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Automatic segmentation of the left ventricle cavity and myocardium in MRI data

Lynch, Michael and Ghita, Ovidiu and Whelan, Paul F. (2006) Automatic segmentation of the left ventricle cavity and myocardium in MRI data. Computers in Biology and Medicine, 36 (4). pp. 389-407. ISSN 0010-4825

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A novel approach for the automatic segmentation has been developed to extract the epi-cardium and endo-cardium boundaries of the left ventricle (lv) of the heart. The developed segmentation scheme takes multi-slice and multi-phase magnetic resonance (MR) images of the heart, transversing the short-axis length from the base to the apex. Each image is taken at one instance in the heart's phase. The images are segmented using a diffusion-based filter followed by an unsupervised clustering technique and the resulting labels are checked to locate the (lv) cavity. From cardiac anatomy, the closest pool of blood to the lv cavity is the right ventricle cavity. The wall between these two blood-pools (interventricular septum) is measured to give an approximate thickness for the myocardium. This value is used when a radial search is performed on a gradient image to find appropriate robust segments of the epi-cardium boundary. The robust edge segments are then joined using a normal spline curve. Experimental results are presented with very encouraging qualitative and quantitative results and a comparison is made against the state-of-the art level-sets method.

Item Type:Article (Published)
Uncontrolled Keywords:image analysis; MRI; left ventricle; segmentation; myocardium; clustering; level-set;
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Engineering and Computing > School of Electronic Engineering
Research Initiatives and Centres > Research Institute for Networks and Communications Engineering (RINCE)
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Copyright Information:Copyright © 2005 Elsevier Ltd
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
ID Code:4678
Deposited On:07 Jul 2009 11:19 by DORAS Administrator. Last Modified 27 Oct 2017 10:02

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