A novel solution of using deep learning for left ventricle detection: Enhanced feature extraction.

Journal: Computer methods and programs in biomedicine
Published Date: Sep 15, 2020

Abstract

BACKGROUND AND AIM: deep learning algorithms have not been successfully used for the left ventricle (LV) detection in echocardiographic images due to overfitting and vanishing gradient descent problem. This research aims to increase accuracy and improves the processing time of the left ventricle detection process by reducing the overfitting and vanishing gradient problem.

Authors

  • Kiran Sharma
    School of Computing and Mathematics, Charles Sturt University, Sydney Campus, Australia.
  • Abeer Alsadoon
    School of Computing and Mathematics, Charles Sturt University, Sydney Campus, Sydney, Australia. aalsadoon@studygroup.com.
  • P W C Prasad
    School of Computing and Mathematics, Charles Sturt University, Sydney Campus, Sydney, Australia.
  • Thair Al-Dala'in
    School of Computing and Mathematics, Charles Sturt University, Sydney Campus, Australia.
  • Tran Quoc Vinh Nguyen
    The University of Da Nang - University of Science and Education, Faculty of Information Technology, Vietnam.
  • Duong Thu Hang Pham
    The University of Da Nang - University of Science and Education, Faculty of Information Technology, Vietnam.

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