LEFT VENTRICLE IMAGE LANDMARKS EXTRACTION USING SUPPORT VECTOR MACHINES
Miguel Ángel Vera, Antonio Bravo · 2007
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.