Evidence map›Paper›PMID 25298930›Full record

ArticleJournal of medical signals and sensors2014

Right ventricle functional parameters estimation in arrhythmogenic right ventricular dysplasia using a robust shape based deformable model.

Mostafa Ghelich Oghli, Vahab Dehlaghi, Ali Mohammad Zadeh, Alireza Fallahi, Mohammad Pooyan

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Article in Journal of medical signals and sensors, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.4field-weighted citation impact, top 35% of its field
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 4 citations in OpenAlex.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors at 4 institutions in 1 country.

Mostafa Ghelich OghliDepartment of Biomedical Engineering, Kermanshah University of Medical Sciences, Kermanshah, Iran.
Vahab DehlaghiDepartment of Biomedical Engineering, Kermanshah University of Medical Sciences, Kermanshah, Iran.
Ali Mohammad ZadehDepartment of Radiology, Shaheed Rajaei Cardiovascular, Medical and Research Center, Tehran, Iran.
Alireza FallahiDepartment of Biomedical Engineering, Hamedan University of Technology, Hamedan, Iran.
Mohammad PooyanDepartment of Biomedical Engineering, Shahed University, Tehran, Iran.
Kermanshah University of Medical Sciences · IRHamedan University of Technology · IRShahed University · IRShaheed Rajaei Cardiovascular Medical and Research Center · IR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Assessment of cardiac right-ventricle functions plays an essential role in diagnosis of arrhythmogenic right ventricular dysplasia (ARVD). Among clinical tests, cardiac magnetic resonance imaging (MRI) is now becoming the most valid imaging technique to diagnose ARVD. Fatty infiltration of the right ventricular free wall can be visible on cardiac MRI. Finding right-ventricle functional parameters from cardiac MRI images contains segmentation of right-ventricle in each slice of end diastole and end systole phases of cardiac cycle and calculation of end diastolic and end systolic volume and furthermore other functional parameters. The main problem of this task is the segmentation part. We used a robust method based on deformable model that uses shape information for segmentation of right-ventricle in short axis MRI images. After segmentation of right-ventricle from base to apex in end diastole and end systole phases of cardiac cycle, volume of right-ventricle in these phases calculated and then, ejection fraction calculated. We performed a quantitative evaluation of clinical cardiac parameters derived from the automatic segmentation by comparison against a manual delineation of the ventricles. The manually and automatically determined quantitative clinical parameters were statistically compared by means of linear regression. This fits a line to the data such that the root-mean-square error (RMSE) of the residuals is minimized. The results show low RMSE for Right Ventricle Ejection Fraction and Volume (≤ 0.06 for RV EF, and ≤ 10 mL for RV volume). Evaluation of segmentation results is also done by means of four statistical measures including sensitivity, specificity, similarity index and Jaccard index. The average value of similarity index is 86.87%. The Jaccard index mean value is 83.85% which shows a good accuracy of segmentation. The average of sensitivity is 93.9% and mean value of the specificity is 89.45%. These results show the reliability of proposed method in these cases that manual segmentation is inapplicable. Huge shape variety of right-ventricle led us to use a shape prior based method and this work can develop by four-dimensional processing for determining the first ventricular slices.

Indexed as

Arrhythmogenic right ventricular dysplasiadeformable modelfunctional parameterssegmentationshape prior

Identifiers

PMID25298930
PMCPMC4187356
OpenAlexW1557171741

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LicenceCC BY-NC-SA
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.