Biomedical Image Processing / Medical Image Processing
Mehdi Marsousi; Javad Alirezaie; Armen Kocharian
Volume 2, Issue 3 , June 2008, , Pages 203-214
Abstract
In this paper, a new method for boundary detection of left ventricle in echocardiography images is proposed. We have modified B-Spline Snake algorithm to achieve much faster convergence and more reliability toward noises in echocardiography images. A novel approach for inserting new node points during ...
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In this paper, a new method for boundary detection of left ventricle in echocardiography images is proposed. We have modified B-Spline Snake algorithm to achieve much faster convergence and more reliability toward noises in echocardiography images. A novel approach for inserting new node points during iterations is applied to maintain a maximum distance between two adjacent nodes. This strategy is applied in order to simultaneously increase the smoothness of the contour and optimize the computational time. A multi-resolution strategy is also adapted to provide further robustness toward noises in the images. In addition, morphological operators are utilized to specify the initial contour automatically within the left ventricle chamber in echocardiography images. The parameters of node points are determined during each transition from coarser to finer resolution according to the average intensity of the sample points on the contour near each node point. The volumes of left ventricle in the end of both systolic and diastolic frames are calculated using modified Simpson method. The ejection fraction ratio is also calculated; this is frequently used by specialist before each surgery. Moreover, a method is introduced to draw the 3D model of left ventricle with the aid of basis function of B-Spline. The proposed method is assessed by comparison between the obtained results and clinical observations by expert radiologists and demonstrates a high accuracy.
