Figure 9.3 shows the different image processing techniques used for segmentation of the plaque volumes. Yuan et al.  used a quantitative vascular analysis tool (QVAT). The QVAT is a semiautomatic, custom-designed program that tracks boundaries and computes areas. Gill et al.  used a mesh-based model that obtained boundaries in three steps. It involved a deformable balloon model of a triangular mesh which is first placed inside a region manually; it is then inflated by inflation forces and then refined by image-based forces. Kim et al.  used an edge-detection tool. Wilhjelm et al.  used a manual segmentation procedure. Yang et al.  used a border-based model, which had three steps. It involved first approximating the outlines of the vessels, followed by the detection of borders, and then the user correction of the borders.
Yang et al.  segmented the wall and plaque in in vitro vascular MR images using a combination of automated and manual processes. A computerized method used edge strength, edge direction, border smoothness, and shape guidance to get the outer wall, lumen, internal elastic lamina, and external elastic lamina boundaries; these boundaries were then modified using the user selection seed points. Boundaries of the outer wall and the lumen were determined by fitting splines to seed points. The internal elastic lamina boundary was obtained
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