A clinical evaluation study of cardiothoracic ratio measurement using artificial intelligence.

Journal: BMC medical imaging
Published Date: Mar 16, 2022

Abstract

BACKGROUND: Artificial intelligence, particularly the deep learning (DL) model, can provide reliable results for automated cardiothoracic ratio (CTR) measurement on chest X-ray (CXR) images. In everyday clinical use, however, this technology is usually implemented in a non-automated (AI-assisted) capacity because it still requires approval from radiologists. We investigated the performance and efficiency of our recently proposed models for the AI-assisted method intended for clinical practice.

Authors

  • Pairash Saiviroonporn
    Department of Radiology, Faculty of Medicine Siriraj Hospital, Mahidol University, 2 Wanglang Road, Bangkoknoi, Bangkok, 10700, Thailand. pairash.sai@gmail.ac.th.
  • Suwimon Wonglaksanapimon
    Department of Radiology, Faculty of Medicine Siriraj Hospital, Mahidol University, 2 Wanglang Road, Bangkoknoi, Bangkok, 10700, Thailand.
  • Warasinee Chaisangmongkon
    Department of Neurobiology and Kavli Institute for Neuroscience, Yale University School of Medicine, New Haven, CT 06511, USA; Institute of Field Robotics, King Mongkut's University of Technology Thonburi, Bangkok 10140, Thailand.
  • Isarun Chamveha
    Perceptra Co., Ltd., Bangkok, Thailand.
  • Pakorn Yodprom
    Department of Radiology, Faculty of Medicine Siriraj Hospital, Mahidol University, 2 Wanglang Road, Bangkoknoi, Bangkok, 10700, Thailand.
  • Krittachat Butnian
    Department of Radiology, Faculty of Medicine Siriraj Hospital, Mahidol University, 2 Wanglang Road, Bangkoknoi, Bangkok, 10700, Thailand.
  • Thanogchai Siriapisith
    Department of Radiology, Faculty of Medicine Siriraj Hospital, Mahidol University, 2 Wanglang Road, Bangkoknoi, Bangkok, 10700, Thailand.
  • Trongtum Tongdee
    Department of Radiology, Faculty of Medicine Siriraj Hospital, Mahidol University, 2 Wanglang Road, Bangkoknoi, Bangkok, 10700, Thailand.

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