Self-Supervised Bi-Pipeline Learning Approach for High Interpretation of Breast Thermal Images

• Main Authors: Roslidar, Roslidar, Alhamdi, Muhammad Jurej, Rahman, Aulia, Saddami, Khairun, Arnia, Fitri, Syukri, Maimun, Munadi, Khairul
• Format: Article
• Published: Institute of Electrical and Electronics Engineers 2024
• Subjects: R Medicine (General); TJ Mechanical engineering and machinery; TK Electrical engineering. Electronics Nuclear engineering
• Online Access: http://eprints.um.edu.my/47109/; https://doi.org/10.1109/ACCESS.2024.3433559
• Institution: Universiti Malaya

The image quality supports a high accuracy rate of medical image diagnosis using computer vision. Digital thermal images resulting from the thermal device usually suffer from many watermarks that may lower the neural network learning performance. Thus, providing only the region of interest (RoI) of...