The potential of AI as a diagnostic aid in MRI breast cancer screening

Abstract

More than 60,000 Japanese women are diagnosed with breast cancer annually, and 13,000 die from the disease.Therefore, breast cancer screening is very important to achieve mortality reduction. We are conducting research and development on deep learning of DWIBS, an image with excellent contrast that emphasizes microscopic water diffusion, and mammary MRI images with various contrasts such as T1WI and T2WI. Using the deep learning model Xception, we developed a diagnostic aid model for fat-suppressed T2-weighted images and diffusion-weighted images. The combination of AI to assist diagnosis by taking advantage of the characteristics of MRI images may further contribute to the goal of reducing the mortality rate of breast cancer screening.