Deep learning-based intravascular ultrasound segmentation for the assessment of coronary artery disease.

Journal: International journal of cardiology
Published Date: Mar 16, 2021

Abstract

BACKGROUND: Accurate segmentation of the coronary arteries with intravascular ultrasound (IVUS) is important to optimize coronary stent implantation. Recently, deep learning (DL) methods have been proposed to develop automatic IVUS segmentation. However, most of those have been limited to segmenting the lumen and vessel (i.e. lumen-intima and media-adventitia borders), not applied to segmenting stent dimension. Hence, this study aimed to develop a DL method for automatic IVUS segmentation of stent area in addition to lumen and vessel area.

Authors

  • Takeshi Nishi
    Division of Cardiovascular Medicine, Stanford University School of Medicine and Stanford Cardiovascular Institute, Stanford, CA, USA; Department of Cardiovascular Medicine, Chiba University Graduate School of Medicine, Chiba, Chiba, Japan. Electronic address: takeshi24@hotmail.co.jp.
  • Rikiya Yamashita
    Artera, Inc., Los Altos, CA.
  • Shinji Imura
    Division of Cardiovascular Medicine, Stanford University School of Medicine and Stanford Cardiovascular Institute, Stanford, CA, USA.
  • Kazuya Tateishi
    Department of Cardiovascular Medicine, Chiba University Graduate School of Medicine, Chiba, Chiba, Japan.
  • Hideki Kitahara
    Department of Cardiovascular Medicine, Chiba University Graduate School of Medicine, Chiba, Chiba, Japan.
  • Yoshio Kobayashi
    Department of Cardiovascular Medicine, Chiba University Graduate School of Medicine, Chiba, Chiba, Japan.
  • Paul G Yock
    Division of Cardiovascular Medicine, Stanford University School of Medicine and Stanford Cardiovascular Institute, Stanford, CA, USA.
  • Peter J Fitzgerald
    Division of Cardiovascular Medicine, Stanford University School of Medicine and Stanford Cardiovascular Institute, Stanford, CA, USA.
  • Yasuhiro Honda
    Division of Cardiovascular Medicine, Stanford University School of Medicine and Stanford Cardiovascular Institute, Stanford, CA, USA. Electronic address: yshonda@stanford.edu.

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