Accurate and generalizable quantitative scoring of liver steatosis from ultrasound images scalable deep learning.

Journal: World journal of gastroenterology
PMID: 35979264

Abstract

BACKGROUND: Hepatic steatosis is a major cause of chronic liver disease. Two-dimensional (2D) ultrasound is the most widely used non-invasive tool for screening and monitoring, but associated diagnoses are highly subjective.

Authors

  • Bowen Li
    Department of Pediatric Cardiology, West China Second University Hospital, Sichuan University, Chengdu, China.
  • Dar-In Tai
    Department of Gastroenterology and Hepatology, Chang Gung Memorial Hospital at Linkou, Chang Gung University, Taoyuan, Taiwan.
  • Ke Yan
    Department of Biostatistics, Medical College of Wisconsin, Milwaukee, Wis.
  • Yi-Cheng Chen
    Department of Gastroenterology and Hepatology, Chang Gung Memorial Hospital, Linkou Medical Center, Taoyuan 33305, Taiwan.
  • Cheng-Jen Chen
    Department of Gastroenterology and Hepatology, Chang Gung Memorial Hospital, Linkou Medical Center, Taoyuan 33305, Taiwan.
  • Shiu-Feng Huang
    Division of Molecular and Genomic Medicine, National Health Research Institute, Taoyuan 33305, Taiwan.
  • Tse-Hwa Hsu
    Department of Gastroenterology and Hepatology, Chang Gung Memorial Hospital, Linkou Medical Center, Taoyuan 33305, Taiwan.
  • Wan-Ting Yu
    Department of Gastroenterology and Hepatology, Chang Gung Memorial Hospital, Linkou Medical Center, Taoyuan 33305, Taiwan.
  • Jing Xiao
    Xiyuan Hospital, China Academy of Chinese Medical Sciences(CACMS), Beijing, China.
  • Lu Le
    ASPIRE Center, VASDHS Residential Rehabilitation Treatment Program, San Diego, California, USA.
  • Adam P Harrison
    Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, Clinical Image Processing Service, Radiology and Imaging Sciences Department, National Institutes of Health Clinical Center, Bethesda, MD 20892-1182, USA.

Keywords

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