Classification of multi-feature fusion ultrasound images of breast tumor within category 4 using convolutional neural networks.

Journal: Medical physics
Published Date: Mar 4, 2024

Abstract

BACKGROUND: Breast tumor is a fatal threat to the health of women. Ultrasound (US) is a common and economical method for the diagnosis of breast cancer. Breast imaging reporting and data system (BI-RADS) category 4 has the highest false-positive value of about 30% among five categories. The classification task in BI-RADS category 4 is challenging and has not been fully studied.

Authors

  • Pengfei Xu
    Engineering Research Center for Cereal Fermentation and Food Biomanufacturing, School of Biotechnology, Jiangnan University, Wuxi, China.
  • Jing Zhao
    Department of Pharmacy, Pharmacoepidemiology and Drug Safety Research Group, Faculty of Mathematics and Natural Sciences, University of Oslo, Oslo, Norway.
  • Mingxi Wan
    Key Laboratory of Biomedical Information Engineering of the Ministry of Education, Department of Biomedical Engineering, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, China.
  • Qing Song
    School of Electrical and Electronic Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore 639798, Singapore. Electronic address: eqsong@ntu.edu.sg.
  • Qiang Su
    Guizhou University of Traditional Chinese Medicine, Guiyang, Guizhou Province, China.
  • Diya Wang
    Department of Biomedical Engineering, Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, China.

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