Improving interobserver agreement and performance of deep learning models for segmenting acute ischemic stroke by combining DWI with optimized ADC thresholds.

Journal: European radiology
Published Date:

Abstract

OBJECTIVES: To examine the role of ADC threshold on agreement across observers and deep learning models (DLMs) plus segmentation performance of DLMs for acute ischemic stroke (AIS).

Authors

  • Chun-Jung Juan
    Department of Medical Imaging, China Medical University Hsinchu Hospital, Hsinchu, Taiwan.
  • Shao-Chieh Lin
    Department of Medical Imaging, China Medical University Hsinchu Hospital, Hsinchu, Taiwan, Republic of China.
  • Ya-Hui Li
    Department of Medical Imaging, China Medical University Hsinchu Hospital, Hsinchu, Taiwan, Republic of China.
  • Chia-Ching Chang
    Department of Medical Imaging, China Medical University Hsinchu Hospital, Hsinchu, Taiwan, Republic of China.
  • Yi-Hung Jeng
    Department of Medical Imaging, China Medical University Hsinchu Hospital, Hsinchu, Taiwan, Republic of China.
  • Hsu-Hsia Peng
    Department of Biomedical Engineering and Environmental Sciences, National Tsing Hua University, Hsinchu 300044, Taiwan.
  • Teng-Yi Huang
    Computational Intelligence Technology Center, Industrial Technology Research Institute, Hsinchu, Taiwan.
  • Hsiao-Wen Chung
    Graduate Institute of Biomedical Electrics and Bioinformatics, National Taiwan University, Taipei, Taiwan.
  • Wu-Chung Shen
    Department of Radiology, School of Medicine, China Medical University, Taichung, Taiwan, Republic of China.
  • Chon-Haw Tsai
    Division of Nephrology, China Medical University Hospital, Taichung, Taiwan.
  • Ruey-Feng Chang
    Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei 10617, Taiwan and Department of Computer Science and Information Engineering, National Taiwan University, Taipei 10617, Taiwan.
  • Yi-Jui Liu
    Department of Automatic Control Engineering, Feng Chia University, Taichung, Taiwan.