Endocardial Border Detection Using Radial Search and Domain Knowledge
Abstract: The ejection
fraction rate is a frequently used parameter when treating patients who
suffered from heart disease. However, the measurement of this ejection rate
depends on manual segmentation of left ventricle cavity in the end-systolic and
end-diastolic phases. This paper proposes a semi-automatic algorithm for the
detection of left ventricular border in two dimensional long axis ultrasound
echocardiographic images. First, we apply a preprocessing filter to the
ultrasound for the sake of speckle reduction. Then the knowledge of the anatomical
structure of human heart and local homogeneity of blood pool is being used to
detect the border of left ventricle. The proposed method evaluates 80
ultrasound images from four healthy volunteers and the generated contours are
compared with contours manually drawn by an expert. The measured Dice Metric
and Hausdorff Distance recorded by the proposed algorithm are 85.1% ± 0.4% and
3.25 ± 0.46 mm respectively. The numerical results reported in this paper
indicate that the proposed algorithm is able to correctly segment the left
ventricle cavity and can be used as an alternative to manual contouring of left
ventricle cavity from ultrasound images.
Keywords: border detection;
radial search; domain knowledge; segmentation of left ventricle;
echocardiography
Author: Yong Chen, DongC Liu
Journal Code: jptkomputergg140028
