Segmentation of Leukoaraiosis on Noncontrast Head CT Using CT-MRI Paired Data Without Human Annotation.

Journal: Brain and behavior
Published Date: Jun 1, 2025

Abstract

OBJECTIVE: Evaluating leukoaraiosis (LA) on CT is challenging due to its low contrast and similarity to parenchymal gliosis. We developed and validated a deep learning algorithm for LA segmentation using CT-MRIFLAIR paired data from a multicenter Korean registry and tested it in a US dataset.

Authors

  • Wi-Sun Ryu
    Artificial Intelligence Research Center, JLK Inc., 5 Teheran-ro 33-gil, Seoul, Republic of Korea. wisunryu@gmail.com.
  • Jae W Song
    Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
  • Jae-Sung Lim
    Department of Neurology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea.
  • Ju Hyung Lee
    Artificial Intelligence Research Center, JLK Inc., Seoul, Republic of Korea.
  • Leonard Sunwoo
    Department of Radiology, Seoul National University Bundang Hospital, 82, Gumi-ro 173 Beon-gil, Bundang-gu, Seongnam-si, Gyeonggi-do 13620, Republic of Korea.
  • Dongmin Kim
    JLK, Incorporated, Eonju-ro, Gangnam-gu, Seoul, South Korea.
  • Dong-Eog Kim
    National Priority Research Center for Stroke and Department of Neurology (W.-S.R, J.C., S.-W.J., D.-S.G., D.-E.K.), Dongguk University Ilsan Hospital, Goyang, Republic of Korea kdongeog@duih.org.
  • Hee-Joon Bae
  • Myungjae Lee
    JLK, Incorporated, Eonju-ro, Gangnam-gu, Seoul, South Korea.
  • Beom Joon Kim
    Departments of Dermatology, Chung-Ang University College of Medicine, Seoul, Korea.

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