Vessel tracking by connecting the dots

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We propose an algorithm for tracking blood vessel segments in Computed Tomographic (CT) images.
Our procedure first finds core points that tend to concentrate along the centerlines of vessels. Intuitively,
the core points are centers of intensity plateaus in two-dimensional slices through the input image. The
starting and the end point of the desired vessel (S and E) are also considered core points. The weighted
core graph is built by connecting nearby core points with edges. Edge weights are designed so that edges
of large weights are unlikely to follow a vessel segment. We compute the shortest path connecting S and
E in the core graph. The output is the result of applying shortcutting operations to this path.

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Categories: Blurring filters, Classification, Data Representation, Derivatives and Integrals, Edge Detection, Feature extraction, Filtering, Image, Level sets, Mathematical Morphology, Mathematics, Missing and Noisy Features, Neighborhood filters, Path, Point distribution models, PointSet, Region growing, Resampling, Segmentation, Spatial Objects, Statistical shape models, Thresholding, Watersheds
Keywords: Computed Tomography, vessel, tracking, topology
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