Hybrid transformer-based model for mammogram classification by integrating prior and current images.

Journal: Medical physics
Published Date: Jan 30, 2025

Abstract

BACKGROUND: Breast cancer screening via mammography plays a crucial role in early detection, significantly impacting women's health outcomes worldwide. However, the manual analysis of mammographic images is time-consuming and requires specialized expertise, presenting substantial challenges in medical practice.

Authors

  • Afsana Ahsan Jeny
    School of Computing, University of Connecticut, Storrs, Connecticut, USA.
  • Sahand Hamzehei
    School of Computing, University of Connecticut, Storrs, Connecticut, USA.
  • Annie Jin
    Department of Radiology, UConn Health, Farmington, Connecticut, USA.
  • Stephen Andrew Baker
    Department of Radiology, UConn Health, Farmington, Connecticut, USA.
  • Tucker Van Rathe
    Department of Radiology, UConn Health, Farmington, Connecticut, USA.
  • Jun Bai
    Department of Hematology, Gansu Provincial Key Laboratory of Hematology , Lanzhou University Second Hospital , Lanzhou 730000 , China.
  • Clifford Yang
    Department of Diagnostic Imaging, University of Connecticut Health Center, Farmington, 06030, CT, USA.
  • Sheida Nabavi
    Department of Computer Science and Engineering, University of Connecticut, Storrs, 06269, CT, USA.

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