Fus2Net: a novel Convolutional Neural Network for classification of benign and malignant breast tumor in ultrasound images.

Journal: Biomedical engineering online
Published Date: Nov 18, 2021

Abstract

BACKGROUND: The rapid development of artificial intelligence technology has improved the capability of automatic breast cancer diagnosis, compared to traditional machine learning methods. Convolutional Neural Network (CNN) can automatically select high efficiency features, which helps to improve the level of computer-aided diagnosis (CAD). It can improve the performance of distinguishing benign and malignant breast ultrasound (BUS) tumor images, making rapid breast tumor screening possible.

Authors

  • He Ma
    Sino-Dutch Biomedical and Information Engineering School, Northeastern University, Shenyang 110819, China and Key Laboratory of Medical Image Computing, Ministry of Education, Northeastern University, Shenyang 110819, China.
  • Ronghui Tian
    College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, Liaoning, 110169, China.
  • Hong Li
    Department of Public Health Sciences, Medical College of South Carolina, Charleston, SC.
  • Hang Sun
    CAS Key Laboratory for Plant Diversity and Biogeography of East Asia, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming 650201, China.
  • Guoxiu Lu
    College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, Liaoning, 110169, China.
  • Ruibo Liu
    College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, Liaoning, 110169, China.
  • Zhiguo Wang
    Sino-Dutch Biomedical and Information Engineering School, Northeastern University, Shenyang, 110169, Liaoning, China.

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