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Updated: Feb 16, 2026
04:23
A Swin Transformer-Based Model for Thyroid Nodule Detection in Ultrasound Images
Published on: April 21, 2023
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An Infrared Thermal Images Database and a New Technique for Thyroid Nodules Analysis
José R González1, Charbel Damião2, Aura Conci1
1Computing Institute, Federal Fluminense University, Niterói, Rio de Janeiro, Brazil.
Studies in Health Technology and Informatics
|January 4, 2018
Summary
This study introduces a new database of infrared thermal images and clinical data for thyroid nodule classification. This resource aids artificial intelligence in diagnosing thyroid cancer more effectively.
Area of Science:
- Medical imaging
- Artificial Intelligence
- Oncology
Background:
- Thyroid nodules and cancer are prevalent health issues.
- Cancerous tissues exhibit higher temperatures than normal tissues.
- Thermography is a valuable tool for detecting abnormalities.
Purpose of the Study:
- To present a novel database for thyroid nodule classification.
- To facilitate the application of artificial intelligence in thyroid cancer diagnosis.
- To provide a standardized dataset for research.
Main Methods:
- Development of a new database with infrared thermal images, clinical, and physiological data.
- Implementation of a semi-automatic image registration method for thermogram preprocessing.
- Proposal of a novel method for Region of Interest (ROI) extraction.
Main Results:
- A comprehensive database for thyroid nodule analysis is established.
- Image preprocessing and ROI extraction methods are detailed.
- ROI results are validated by medical specialists.
Conclusions:
- The presented database and methods support AI-driven thyroid nodule classification.
- This work provides a valuable resource for future research in thermographic diagnostics.
- The validated ROI extraction method enhances diagnostic accuracy.
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