Real-time Detection of Aortic Valve in Echocardiography using Convolutional Neural Networks.

Journal: Current medical imaging
PMID:

Abstract

BACKGROUND: Valvular heart disease is a serious disease leading to mortality and increasing medical care cost. The aortic valve is the most common valve affected by this disease. Doctors rely on echocardiogram for diagnosing and evaluating valvular heart disease. However, the images from echocardiogram are poor in comparison to Computerized Tomography and Magnetic Resonance Imaging scan. This study proposes the development of Convolutional Neural Networks (CNN) that can function optimally during a live echocardiographic examination for detection of the aortic valve. An automated detection system in an echocardiogram will improve the accuracy of medical diagnosis and can provide further medical analysis from the resulting detection.

Authors

  • Muhammad Hanif Ahmad Nizar
    Department of Biomedical Engineering, Faculty of Engineering, University of Malaya, Jalan Universiti, Kuala Lumpur 50603, Malaysia.
  • Chow Khuen Chan
    Department of Biomedical Engineering, Faculty of Engineering, University of Malaya, Jalan Universiti, Kuala Lumpur 50603, Malaysia.
  • Azira Khalil
    Faculty of Science and Technology, Islamic Science University of Malaysia, 71800, Nilai, Negeri Sembilan, Malaysia.
  • Ahmad Khairuddin Mohamed Yusof
    National Heart Institute, Kuala Lumpur 50400, Malaysia.
  • Khin Wee Lai
    Department of Biomedical Engineering, Faculty of Engineering, University of Malaya, 50603, Kuala Lumpur, Malaysia.