Breast MRI Segmentation and Ki-67 High- and Low-Expression Prediction Algorithm Based on Deep Learning.

Journal: Computational and mathematical methods in medicine
Published Date: Oct 4, 2022

Abstract

RESULTS: The DSC, PPV, and sensitivity of our combined model are 0.94, 0.93, and 0.94, respectively, with better segmentation performance. And we compare with the segmentation frameworks of other papers and find that our combined model can make accurate segmentation of breast tumors.

Authors

  • Yuan-Zhe Li
    Department of CT/MRI, The Second Affiliated Hospital of Fujian Medical University, Quanzhou 362000, China.
  • Yin-Hui Huang
    Department of Neurology, Jinjiang Municipal Hospital, Quanzhou 362000, China.
  • Xian-Yan Su
    Department of CT/MRI, The Second Affiliated Hospital of Fujian Medical University, Quanzhou 362000, China.
  • Zhen-Qi Gu
    Galactophore Department, The First School of Clinical Medicine, Zhejiang Chinese Medical University, 548 Binwen Road, Hangzhou 310000, China.
  • Qing-Quan Lai
    Department of CT/MRI, The Second Affiliated Hospital of Fujian Medical University, Quanzhou 362000, China.
  • Jing Huang
    Department of Nephrology, The Second Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China.
  • Shu-Ting Li
    Department of Ophthalmology, Shanghai Jiaotong University Affiliated Sixth People's Hospital , Shanghai, China.
  • Yi Wang
    Department of Neurology, Children's Hospital of Fudan University, National Children's Medical Center, Shanghai, China.

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