Developing a deep learning model for predicting ovarian cancer in Ovarian-Adnexal Reporting and Data System Ultrasound (O-RADS US) Category 4 lesions: A multicenter study.

Journal: Journal of cancer research and clinical oncology
Published Date:

Abstract

PURPOSE: To develop a deep learning (DL) model for differentiating between benign and malignant ovarian tumors of Ovarian-Adnexal Reporting and Data System Ultrasound (O-RADS US) Category 4 lesions, and validate its diagnostic performance.

Authors

  • Wenting Xie
    Department of Ultrasound Medicine, The Second Affiliated Hospital of Fujian medical University, Quanzhou, Fujian Province, 362000, China.
  • Wenjie Lin
    Department of Ultrasound Medicine, The Second Affiliated Hospital of Fujian medical University, Quanzhou, Fujian Province, 362000, China.
  • Ping Li
    Department of Gastroenterology, Beijing Ditan Hospital, Capital Medical University, Beijing, China.
  • Hongwei Lai
    Department of Ultrasound, Fujian Provincial Maternity and Children's Hospital, Fuzhou, Fujian Province, 350014, China.
  • Zhilan Wang
    Department of Ultrasound, Nanping First Hospital Affiliated to Fujian Medical University, Nanping, Fujian Province, 35300, China.
  • Peizhong Liu
    College of Engineering, Huaqiao University, No. 269, Chenghua North Road, Quanzhou, 362021, Fujian, China. pzliu@hqu.edu.cn.
  • YiJun Huang
    School of Software, Nanchang University, Nanchang, Jiangxi, China.
  • Yao Liu
    Innovation Research Institute of Combined Acupuncture and Medicine, Shaanxi University of CM, Xianyang 712046, China.
  • Lina Tang
    Department of Ultrasound, Fujian Cancer Hospital, Clinical Oncology School of Fujian Medical University, Fuzhou, Fujian Province, 350014, China. tanglina@fjzlhospital.com.
  • Guorong Lyu
    Department of Ultrasound, The Second Affiliated Hospital of Fujian Medical University, Quanzhou 362000, China.