Breast tumour classification in DCE-MRI via cross-attention and discriminant correlation analysis enhanced feature fusion.

Journal: Clinical radiology
Published Date: Jul 1, 2025

Abstract

AIM: Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) has proven to be highly sensitive in diagnosing breast tumours, due to the kinetic and volumetric features inherent in it. To utilise the kinetics-related and volume-related information, this paper aims to develop and validate a classification for differentiating benign and malignant breast tumours based on DCE-MRI, though fusing deep features and cross-attention-encoded radiomics features using discriminant correlation analysis (DCA).

Authors

  • F Pan
  • B Wu
    Rory Meyers College of Nursing, New York University, New York, NY, USA.
  • X Jian
    School of Biomedical Engineering, Capital Medical University, Beijing, 100069, China; Beijing Key Laboratory of Fundamental Research on Biomechanics in Clinical Application, Capital Medical University, Beijing, 100069, China.
  • C Li
    Department of Animal Sciences, University of Florida, Gainesville 32611.
  • D Liu
    Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA.
  • N Zhang
    Department of Medical Microbiology, Capital Medical University, Beijing, China.

Keywords

External Resources

Popular Topics
Recent Journals