Authors:
Prashant Bansod
1
;
U. B. Desai
1
and
Nitin Burkule
2
Affiliations:
1
Indian Institute of Technology, India
;
2
Cardiologist, Asian Heart Hospital and Research Center, India
Keyword(s):
Contrast echocardiography, Left ventricle, Segmentation, Spatio-temporal clustering.
Related
Ontology
Subjects/Areas/Topics:
Applications and Services
;
Biomedical Engineering
;
Biomedical Signal Processing
;
Computer Vision, Visualization and Computer Graphics
;
Medical Image Detection, Acquisition, Analysis and Processing
Abstract:
We present a spatio-temporal clustering algorithm for detection of endocardial contours in short axis (SAX) contrast echocardiographic image sequences. A semiautomatic method for segmentation of left ventricle in SAX videos is proposed which uses this algorithm and at the same time requires minimal expert intervention. Expert is required to specify a few candidate points belonging to the contour, only in the first frame of the sequence. The initial contour is approximated by fitting an ellipse in the region defined by the points specified. This region is identified as the principal cluster corresponding to the left ventriclular cavity. Later the density based clustering was applied for regularization on the inital contour. We have extended the DBSCAN algorithm for identification of the principal cluster corresponding to the left ventricle from the image. The algorithm also incorporates the temporal information from the adjacent frames during the segmentation process. The algorithm de
veloped was applied to 10 data sets over full cardiac cycle and the results were validated by comparing computer generated boundaries to those manually outlined by one expert. The maximum error in the contours detected was ±2.9mm. The spatio-temporal clustering algorithm proposed in this paper offers an efficient semiautomatic segmentation of heart chambers in 2D contrast echocardiography sequences.
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