Enhancing cardiac function assessment: Developing and validating a domain adaptive framework for automating the segmentation of echocardiogram videos.

Journal: Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Published Date: Aug 13, 2025

Abstract

BACKGROUND: Accurate segmentation of echocardiographic images is essential for assessing cardiac function, particularly in calculating key metrics such as ejection fraction. However, challenges such as domain discrepancy, noisy data, anatomical variability, and complex imaging conditions often hinder the performance of deep learning models in this domain.

Authors

  • Mojdeh Nazari
    Cardiovascular Disease Research Center, Department of Cardiology, School of Medicine, Heshmat Hospital, Guilan University of Medical Sciences, Rasht, Iran. mojdeh.nazari@sbmu.ac.ir.
  • Hassan Emami
    Faculty of Allied Medical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
  • Reza Rabiei
    Department of Health Information Technology and Management, School of Allied Medical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
  • Hamid Reza Rabiee
    Department of Computer Engineering, Sharif University of Technology, Tehran, Iran.
  • Arsalan Salari
    Cardiovascular Disease Research Center, Department of Cardiology, School of Medicine, Heshmat Hospital, Guilan University of Medical Sciences, Rasht, Iran.
  • Hossein Sadr
    Department of Computer Engineering, Rahbord Shomal Institute of Higher Education, Rasht, Iran.

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