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Authors: Antonio Bravo 1 ; José Clemente 1 and Rubén Medina 2

Affiliations: 1 Universidad Nacional Experimental del Táchira, Venezuela ; 2 Universidad de Los Andes, Venezuela

Keyword(s): Segmentation, Unsupervised clustering, Mean shift, Cardiac images, Human heart, Left ventricle.

Related Ontology Subjects/Areas/Topics: Computer Vision, Visualization and Computer Graphics ; Image and Video Analysis ; Segmentation and Grouping

Abstract: In this paper an image segmentation scheme that is based on combinations of a non–parametric technique and a seed based clustering algorithm is reported. The method has been applied to clinical unsubtracted angiograms of the human heart. The first step of the method consists in applying a mean shift–based filter in order to improve the left ventricle cavity information in angiographic images. Second, the initial seed is semi–automatically generated from the aortic valve manual localization by a specialist. Third, each angiographic image is segmented using a clustering algorithm that begins with the seed which is grown until image pixels associated to the left ventricle cavity are clustered. A validation is performed by comparing the estimated contours with respect to contours manually traced by a cardiologists. From this validation stage the maximum of the average contour error considering six angiographic sequences (a total of 178 images) is 7.30 % .

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Paper citation in several formats:
Bravo, A.; Clemente, J. and Medina, R. (2010). SEED–GROWING HEART SEGMENTATION IN HUMAN ANGIOGRAMS. In Proceedings of the International Conference on Computer Vision Theory and Applications (VISIGRAPP 2010) - Volume 2: VISAPP; ISBN 978-989-674-029-0; ISSN 2184-4321, SciTePress, pages 91-96. DOI: 10.5220/0002848900910096

@conference{visapp10,
author={Antonio Bravo. and José Clemente. and Rubén Medina.},
title={SEED–GROWING HEART SEGMENTATION IN HUMAN ANGIOGRAMS},
booktitle={Proceedings of the International Conference on Computer Vision Theory and Applications (VISIGRAPP 2010) - Volume 2: VISAPP},
year={2010},
pages={91-96},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002848900910096},
isbn={978-989-674-029-0},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the International Conference on Computer Vision Theory and Applications (VISIGRAPP 2010) - Volume 2: VISAPP
TI - SEED–GROWING HEART SEGMENTATION IN HUMAN ANGIOGRAMS
SN - 978-989-674-029-0
IS - 2184-4321
AU - Bravo, A.
AU - Clemente, J.
AU - Medina, R.
PY - 2010
SP - 91
EP - 96
DO - 10.5220/0002848900910096
PB - SciTePress

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