Benign and malignant detection and classification for small size image of breast tumor recognition system using u-net model

• Main Authors: Suryanti, Awang, Kumar, Saumya, Nur Syafiqah, Mohd Nafis, Raihanah, Haroon
• Format: Conference or Workshop Item
• Language: English; English
• Published: IEEE 2024
• Subjects: QA75 Electronic computers. Computer science
• Online Access: http://umpir.ump.edu.my/id/eprint/43028/2/Benign%20and%20Malignant%20Detection%20and%20Classification%20for%20Small%20Size%20Image%20of%20Breast%20Tumor%20Recognition%20System%20using%20U-Net%20Model%20-%20intro.pdf; http://umpir.ump.edu.my/id/eprint/43028/1/Benign%20and%20Malignant%20Detection%20and%20Classification%20for%20Small%20Size%20Image%20of%20Breast%20Tumor%20Recognition%20System%20using%20U-Net%20Model.pdf; http://umpir.ump.edu.my/id/eprint/43028/; https://doi.org/10.1109/AiDAS63860.2024.10730254
• Institution: Universiti Malaysia Pahang Al-Sultan Abdullah

Breast tumor recognition is a critical task in the field of medical imaging systems, aiming to differentiate between benign and malignant tumors. To differentiate the tumors, an efficient technique is crucial to detect and classify it to avoid misdetection and misclassification, at the same time can...