ABSTRACT
Breast cancer takes the first position in the list of cancers among Indian women, while its survival rate is 66.1%. One of the serious challenges faced in the management of breast cancer outcomes in India happens to be late-stage detection, where treatment options are already becoming minimized. Thermal imaging employs cameras that record temperature distributions on surfaces and thereby distinguish between the higher temperatures caused by the heat emitted from cancer cells. This technology enables the pinpointing of malignant tumors through differences in thermal signatures. Along with this innovative approach, here, the Generative Adversarial Networks (GANs), a modern technology in the field of artificial intelligence, which we use for enhancing the analysis of thermal images, are also used. Artificial neural networks GANs can generate additional synthetic thermal images that are just like the real ones, and this diversifies the dataset as well as improves its robustness. Hence, machine learning AI algorithms can rely on these features, and thus, they achieve a higher accuracy rate while diagnosing breast cancer.
