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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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 |
work_keys_str_mv |
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1725572443660091392 |