Abstract
The prevalent model for second order variation in 3-D volumes is an ellipsoid spanned by the magnitudes of the Hessian eigenvalues. Here, we describe this variation as a vector in an orthogonal shape space spanned by spherical harmonic basis functions. From this newsh ape-space, a truly rotation- and shape-invariant signal energy is defined, consistent orientation information is extracted and shape sensitive quantities are employed. The advantage of these quantities is demonstrated in detection of stenosis in Magnetic Resonance Angiography( MRA) volume. The news hape space is expected to improve both the theoretical understanding and the implementation of Hessian based analysis in other applications as well.
Acknowledgment
We are indebted to Dr. A. Frangi for access to the CE MRA data sets. We gratefully acknowledge the financial support from the Swedish Foundation for Strategic Research through the VISIT program.
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Lin, Q., Danielsson, PE. (2001). Stenosis Detection Using a New Shape Space for Second Order 3D-Variations. In: Insana, M.F., Leahy, R.M. (eds) Information Processing in Medical Imaging. IPMI 2001. Lecture Notes in Computer Science, vol 2082. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45729-1_39
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DOI: https://doi.org/10.1007/3-540-45729-1_39
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