Comparison of Traditional Radiomics, Deep Learning Radiomics and Fusion Methods for Axillary Lymph Node Metastasis Prediction in Breast Cancer.

Journal: Academic radiology
Published Date: Nov 11, 2022

Abstract

RATIONALE AND OBJECTIVES: Accurate identification of axillary lymph node (ALN) status in breast cancer patients is important for determining treatment options and avoiding axillary overtreatments. Our study aims to comprehensively compare the performance of the traditional radiomics model, deep learning radiomics model, and the fusion models in evaluating breast cancer ALN status based on dynamic contrast-enhanced-magnetic resonance imaging (DCE-MRI) images.

Authors

  • Xue Li
    Department of Clinical Research Center, Dazhou Central Hospital, Dazhou 635000, China.
  • Lifeng Yang
    College of Information and Computer, Taiyuan University of Technology, Jinzhong, China.
  • Xiong Jiao
    College of Biomedical Engineering, Taiyuan University of Technology, Jinzhong, Shanxi, China. Electronic address: jiaoxiong@tyut.edu.cn.

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