Automated Detection of the Arterial Inner Walls of the Common Carotid Artery Based on Dynamic B-Mode Signals

Abstract

In this paper we propose a novel scheme able to automatically detect the intima and adventitia of both near and far walls of the common carotid artery in dynamic B-mode RF (radiofrequency) image sequences, with and without plaques. Via this automated system the lumen diameter changes along the heart cycle can be detected. Three image sequences have been tested and all results are compared to manual tracings made by two professional experts. The average errors for near and far wall detection are 0.058 mm and 0.067 mm, respectively. This system is able to analyze arterial plaques dynamically which is impossible to do manually due to the tremendous human workload involved.

Exact solution to median surface problem using 3D graph search and application to parameter space exploration

“…In our tests the involved dynamic programming approach from [38] has two parameters only. In the case of more parameters the number of sampled parameter settings certainly increases.…”

“…Even if it is not our intention to directly apply the graph search algorithm for 3D segmentation, we also tested this option by applying the same preprocessing as in the baseline segmentation method used in this work [38]. For video 1, see Table 2, the performance measure (average L 1 deviation in z) is 0.57 (near wall) and 0.53 (far wall), which is comparable with our ensemble solution (0.63 and 0.57, respectively).…”

“…The dynamic programming approach from [38] was applied to detect the two contours. This algorithm has two parameters.…”

“…This insufficiency can be alleviated by using clues from other mutually related boundaries or surfaces. Indeed, codetection of multiple coupled surfaces frequently yields superior performance compared to the common single-surface detection approaches [31,25,[38][39][40]. Thus, it is essential to extend the single terrain-like surface median problem to the case of multiple coupled surfaces.…”

Automatic detection of the carotid artery boundary on cross-sectional MR image sequences using a circle model guided dynamic programming

“…It is applicable in image processing to solve optimal problems such as finding a minimum (or maximum) with some given constraints[16,17]. However, the limitation of using this technique in images is that it cannot solve the closed form contour.…”