Segmentation of Left and Right Ventricles in Cardiac MRI Using Active Contours

Segmentation of left and right ventricles plays a crucial role in quantitatively analyzing the global and regional information in the cardiac magnetic resonance imaging (MRI). In MRI, the intensity inhomogeneity and weak or blurred object boundaries are the problems, which makes it difficult for the...

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Main Authors: Shafiullah Soomro, Farhan Akram, Asad Munir, Chang Ha Lee, Kwang Nam Choi
Format: Article
Language:English
Published: Hindawi Limited 2017-01-01
Series:Computational and Mathematical Methods in Medicine
Online Access:http://dx.doi.org/10.1155/2017/8350680
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spelling doaj-5a713e899de14825991f39ed50befd132020-11-24T23:21:11ZengHindawi LimitedComputational and Mathematical Methods in Medicine1748-670X1748-67182017-01-01201710.1155/2017/83506808350680Segmentation of Left and Right Ventricles in Cardiac MRI Using Active ContoursShafiullah Soomro0Farhan Akram1Asad Munir2Chang Ha Lee3Kwang Nam Choi4Department of Computer Science and Engineering, Chung-Ang University, Seoul 156-756, Republic of KoreaDepartment of Computer Engineering and Mathematics, Rovira i Virgili University, 43007 Tarragona, SpainDepartment of Computer Science and Engineering, Chung-Ang University, Seoul 156-756, Republic of KoreaDepartment of Computer Science and Engineering, Chung-Ang University, Seoul 156-756, Republic of KoreaDepartment of Computer Science and Engineering, Chung-Ang University, Seoul 156-756, Republic of KoreaSegmentation of left and right ventricles plays a crucial role in quantitatively analyzing the global and regional information in the cardiac magnetic resonance imaging (MRI). In MRI, the intensity inhomogeneity and weak or blurred object boundaries are the problems, which makes it difficult for the intensity-based segmentation methods to properly delineate the regions of interests (ROI). In this paper, a hybrid signed pressure force function (SPF) is proposed, which yields both local and global image fitted differences in an additive fashion. A characteristic term is also introduced in the SPF function to restrict the contour within the ROI. The overlapping dice index and Hausdorff-Distance metrics have been used over cardiac datasets for quantitative validation. Using 2009 LV MICCAI validation dataset, the proposed method yields DSC values of 0.95 and 0.97 for endocardial and epicardial contours, respectively. Using 2012 RV MICCAI dataset, for the endocardial region, the proposed method yields DSC values of 0.97 and 0.90 and HD values of 8.51 and 7.67 for ED and ES, respectively. For the epicardial region, it yields DSC values of 0.92 and 0.91 and HD values of 6.47 and 9.34 for ED and ES, respectively. Results show its robustness in the segmentation application of the cardiac MRI.http://dx.doi.org/10.1155/2017/8350680
collection DOAJ
language English
format Article
sources DOAJ
author Shafiullah Soomro
Farhan Akram
Asad Munir
Chang Ha Lee
Kwang Nam Choi
spellingShingle Shafiullah Soomro
Farhan Akram
Asad Munir
Chang Ha Lee
Kwang Nam Choi
Segmentation of Left and Right Ventricles in Cardiac MRI Using Active Contours
Computational and Mathematical Methods in Medicine
author_facet Shafiullah Soomro
Farhan Akram
Asad Munir
Chang Ha Lee
Kwang Nam Choi
author_sort Shafiullah Soomro
title Segmentation of Left and Right Ventricles in Cardiac MRI Using Active Contours
title_short Segmentation of Left and Right Ventricles in Cardiac MRI Using Active Contours
title_full Segmentation of Left and Right Ventricles in Cardiac MRI Using Active Contours
title_fullStr Segmentation of Left and Right Ventricles in Cardiac MRI Using Active Contours
title_full_unstemmed Segmentation of Left and Right Ventricles in Cardiac MRI Using Active Contours
title_sort segmentation of left and right ventricles in cardiac mri using active contours
publisher Hindawi Limited
series Computational and Mathematical Methods in Medicine
issn 1748-670X
1748-6718
publishDate 2017-01-01
description Segmentation of left and right ventricles plays a crucial role in quantitatively analyzing the global and regional information in the cardiac magnetic resonance imaging (MRI). In MRI, the intensity inhomogeneity and weak or blurred object boundaries are the problems, which makes it difficult for the intensity-based segmentation methods to properly delineate the regions of interests (ROI). In this paper, a hybrid signed pressure force function (SPF) is proposed, which yields both local and global image fitted differences in an additive fashion. A characteristic term is also introduced in the SPF function to restrict the contour within the ROI. The overlapping dice index and Hausdorff-Distance metrics have been used over cardiac datasets for quantitative validation. Using 2009 LV MICCAI validation dataset, the proposed method yields DSC values of 0.95 and 0.97 for endocardial and epicardial contours, respectively. Using 2012 RV MICCAI dataset, for the endocardial region, the proposed method yields DSC values of 0.97 and 0.90 and HD values of 8.51 and 7.67 for ED and ES, respectively. For the epicardial region, it yields DSC values of 0.92 and 0.91 and HD values of 6.47 and 9.34 for ED and ES, respectively. Results show its robustness in the segmentation application of the cardiac MRI.
url http://dx.doi.org/10.1155/2017/8350680
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