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Related Experiment Video

Updated: Dec 15, 2025

Author Spotlight: Integrating Ultrasound Imaging with Biochemical Markers for Thyroid Disease Diagnosis

Author Spotlight: Integrating Ultrasound Imaging with Biochemical Markers for Thyroid Disease Diagnosis

Published on: February 9, 2024

Interactive thyroid whole slide image diagnostic system using deep representation.

Pingjun Chen¹, Xiaoshuang Shi¹, Yun Liang¹

¹J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, Gainesville, FL, United States.

Computer Methods and Programs in Biomedicine

|July 8, 2020

Summary

This summary is machine-generated.

This study introduces an interactive system for diagnosing thyroid frozen sections using whole slide images (WSIs). Pathologist-selected suspicious regions improve diagnostic accuracy and efficiency in computer-aided diagnosis.

Keywords:

Deep representation Region retrieval Suspicious region Thyroid frozen section Whole slide image

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Area of Science:

Digital pathology
Computer-aided diagnosis
Thyroid histopathology

Background:

Whole slide images (WSIs) present computational challenges for automated diagnosis.
Suspicious regions in thyroid WSIs are identifiable, aiding targeted analysis.

Purpose of the Study:

To develop an interactive WSI diagnostic system for thyroid frozen sections.
To leverage pathologist-identified suspicious regions for improved computer-aided diagnosis.

Main Methods:

Generating feature representations from suspicious regions using deep neural networks.
Extracting and fusing patch features for comprehensive analysis.
Evaluating region classification and retrieval using multiple classifiers and hashing methods.

Main Results:

Achieved 96.1% cross-validated classification accuracy on 345 thyroid frozen sections.
Obtained a retrieval mean average precision (MAP) of 0.972.
Demonstrated system potential in practical thyroid frozen section diagnosis.

Conclusions:

The interactive system reduces interference from irrelevant regions and lowers computational costs.
Enables fine-grained, precise retrieval of suspicious regions.
Fosters a collaborative relationship between pathologists and diagnostic systems.