Deep learning-based Hounsfield unit value measurement method for bolus tracking images in cerebral computed tomography angiography.

Journal: Computers in biology and medicine
Published Date: Sep 2, 2021

Abstract

BACKGROUND: Patient movement during bolus tracking (BT) impairs the accuracy of Hounsfield unit (HU) measurements. This study assesses the accuracy of measuring HU values in the internal carotid artery (ICA) using an original deep learning (DL)-based method as compared with using the conventional region of interest (ROI) setting method.

Authors

  • Shota Watanabe
    Division of Positron Emission Tomography, Institute of Advanced Clinical Medicine, Kindai University Hospital, 377-2 Ohno-Higashi, Osakasayama, Osaka, 589-8511, Japan; Radiology Center, Kindai University Hospital, 377-2 Ohno-Higashi, Osakasayama, Osaka, 589-8511, Japan. Electronic address: shouta-w@med.kindai.ac.jp.
  • Kenta Sakaguchi
    Radiology Center, Kindai University Hospital, 377-2 Ohnohigashi, Osakasayama, Osaka, 589-8511, Japan. sakaguchi_kenta@med.kindai.ac.jp.
  • Daisuke Murata
    Radiology Center, Kindai University Hospital, 377-2 Ohno-Higashi, Osakasayama, Osaka, 589-8511, Japan. Electronic address: murata.dys@gmail.com.
  • Kazunari Ishii
    Division of Positron Emission Tomography, Institute of Advanced Clinical Medicine, Kindai University, Osaka, Japan.

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