Key result
A probabilistic algorithm produced robust lumen segmentation in ultrasound images, showing increased immunity to speckle noise and reduced susceptibility to region overflowing compared to conventional methods.
A novel probabilistic algorithm for tracking arterial walls in ultrasound images offers improved segmentation performance over conventional thresholding techniques by reducing noise interference and boundary overflow.
May aid vascular ultrasound research; leaves open clinical validation before practice adoption.
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.
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Kanber et al. (2012) studied Arterial wall tracking in ultrasound images. Probabilistic algorithm for computerized tracking vs. Conventional region growing technique based on intensity thresholding was evaluated on Lumen segmentation efficacy and robustness. A probabilistic algorithm produced robust lumen segmentation in ultrasound images, showing increased immunity to speckle noise and reduced susceptibility to region overflowing compared to conventional methods.
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