Study of multistep Dense U-Net-based automatic segmentation for head MRI scans.

Journal: Medical physics
PMID: 37956307

Abstract

BACKGROUND: Despite extensive efforts to obtain accurate segmentation of magnetic resonance imaging (MRI) scans of a head, it remains challenging primarily due to variations in intensity distribution, which depend on the equipment and parameters used.

Authors

  • Yongha Gi
    Department of Bio-medical Engineering, Korea University, Seoul, Republic of Korea.
  • Geon Oh
    Department of Bio-medical Engineering, Korea University, Seoul, Republic of Korea.
  • Yunhui Jo
    Institute of Global Health Technology (IGHT), Korea University, Seoul, Republic of Korea.
  • Hyeongjin Lim
    Department of Bio-medical Engineering, Korea University, Seoul, Republic of Korea.
  • Yousun Ko
    Biomedical Research Center, Asan Institute for Life Sciences, Asan Medical Center, Seoul, Republic of Korea.
  • Jinyoung Hong
    Department of Bio-medical Engineering, Korea University, Seoul, Republic of Korea.
  • Eunjun Lee
    Department of Bio-medical Engineering, Korea University, Seoul, Republic of Korea.
  • Sangmin Park
    Department of Transportation System Engineering, Ajou University, Suwon, Republic of Korea.
  • Taemin Kwak
    Department of Bio-medical Engineering, Korea University, Seoul, Republic of Korea.
  • Sangcheol Kim
    Department of Bio-medical Engineering, Korea University, Seoul, Republic of Korea.
  • Myonggeun Yoon
    Department of Bio-medical Engineering, Korea University, Seoul, Republic of Korea.

Keywords

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