with a low incidence rate and is easily misdiagnosed in clinical practice, which directly affects a patient's treatment decision. However, it has not been adequately investigated to recognize the rare, benign, and malignant categories of thyroid using the deep learning method and recommend the rare to pathologists. Methods: We present an empirical decision tree based on the binary classification results of the patch-based UNet model to predict rare categories and recommend annotated lesion areas to be rereviewed by pathologists. Results: Applying this framework to 1,374 whole-slide images (WSIs) of frozen sections from thyroid lesions, we obtained an area under a curve of 0.946 and 0.986 for th

SUBMITTER: Zhu X 

PROVIDER: S-EPMC9298848 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature