Deep learning for differentiation of benign and malignant solid liver lesions on ultrasonography.

Journal: Abdominal radiology (New York)
Published Date: Feb 1, 2021

Abstract

PURPOSE: The ability to reliably distinguish benign from malignant solid liver lesions on ultrasonography can increase access, decrease costs, and help to better triage patients for biopsy. In this study, we used deep learning to differentiate benign from malignant focal solid liver lesions based on their ultrasound appearance.

Authors

  • Ianto Lin Xi
    Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania.
  • Jing Wu
    School of Pharmaceutical Science, Jiangnan University, Wuxi, 214122, Jiangsu, China.
  • Jing Guan
    Department of Radiology, The Second Xiangya Hospital of Central South University, No.139 Middle Renmin Road, Changsha, Hunan 410011, PR China.
  • Paul J Zhang
    Department of Pathology and Laboratory Medicine, Hospital of the University of Pennsylvania, Philadelphia, Pennsylvania.
  • Steven C Horii
    Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia, PA, 19104, USA.
  • Michael C Soulen
    Department of Radiology, Division of Interventional Radiology, Perelman School of Medicine of the University of Pennsylvania, Philadelphia, Pennsylvania.
  • Zishu Zhang
    Department of Radiology, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China. S.Stavropoulos@uphs.upenn.edu Harrison_Bai@Brown.edu zishuzhang@csu.edu.cn.
  • Harrison X Bai
    Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia, Pennsylvania.

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