Minimally Interactive Knowledge-based Coronary Tracking in CTA using a Minimal Cost Path
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Please use this identifier to cite or link to this publication: http://hdl.handle.net/10380/1435
An algorithm for minimally interactive coronary artery tracking is presented. Tracking ability and accuracy results are demonstrated on 16 images CTA images.
First, a region of interest is automatically selected and a denoising filter applied. Then, for each voxel the probability of belonging to a coronary vessel is estimated from a feature space and a vesselness measure is used to obtain a cost function. The vessel starting point is obtained automatically, while the end point is provided by the user. Finally, the centerline is obtained as the minimal cost path between both points.

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Comment by Elnaz Ezzati yellow
hello
I'm Ms student and interested in CTA image processing. May I ask to send me the source code that extract centerline from coronary artery?


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Categories: Anisotropic blurring filters, Classification, Density Estimation, Feature extraction, Filtering, Images, IO, Iterative clustering, Mathematical Morphology, Non-parametric Techniques, Region growing, Segmentation, Thresholding, Unsupervised learning and clustering
Keywords: CTA coronary tracking, Minimal cost path, Non parametric density estimation, Image denoising
Toolkits: ITK, VTK
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