Title :
Discriminating normal and abnormal left ventricular shapes in four-chamber view 2D echocardiography
Author :
Syeda-Mahmood, Tanveer ; Quan Wang ; McNeillie, Patrick ; Beymer, David ; Compas, Colin
Author_Institution :
IBM Almaden Res. Center, San Jose, CA, USA
fDate :
April 29 2014-May 2 2014
Abstract :
In this paper, we address discrimination between normal and abnormal left ventricular shapes by capturing deviations from the normal appearance through a new parametric distorted elliptic shape model. To apply the parametric description, we automatically locate the left ventricular region in 4-chamber views and extract its bounding contours and pose. The parametric description of the elliptic fit with minimum alignment error with the bounding contour then becomes the shape descriptor for the bounding contour. Labeled vectors from normal and damaged left ventricular regions are separated into two classes using a support vector machine. Results are presented on a large database of normal and abnormal left ventricular images showing the effectiveness of the parametric features for normal/abnormal discrimination.
Keywords :
echocardiography; image matching; medical image processing; support vector machines; 2D echocardiography; abnormal left ventricular shape; damaged left ventricular region; elliptic shape model; four-chamber view; minimum alignment error; normal left ventricular shape; parametric distorted model; shape descriptor; support vector machine; Active shape model; Echocardiography; Heart; Image segmentation; Shape; Support vector machine classification; 4-chamber views; LV segmentation; echocardiography; parametric models; shape matching;
Conference_Titel :
Biomedical Imaging (ISBI), 2014 IEEE 11th International Symposium on
Conference_Location :
Beijing
DOI :
10.1109/ISBI.2014.6867893