Revolutionizing breast cancer Ki-67 diagnosis: ultrasound radiomics and fully connected neural networks (FCNN) combination method.

Journal: Breast cancer research and treatment
Published Date: Jun 9, 2024

Abstract

PURPOSE: This study aims to assess the diagnostic value of ultrasound habitat sub-region radiomics feature parameters using a fully connected neural networks (FCNN) combination method L2,1-norm in relation to breast cancer Ki-67 status.

Authors

  • Yanfeng Li
    School of Electronic and Information Engineering, Beijing Jiaotong University, Shangyuan Village No 3 in Haidian, Beijing, China.
  • Wengxing Long
    Department of Interventional Vascular Surgery, Affiliated Hospital (Clinical College) of Xiangnan University, Chenzhou, 423000, People's Republic of China.
  • Hongda Zhou
    Department of Oncology, Affiliated Hospital of Xiangnan University, Chenzhou, 423000, Hunan, People's Republic of China.
  • Tao Tan
    Faculty of Applied Sciences, Macao Polytechnic University, Macao, China.
  • Hui Xie
    Department of Breast Diseases, The First Affiliated Hospital of Nanjing Medical University & Jiangsu Province Hospital, Nanjing, Jiangsu, China.

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