Please use this identifier to cite or link to this item: http://hdl.handle.net/2381/37668
Title: A Probabilistic Approach to Computerized Tracking of Arterial Walls in Ultrasound Image Sequences
Authors: Kanber, Baris
Ramnarine, Kumar Vids
First Published: 2012
Publisher: Hindawi Publishing Corporation
Citation: ISRN Signal Processing, 2012: 179087
Abstract: Tracking of arterial walls in ultrasound image sequences is useful for studying the dynamics of arteries. Manual delineation is prohibitively labour intensive and existing methods of computerized segmentation are limited in terms of applicability and availability. This paper presents a probabilistic approach to the computerized tracking of arterial walls that is effective and easy to implement. In the probabilistic approach, given a point B with a probability Pb of being in an arterial lumen of interest, the probability Pa that a neighbouring point A is also a part of the same lumen is proportional to Pb with a Gaussian fall in probability with increasing grayscale contrast between the two points. Efficacy of the probabilistic algorithm was evaluated by testing it on ultrasound images and image sequences of the carotid arteries and the abdominal aorta and various laboratory, ultrasound test objects. The results showed that the probabilistic algorithm produced robust and effective lumen segmentation in the majority of cases encountered. Comparison with a conventional region growing technique based on intensity thresholding with a running, regional intensity average identified the main benefits of the probabilistic approach as increased immunity to speckle noise within the arterial lumen and a reduced susceptibility to region overflowing at boundary imperfections.
DOI Link: 10.5402/2012/179087
ISSN: 2090-5041
eISSN: 2090-505X
Links: http://www.hindawi.com/journals/isrn/2012/179087/
http://hdl.handle.net/2381/37668
Version: Publisher Version
Status: Peer-reviewed
Type: Journal Article
Rights: Copyright © 2012 Baris Kanber and Kumar Vids Ramnarine. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Appears in Collections:Published Articles, Dept. of Cardiovascular Sciences

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