Abstract
The traditional Hessian-related vessel filters often suffer from the problem of handling non-cylindrical objects. To remedy the shortcoming, we present a shape-tuned strain energy density function to measure vessel likelihood in 3D images. Based on the tensor invariants and stress-strain principle in mechanics, a new shape discriminating and vessel strength measure function is formulated. The synthetical and clinical data experiments verify the performance of our method in enhancing complex vascular structures including branches, bifurcations, and feature details. © 2010 Springer-Verlag.
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CITATION STYLE
Xiao, C., Staring, M., Shamonin, D., Reiber, J. H. C., Stolk, J., & Stoel, B. C. (2010). A strain energy filter for 3D vessel enhancement. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6363 LNCS, pp. 367–374). https://doi.org/10.1007/978-3-642-15711-0_46
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