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Current Medical Imaging

Editor-in-Chief

ISSN (Print): 1573-4056
ISSN (Online): 1875-6603

Research Article

Segmentation of Short Axis CMR Images Using Hybrid Method

Author(s): A.V. Nageswararao*, S. Peter Babu and S. Srinivasan

Volume 14, Issue 3, 2018

Page: [461 - 467] Pages: 7

DOI: 10.2174/1573405613666170504151357

Price: $65

Abstract

Background: Highly advanced and sophisticated imaging modality, Cardiac Magnetic Resonance (CMR) images are referred to examine the cardiac morphology and its function.

Methods: In this work, the main aim is to develop a hybrid segmentation method for automatic segmentation of both left, right ventricles from short axis CMR images. In the proposed hybrid segmentation method, Fast Adaptive K-Means (FAKM) clustering method is used to locate the ventricles which are further segmented by Distance Regularized Level Set Evolution (DRLSE) method.

Results: The validation parameters show that the segmentation by proposed hybrid method is better than hybrid methods like Gaussian mixture model with dynamic programming and semi-automatic method.

Discussions: Further, FAKM hybrid method is evaluated based on End Systolic Volume (ESV), End Diastolic Volume (EDV) and Ejection Fraction (EF).

Conclusion: The analytical result shows that the hybrid method of FAKM with DRLSE gives faster and better results.

Keywords: Clustering, level set, DRLSE, EDV, Ejection Fraction (EF), CMR images.

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