Segmentation of jet area to quantity the severity of mitral regurgitation by color Doppler echocardiography

Mitral regurgitation (MR) is a disorder of mitral valve and it is one of the most common causes of cardiovascular morbidity and mortality. Mitral valve allows blood to flow from left atrium, to the left ventricle and Mitral Valve regurgitation results in poor apposition of the valvular leaflets, so...

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Main Authors: N Chidambaram, G N Balaji, T S Subashini
Format: Article
Language:English
Published: Wolters Kluwer Medknow Publications 2018-01-01
Series:International Journal of Noncommunicable Diseases
Subjects:
SVM
Online Access:http://www.ijncd.org/article.asp?issn=2468-8827;year=2018;volume=3;issue=4;spage=134;epage=138;aulast=Chidambaram
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spelling doaj-b796e55e8ce74746a0a3ff392fcb73a92020-11-25T01:30:20ZengWolters Kluwer Medknow PublicationsInternational Journal of Noncommunicable Diseases2468-88272468-88352018-01-013413413810.4103/jncd.jncd_50_18Segmentation of jet area to quantity the severity of mitral regurgitation by color Doppler echocardiographyN ChidambaramG N BalajiT S SubashiniMitral regurgitation (MR) is a disorder of mitral valve and it is one of the most common causes of cardiovascular morbidity and mortality. Mitral valve allows blood to flow from left atrium, to the left ventricle and Mitral Valve regurgitation results in poor apposition of the valvular leaflets, so that the heart's mitral valve doesn't close tightly, allowing blood to flow backward into the left atrium. Transthoracic Echocardiography (TTE) with Doppler is the widely used non-invasive technology for the detection and evaluation of severity of valvular regurgitation. Proximal isovelocity surface area (PISA) method has been widely accepted by clinicians as a means for grading MR severity. In this paper an alternate method to PISA to automatically quantify mitral valve regurgitation severity is proposed. This work attempts to automatically segment the jet region in color Doppler images using K-Means clustering. Further to quantify mitral regurgitation, jet area parameters and shape features are extracted from the segmented jet region which are then modeled using classifiers such as Support Vector machine (SVM) and Back Propagation Neural Network (BPNN). Quantifying MR with PISA calls for considerable expertise as a number of components must be taken into account to fully assess the severity of mitral regurgitation, however the results of the proposed method indicate that it could be used as an alternate method to automatically assess the severity of mitral regurgitation.http://www.ijncd.org/article.asp?issn=2468-8827;year=2018;volume=3;issue=4;spage=134;epage=138;aulast=ChidambaramBPNNcolor Dopplerjet area parametersK-meansmitral regurgitationregurgitant jetshape featuresSVM
collection DOAJ
language English
format Article
sources DOAJ
author N Chidambaram
G N Balaji
T S Subashini
spellingShingle N Chidambaram
G N Balaji
T S Subashini
Segmentation of jet area to quantity the severity of mitral regurgitation by color Doppler echocardiography
International Journal of Noncommunicable Diseases
BPNN
color Doppler
jet area parameters
K-means
mitral regurgitation
regurgitant jet
shape features
SVM
author_facet N Chidambaram
G N Balaji
T S Subashini
author_sort N Chidambaram
title Segmentation of jet area to quantity the severity of mitral regurgitation by color Doppler echocardiography
title_short Segmentation of jet area to quantity the severity of mitral regurgitation by color Doppler echocardiography
title_full Segmentation of jet area to quantity the severity of mitral regurgitation by color Doppler echocardiography
title_fullStr Segmentation of jet area to quantity the severity of mitral regurgitation by color Doppler echocardiography
title_full_unstemmed Segmentation of jet area to quantity the severity of mitral regurgitation by color Doppler echocardiography
title_sort segmentation of jet area to quantity the severity of mitral regurgitation by color doppler echocardiography
publisher Wolters Kluwer Medknow Publications
series International Journal of Noncommunicable Diseases
issn 2468-8827
2468-8835
publishDate 2018-01-01
description Mitral regurgitation (MR) is a disorder of mitral valve and it is one of the most common causes of cardiovascular morbidity and mortality. Mitral valve allows blood to flow from left atrium, to the left ventricle and Mitral Valve regurgitation results in poor apposition of the valvular leaflets, so that the heart's mitral valve doesn't close tightly, allowing blood to flow backward into the left atrium. Transthoracic Echocardiography (TTE) with Doppler is the widely used non-invasive technology for the detection and evaluation of severity of valvular regurgitation. Proximal isovelocity surface area (PISA) method has been widely accepted by clinicians as a means for grading MR severity. In this paper an alternate method to PISA to automatically quantify mitral valve regurgitation severity is proposed. This work attempts to automatically segment the jet region in color Doppler images using K-Means clustering. Further to quantify mitral regurgitation, jet area parameters and shape features are extracted from the segmented jet region which are then modeled using classifiers such as Support Vector machine (SVM) and Back Propagation Neural Network (BPNN). Quantifying MR with PISA calls for considerable expertise as a number of components must be taken into account to fully assess the severity of mitral regurgitation, however the results of the proposed method indicate that it could be used as an alternate method to automatically assess the severity of mitral regurgitation.
topic BPNN
color Doppler
jet area parameters
K-means
mitral regurgitation
regurgitant jet
shape features
SVM
url http://www.ijncd.org/article.asp?issn=2468-8827;year=2018;volume=3;issue=4;spage=134;epage=138;aulast=Chidambaram
work_keys_str_mv AT nchidambaram segmentationofjetareatoquantitytheseverityofmitralregurgitationbycolordopplerechocardiography
AT gnbalaji segmentationofjetareatoquantitytheseverityofmitralregurgitationbycolordopplerechocardiography
AT tssubashini segmentationofjetareatoquantitytheseverityofmitralregurgitationbycolordopplerechocardiography
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