Evaluation of transfer learning of pre-trained CNNs applied to breast cancer detection on infrared images.

Breast cancer accounts for the highest number of female deaths worldwide. Early detection of the disease is essential to increase the chances of treatment and cure of patients. Infrared thermography has emerged as a promising technique for diagnosis of the disease due to its low cost and that it does not emit harmful radiation, and it gives good results when applied in young women.

Breast tumor localization using skin surface temperatures from a 2D anatomic model without knowledge of the thermophysical properties.

Breast cancer is the second most common type of cancer among women after nonmelanoma skin cancer. Use of mammography, the main method to diagnose the disease, has several limitations in parts of the population. The primary goal of this work was to detect and localize the geometric centers of mammary tumors using only superficial temperatures of the breast skin.