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Carotid Artery Contour Extraction from Ultrasound Images Using Multi-Resolution-Analysis and Watershed Segmentation Scheme Amr R. Abdel-Dayem and Mahmoud R. El-Sakka, Senior Member, IEEE Computer Science Department, University of Western Ontario London, Ontario, Canada ABSTRACT This paper introduces a novel segmentation scheme based on multi-resolution analysis and watershed segmentation algorithm. The proposed scheme consists of six major stages. These stages are 1) pre-processing, 2) wavelet transform, 3) image denoising, 4) watershed segmentation, 5) segmented image projection and finally 6) boundary extraction. Experimental results demonstrated the efficiency of the proposed scheme in segmenting carotid artery ultrasound images, where the computational cost of the watershed-based segmentation scheme is reduced, as it is applied to a small low‑resolution image. At the same time, the segmentation accuracy is increased as the proposed scheme is more robust to noise and hence, it prevents over segmentation in final segmented images. Keywords: Wavelet transforms; watershed segmentation; computer aided diagnostic; plaque precipitation.
BIOGRAPHY:
BibTex: @ARTICLE{P1150547002,
AUTHOR = {Amr R. Abdel-Dayem
and Mahmoud R. El-Sakka},
TITLE = {Carotid Artery Contour Extraction from Ultrasound Images Using Multi-Resolution-Analysis and Watershed Segmentation Scheme}, JOURNAL = {ICGST International Journal on Graphics, Vision and Image Processing}, YEAR = {2005}, VOLUME={05}, ISSUE = {9}, PAGES={1--10} } ( |
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