Abstract
The edge or shape preservation property of connected attribute filters is a desirable feature for biomedical imaging and makes them a suitable tool for problems in which accurate shape analysis is of importance. However, there are still comparatively few attributes for 3D filtering upon which to select features of interest besides, efficient and fast computation of attributes from volumetric data is still a daunting challenge. In particular, whereas a vast literature on 2D moment invariants exist, far fewer 3D moment invariants are available. In this study we introduce a new, radial-moment based roundness attribute in 3D, and provide a memory-efficient algorithm to compute it, even for very high moment orders. It satisfies similarity transformations of translation, rotation and scaling invariance and be generalised to higher order moments without performance degradation. We show the utility of the new attribute in the isolation of kidney stones and other structures in 3D CT and MRI images.
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Kiwanuka, F.N., Wilkinson, M.H.F. (2012). Radial Moment Invariants for Attribute Filtering in 3D. In: Köthe, U., Montanvert, A., Soille, P. (eds) Applications of Discrete Geometry and Mathematical Morphology. WADGMM 2010. Lecture Notes in Computer Science, vol 7346. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32313-3_5
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DOI: https://doi.org/10.1007/978-3-642-32313-3_5
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