Reconstruction of EIT Images Using Fish School Search and Non-Blind Search

Breast cancer is the most common type of cancer among women, affecting 2.1 million women per year worldwide. The best strategy for decreasing disease morbidity and mortality is early detection. Mammography is the most used exam for the diagnosis of breast cancer. However, this technique uses ionizing radiation and causes discomfort to the patient. One promising technique that can be used for early detection of breast cancer is electrical impedance tomography (EIT), which is an imaging technique free of ionizing radiation. Yet, its images still have low resolution, making it difficult to use in breast cancer diagnosis. Thus, the development of new reconstruction methods aiming better resolution is necessary. This work evaluates the performance of the reconstruction algorithm based on fish school search with non-blind search in a 3,190 finite element mesh.