LEFT VENTRICLE IMAGE LANDMARKS EXTRACTION USING SUPPORT VECTOR MACHINES

Miguel A. Vera, Antonio J. Bravo

Abstract

This paper introduces an approach for efficient myocardial landmarks detection in angiograms. Several anatomical landmarks located on the left ventricle are obtained by mean of a support vector machine. Training set corresponds a dataset of landmark and non-landmark 31×31 pixel patterns. Our support vector machine uses the structural risk minimization principle as inference rule and radial basis function kernel. In the training phase false positives were not registered and in the detection phase 100% of recognition was obtained.

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Paper Citation


in Harvard Style

A. Vera M. and J. Bravo A. (2007). LEFT VENTRICLE IMAGE LANDMARKS EXTRACTION USING SUPPORT VECTOR MACHINES . In Proceedings of the Second International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, ISBN 978-972-8865-73-3, pages 339-343. DOI: 10.5220/0002059503390343


in Bibtex Style

@conference{visapp07,
author={Miguel A. Vera and Antonio J. Bravo},
title={LEFT VENTRICLE IMAGE LANDMARKS EXTRACTION USING SUPPORT VECTOR MACHINES},
booktitle={Proceedings of the Second International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP,},
year={2007},
pages={339-343},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002059503390343},
isbn={978-972-8865-73-3},
}


in EndNote Style

TY - CONF
JO - Proceedings of the Second International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP,
TI - LEFT VENTRICLE IMAGE LANDMARKS EXTRACTION USING SUPPORT VECTOR MACHINES
SN - 978-972-8865-73-3
AU - A. Vera M.
AU - J. Bravo A.
PY - 2007
SP - 339
EP - 343
DO - 10.5220/0002059503390343