Breast Cancer Detection Auxiliary System Leveraging Deep Learning and Mixed Reality
Szu‐Yin Lin, Ming-Chun Chien, Edwin Tiong Kwong Meng, Yu-Chien Wang, Yu-Yi Kuo, Che-Hsuan Lin · 2023
According to the World Health Organization (WHO), in 2022, breast cancer is the most diagnosed cancer among women worldwide, irrespective of age. In Taiwan, it is the most prevalent cancer among women and has the fourth-highest mortality rate. Additionally, diagnosing breast cancer often takes a long time searching for symptoms. In this study, we propose utilizing artificial intelligence image analysis methods and mixed reality interfaces to track and compare breast cancer images. We employed a deep learning convolutional neural network to analyze and classify acquired images of benign or malignant cases. Thus, establishing breast cancer tracking and a diagnostic decision support system for physicians to reference would benefit the future medical field. By incorporating mixed reality technology, doctors can save time and reduce labor costs without being constrained by geographic limitations.