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"A Strain Energy Filter for 3D Vessel Enhancement"
Changyan Xiao, Marius Staring, Denis P. Shamonin, Johan H.C. Reiber, Jan Stolk and Berend C. Stoel
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.
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Copyright © 2010 by the authors.
Published version © 2010 by Springer Lecture Notes in Computer Science.
Personal use of this material is permitted. However, permission to reprint or republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works, must be obtained from the copyright holder.
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Source code
The source code of the methods described in this paper can be found in the toolkit ITKTools, available at https://github.com/ITKTools/ITKTools. The specific tool is pxenhancement. |
BibTeX entry
| @inproceedings{Xiao:2010, |
| author |
= {Xiao, Changyan and Staring, Marius and Shamonin, Denis P. and Reiber, Johan H.C. and Stolk, Jan and Stoel, Berend C.}, |
| title |
= {A Strain Energy Filter for 3D Vessel Enhancement}, |
| booktitle |
= {Medical Image Computing and Computer-Assisted Intervention}, |
| editor |
= {T. Jiang, and etal,}, |
| address |
= {Beijing, China}, |
| series |
= {Lecture Notes in Computer Science}, |
| volume |
= {6363}, |
| pages |
= {367 - 374}, |
| year |
= {2010}, |
| } |
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