Journal
ULTRASOUND IN MEDICINE AND BIOLOGY
Volume 34, Issue 9, Pages 1482-1498Publisher
ELSEVIER SCIENCE INC
DOI: 10.1016/j.ultrasmedbio.2008.01.022
Keywords
intravascular ultrasound; contour detection; segmentation; radial basis functions
Funding
- GSRT
- GSRT A8-PK06
- Greek State Scholarships Foundation
- Aristotle University Research Committee
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Intravascular ultrasound (IVUS) constitutes a valuable technique for the diagnosis of coronary atherosclerosis. The detection of lumen and media-adventitia borders in IVUS images represents a necessary step towards the reliable quantitative assessment of atherosclerosis. In this work, a fully automated technique for the detection of lumen and media-adventitia borders in IVUS images is presented. This comprises two different steps for contour initialization: one for each corresponding contour of interest and a procedure for the refinement of the detected contours. Intensity information, as well as the result of texture analysis, generated by means of a multilevel discrete wavelet frames decomposition, are used in two different techniques for contour initialization. For subsequently producing smooth contours, three techniques based on low-pass filtering and radial basis functions are introduced. The different combinations of the proposed methods are experimentally evaluated in large datasets of IVUS images derived from human coronary arteries. It is demonstrated that our proposed segmentation approaches can quickly and reliably perform automated segmentation of IVUS images.
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