This paper presents a hybrid method to extract endocardial contour of the right ventricular (RV) in 4-slices from 3D\nechocardiography dataset. The overall framework comprises four processing phases. In Phase I, the region of interest (ROI) is\nidentified by estimating the cavity boundary. Speckle noise reduction and contrast enhancement were implemented in Phase II as\npreprocessing tasks. In Phase III, the RV cavity region was segmented by generating intensity threshold which was used for once\nfor all frames. Finally, Phase IV is proposed to extract the RV endocardial contour in a complete cardiac cycle using a combination\nof shape-based contour detection and improved radial search algorithm. The proposed method was applied to 16 datasets of 3D\nechocardiography encompassing the RV in long-axis view. The accuracy of experimental results obtained by the proposed method\nwas evaluated qualitatively and quantitatively. It has been done by comparing the segmentation results of RV cavity based on\nendocardial contour extraction with the ground truth.The comparative analysis results show that the proposed method performs\nefficiently in all datasets with overall performance of 95% and the root mean square distances (RMSD) measure in terms of mean\n�± SD was found to be 2.21 �± 0.35mm for RV endocardial contours.
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