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Evaluation of a Semi-automatic Right Ventricle Segmentation Method on Short-Axis MR Images

The purpose of this study was to evaluate a semi-automatic right ventricle segmentation method on short-axis cardiac cine MR images which segment all right ventricle contours in a cardiac phase using one seed contour. Twenty-eight consecutive short-axis, four-chamber, and tricuspid valve view cardia...

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Autores principales: Yilmaz, Pinar, Wallecan, Karel, Kristanto, Wisnumurti, Aben, Jean-Paul, Moelker, Adriaan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6148820/
https://www.ncbi.nlm.nih.gov/pubmed/29524154
http://dx.doi.org/10.1007/s10278-018-0061-3
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author Yilmaz, Pinar
Wallecan, Karel
Kristanto, Wisnumurti
Aben, Jean-Paul
Moelker, Adriaan
author_facet Yilmaz, Pinar
Wallecan, Karel
Kristanto, Wisnumurti
Aben, Jean-Paul
Moelker, Adriaan
author_sort Yilmaz, Pinar
collection PubMed
description The purpose of this study was to evaluate a semi-automatic right ventricle segmentation method on short-axis cardiac cine MR images which segment all right ventricle contours in a cardiac phase using one seed contour. Twenty-eight consecutive short-axis, four-chamber, and tricuspid valve view cardiac cine MRI examinations of healthy volunteers were used. Two independent observers performed the manual and automatic segmentations of the right ventricles. Analyses were based on the ventricular volume and ejection fraction of the right heart chamber. Reproducibility of the manual and semi-automatic segmentations was assessed using intra- and inter-observer variability. Validity of the semi-automatic segmentations was analyzed with reference to the manual segmentations. The inter- and intra-observer variability of manual segmentations were between 0.8 and 3.2%. The semi-automatic segmentations were highly correlated with the manual segmentations (R(2) 0.79–0.98), with median difference of 0.9–4.8% and of 3.3% for volume and ejection fraction parameters, respectively. In comparison to the manual segmentation, the semi-automatic segmentation produced contours with median dice metrics of 0.95 and 0.87 and median Hausdorff distance of 5.05 and 7.35 mm for contours at end-diastolic and end-systolic phases, respectively. The inter- and intra-observer variability of the semi-automatic segmentations were lower than observed in the manual segmentations. Both manual and semi-automatic segmentations performed better at the end-diastolic phase than at the end-systolic phase. The investigated semi-automatic segmentation method managed to produce a valid and reproducible alternative to manual right ventricle segmentation.
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spelling pubmed-61488202018-09-26 Evaluation of a Semi-automatic Right Ventricle Segmentation Method on Short-Axis MR Images Yilmaz, Pinar Wallecan, Karel Kristanto, Wisnumurti Aben, Jean-Paul Moelker, Adriaan J Digit Imaging Article The purpose of this study was to evaluate a semi-automatic right ventricle segmentation method on short-axis cardiac cine MR images which segment all right ventricle contours in a cardiac phase using one seed contour. Twenty-eight consecutive short-axis, four-chamber, and tricuspid valve view cardiac cine MRI examinations of healthy volunteers were used. Two independent observers performed the manual and automatic segmentations of the right ventricles. Analyses were based on the ventricular volume and ejection fraction of the right heart chamber. Reproducibility of the manual and semi-automatic segmentations was assessed using intra- and inter-observer variability. Validity of the semi-automatic segmentations was analyzed with reference to the manual segmentations. The inter- and intra-observer variability of manual segmentations were between 0.8 and 3.2%. The semi-automatic segmentations were highly correlated with the manual segmentations (R(2) 0.79–0.98), with median difference of 0.9–4.8% and of 3.3% for volume and ejection fraction parameters, respectively. In comparison to the manual segmentation, the semi-automatic segmentation produced contours with median dice metrics of 0.95 and 0.87 and median Hausdorff distance of 5.05 and 7.35 mm for contours at end-diastolic and end-systolic phases, respectively. The inter- and intra-observer variability of the semi-automatic segmentations were lower than observed in the manual segmentations. Both manual and semi-automatic segmentations performed better at the end-diastolic phase than at the end-systolic phase. The investigated semi-automatic segmentation method managed to produce a valid and reproducible alternative to manual right ventricle segmentation. Springer International Publishing 2018-03-09 2018-10 /pmc/articles/PMC6148820/ /pubmed/29524154 http://dx.doi.org/10.1007/s10278-018-0061-3 Text en © The Author(s) 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Article
Yilmaz, Pinar
Wallecan, Karel
Kristanto, Wisnumurti
Aben, Jean-Paul
Moelker, Adriaan
Evaluation of a Semi-automatic Right Ventricle Segmentation Method on Short-Axis MR Images
title Evaluation of a Semi-automatic Right Ventricle Segmentation Method on Short-Axis MR Images
title_full Evaluation of a Semi-automatic Right Ventricle Segmentation Method on Short-Axis MR Images
title_fullStr Evaluation of a Semi-automatic Right Ventricle Segmentation Method on Short-Axis MR Images
title_full_unstemmed Evaluation of a Semi-automatic Right Ventricle Segmentation Method on Short-Axis MR Images
title_short Evaluation of a Semi-automatic Right Ventricle Segmentation Method on Short-Axis MR Images
title_sort evaluation of a semi-automatic right ventricle segmentation method on short-axis mr images
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6148820/
https://www.ncbi.nlm.nih.gov/pubmed/29524154
http://dx.doi.org/10.1007/s10278-018-0061-3
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