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Figure 8.12: An example of the MRF-based active contour framework. (a) The original image of T1W MR image on carotid artery lumen. (b) Edge map by Canny edge detector. (c) Segmentation result of QHCF algorithm with Trc = 10, p1 = 400, p2 = 1000, Tmin = 20. (d) Lumen contour based on the QHCF algorithm. (e) Six selected control points. (f) Fine-tuned contour by applying MPA.

Figure 8.12: An example of the MRF-based active contour framework. (a) The original image of T1W MR image on carotid artery lumen. (b) Edge map by Canny edge detector. (c) Segmentation result of QHCF algorithm with Trc = 10, p1 = 400, p2 = 1000, Tmin = 20. (d) Lumen contour based on the QHCF algorithm. (e) Six selected control points. (f) Fine-tuned contour by applying MPA.

segmentation and ACM models. In addition, it is also very flexible and can easily include prior knowledge from various applications. An example of blood vessel tracking and lumen segmentation in magnetic resonance image sequences is studied and the experimental results have demonstrated very satisfactory performance.

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Figure 8.13: MR images of a human carotid artery from proximal common (a) through the bifurcation that occurs between images (g) and (h) to the distal internal and external carotids (j). Tracked lumen boundaries are visualized as distinct lines separating the lumen from adjacent tissues. This series also illustrates the topology change tracking ability of the proposed framework from the single lumen of the common carotid to the two lumens of the bifurcation, internal, and external carotid arteries. The location of real bifurcation happens between image (g) and (h). The closed bright curves along lumen boundary are the tracked contours. These results also demonstrate the topology change handling ability of the proposed framework.

Figure 8.13: MR images of a human carotid artery from proximal common (a) through the bifurcation that occurs between images (g) and (h) to the distal internal and external carotids (j). Tracked lumen boundaries are visualized as distinct lines separating the lumen from adjacent tissues. This series also illustrates the topology change tracking ability of the proposed framework from the single lumen of the common carotid to the two lumens of the bifurcation, internal, and external carotid arteries. The location of real bifurcation happens between image (g) and (h). The closed bright curves along lumen boundary are the tracked contours. These results also demonstrate the topology change handling ability of the proposed framework.

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