Robust and automatic diagnosis of the intraventricular mechanical dyssynchrony for the left ventricle in cardiac magnetic resonance images

Robust and automatic diagnosis of the intraventricular mechanical dyssynchrony for the left... Int J CARS (2017) 12:1471–1480 DOI 10.1007/s11548-017-1574-9 ORIGINAL ARTICLE Robust and automatic diagnosis of the intraventricular mechanical dyssynchrony for the left ventricle in cardiac magnetic resonance images Zhenzhou Wang Received: 21 October 2016 / Accepted: 20 March 2017 / Published online: 27 March 2017 © CARS 2017 Abstract Keywords Left ventricular dyssynchrony · Auto-diagnosis · Purpose Robust and automatic diagnosis of the mechanical Image processing · Cross-correlation · Fourier shape filter dyssynchrony for the left ventricle is essential for the car- diac resynchronization therapy. However, no existing method could meet the desired accuracy yet. In this paper, a new Introduction approach is proposed for auto-diagnosis of the intraventricu- lar mechanical dyssynchrony of the left ventricle based on a Cardiac resynchronization therapy (CRT) has been grow- series of image processing and signal processing techniques. ing dramatically over time ever since its fist introduction Methods Firstly, the boundary of the left ventricle is iden- in the early 1990s. It has been demonstrated that CRT tified automatically by the segmentation method. Secondly, could significantly improve the symptoms, exercise toler- the correspondence trajectories are computed based on the ance and the quality of life. A major predictor of response tangent field to make http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Computer Assisted Radiology and Surgery Springer Journals

Robust and automatic diagnosis of the intraventricular mechanical dyssynchrony for the left ventricle in cardiac magnetic resonance images

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Publisher
Springer International Publishing
Copyright
Copyright © 2017 by CARS
Subject
Medicine & Public Health; Imaging / Radiology; Surgery; Health Informatics; Computer Imaging, Vision, Pattern Recognition and Graphics; Computer Science, general
ISSN
1861-6410
eISSN
1861-6429
D.O.I.
10.1007/s11548-017-1574-9
Publisher site
See Article on Publisher Site

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