Breast Cancer Detection using IR-UWB with Deep Learning - Khumdee, Mawin; Assawaroongsakul, Pongpol; Phasukkit, Pattarapong; Houngkamhang, Nongluck (My University, 2021)
This paper proposes breast cancer positioning detection using the IR-UWB system with deep learning, which is an interesting alternative method. When compared to ultrasound, x-ray mammogram, and CT-scan, there are several advantages to using IR-UWB, including low cost, less energy required, less long-term effect, portability, and providing much more breast cancer screening access for patients. Nowadays, the IR-UWB system has many techniques for processing IR-UWB signals, and one of the most interesting technique is using deep learning. In this study, we collected data from nine IR-UWB antennas. Then, the prepared data is fed through Deep Neural Networks to find the hidden patterns of signal and predict the cancer position which are 16 of breast cancer positions and one of undetected, also known as 17 classes. The model gave an average accuracy up to 95.60%.
Keywords: Breast Cancer; Deep Neural Network; IR-UWB