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 of being in an arterial lumen of interest, the probability that a neighbouring point A is also a part of the same lumen is proportional to 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. 1. Introduction Greyscale ultrasound imaging (B-mode) is an established tool for the noninvasive imaging of the human body. Such imaging procedures are often accompanied by measurements that are conveniently performed using the ultrasonic calipers. However, it becomes a time-consuming manual task for the operator if the measurements need to be repeated a large number of times, for example, over a time series. In B-Mode vascular ultrasound, such a situation arises when one needs to track the position of the arterial walls over many frames in order to study to distension of the arteries throughout the cardiac cycle. Although specific solutions for tracking the position of the arterial walls using B-Mode ultrasound are available (Table 1), for example, by region tracking/block matching [1] or computerized edge detection [2], many of these techniques are limited in terms of applicability and some techniques have particular vulnerability to image noise. Also, a general purpose segmentation algorithm should be able to track the position of the arterial walls over a sizeable length of the artery and for any vessel orientation and morphology. Table 1: A selection of specific solutions reported to date applicable
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