Open Access. Powered by Scholars. Published by Universities.®
Electrical and Computer Engineering
Electronic Theses and Dissertations
BYOL;Contrastive Learning;Domain Adaptation;Mammogram images;Self-Supervised Learning;SimCLR
Articles 1 - 1 of 1
Full-Text Articles in Entire DC Network
Enhancing Breast Cancer Detection Through Combination Of Contrastive Learning And Adversarial Domain Adaptation, Mahnoosh Torabi
Enhancing Breast Cancer Detection Through Combination Of Contrastive Learning And Adversarial Domain Adaptation, Mahnoosh Torabi
Electronic Theses and Dissertations
The most common cancer diagnosed worldwide is breast cancer and early detection is essential for reducing mortality. The best standard for early detection of breast cancer is digital mammography, which can aid physicians in treating the illness when it is still curable. However, inaccurate mammography diagnoses are frequent and can cause patients to undergo unnecessary examinations and therapies. This study aims to explore deep-learning techniques that can be utilized to implement and train a model to identify breast cancer cases in mammograms. Current deep learning-based diagnostic techniques are hindered by two fundamental issues: the expensive and time-consuming task of data …