Validation of a deep-learning semantic segmentation approach to fully automate MRI-based left-ventricular deformation analysis in cardiotoxicity.

Journal: The British journal of radiology
PMID: 33571002

Abstract

OBJECTIVE: Left-ventricular (LV) strain measurements with the Displacement Encoding with Stimulated Echoes (DENSE) MRI sequence provide accurate estimates of cardiotoxicity damage related to chemotherapy for breast cancer. This study investigated an automated and supervised deep convolutional neural network (DCNN) model for LV chamber quantification before strain analysis in DENSE images.

Authors

  • Julia Karr
    Departments of Mechanical Engineering and Pharmacology, University of South Alabama, Mobile, AL, USA.
  • Michael Cohen
    Department of Neurosurgery, Northern Light Neurosurgery and Spine, Bangor, Maine, USA.
  • Samuel A McQuiston
    Department of Radiology, University of South Alabama, Mobile, AL, USA.
  • Teja Poorsala
    Departments of Oncology and Hematology, University of South Alabama, Mobile, AL, USA.
  • Christopher Malozzi
    Department of Cardiology, College of Medicine, University of South Alabama, Mobile, AL, USA.

Keywords

External Resources

Popular Topics
Recent Journals