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

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  • Hirahara Daisuke
    Department of AI Research Lab, Harada Academy Department of Advanced Biomedical Imaging Informatics, St. Marianna University School of Medicine Department of Clinical Imaging, Graduate School of Medicine, Tohoku University
  • Takahara Taro
    Department of Biomedical Engineering, Tokai University School of Engineering

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  • MRI 乳がん検診における診断補助 AI の可能性

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.

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