Performance of novel deep learning network with the incorporation of the automatic segmentation network for diagnosis of breast cancer in automated breast ultrasound.

Journal: European radiology
Published Date: Apr 30, 2022

Abstract

OBJECTIVE: To develop novel deep learning network (DLN) with the incorporation of the automatic segmentation network (ASN) for morphological analysis and determined the performance for diagnosis breast cancer in automated breast ultrasound (ABUS).

Authors

  • Qiucheng Wang
    Department of Ultrasound, Harbin Medical University Cancer Hospital, No. 150, Haping Road, Nangang District, Harbin, Heilongjiang Province, China.
  • He Chen
    School of Food and Biological Engineering, Shaanxi University of Science and Technology Xi&#;an, China.
  • Gongning Luo
  • Bo Li
    Electric Power Research Institute, Yunnan Power Grid Co., Ltd., Kunming, Yunnan, China.
  • Haitao Shang
    Department of Ultrasound, Harbin Medical University Cancer Hospital, No. 150, Haping Road, Nangang District, Harbin, Heilongjiang Province, China.
  • Hua Shao
    Department of Vascular Surgery, Dalian University Affiliated Xinhua Hospital, Dalian 116021, Liaoning Province, China.
  • Shanshan Sun
    Shandong Institute for Food and Drug Control, Ji'nan 250101, China.
  • Zhongshuai Wang
    School of Computer Science and Technology, Harbin Institute of Technology, No. 92, Xidazhi Street, Nangang District, Harbin, Heilongjiang Province, China.
  • Kuanquan Wang
  • Wen Cheng
    Department of Neurosurgery, Shengjing Hospital of China Medical University, Shenyang 110004, China.

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