• Jpn J Radiol · Jan 2019

    Review

    Improvement of image quality at CT and MRI using deep learning.

    • Toru Higaki, Yuko Nakamura, Fuminari Tatsugami, Takeshi Nakaura, and Kazuo Awai.
    • Department of Diagnostic Radiology, Graduate School of Biomedical and Health Science, Hiroshima University, 1-2-3 Kasumi, Minami-ku, Hiroshima, 734-8551, Japan. higaki@hiroshima-u.ac.jp.
    • Jpn J Radiol. 2019 Jan 1; 37 (1): 73-80.

    AbstractDeep learning has been developed by computer scientists. Here, we discuss techniques for improving the image quality of diagnostic computed tomography and magnetic resonance imaging with the aid of deep learning. We categorize the techniques for improving the image quality as "noise and artifact reduction", "super resolution" and "image acquisition and reconstruction". For each category, we present and outline the features of some studies.

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