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A Probabilistic Approach to Computerized Tracking of Arterial Walls in Ultrasound Image Sequences

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posted on 2016-05-31, 11:58 authored by Baris Kanber, Kumar Vids Ramnarine
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.

History

Citation

ISRN Signal Processing, 2012: 179087

Author affiliation

/Organisation/COLLEGE OF MEDICINE, BIOLOGICAL SCIENCES AND PSYCHOLOGY/School of Medicine/Department of Cardiovascular Sciences

Version

  • VoR (Version of Record)

Published in

ISRN Signal Processing

Publisher

Hindawi Publishing Corporation

issn

2090-5041

eissn

2090-505X

Acceptance date

2012-11-19

Copyright date

2012

Available date

2016-05-31

Publisher version

http://www.hindawi.com/journals/isrn/2012/179087/

Language

en

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