Title :
Improved Dempster and Shafer theory to fuse region and edge based level set for endocardial contour detection
Author :
Ketout, Hussin ; GU, Jason ; Horne, Gabrielle
Author_Institution :
Dalhousie Univ., Halifax, NS, Canada
Abstract :
Data fusion is an important tool for improving the performance of a detection system when more than one classifier is available. The reasoning logic of Dempster-Shafer evidence theory for fusion is similar to that of humans. This paper discusses application of a data fusion method which is based on improvements to the Dempster-Shafer theory, to echocardiographic images in order to increase the detection accuracy of the endocardial contours. In this paper, edge and region based level sets are implemented. The Improved Dempster-Shafer evidence fusion algorithm is applied to combine the detected contours resulting in promising results as shown by computational experiments.
Keywords :
echocardiography; edge detection; inference mechanisms; medical image processing; set theory; Dempster-Shafer evidence fusion algorithm; Dempster-Shafer evidence theory; Dempster-Shafer theory; computational experiments; data fusion method; detected contours; detection accuracy; detection system; echocardiographic images; edge based level set; endocardial contour detection; endocardial contours; fuse region; reasoning logic; region based level sets; Deformable models; Equations; Heart; Image edge detection; Image segmentation; Level set; Mathematical model; Dempster-Shafer theory; Echocardiography; Endocardial; Level set; edge based; region based;
Conference_Titel :
Intelligent Control and Automation (WCICA), 2012 10th World Congress on
Conference_Location :
Beijing
Print_ISBN :
978-1-4673-1397-1
DOI :
10.1109/WCICA.2012.6359428