Abstract
In this paper we describe a rotation-invariant attribute filter based on estimating the sphericity or roundness of objects by efficiently computing surface area and volume of connected components. The method is based on an efficient algorithm to compute all iso-surfaces of all nodes in a Max-Tree. With similar properties to moment-based attributes like sparseness, non-compactness, and elongation, our sphericity attribute can supplement these in finding blood-vessels in time-of-flight MR angiograms. We compare the method to a discrete surface area method based on adjacency, which has been used for urinary stone detection. Though the latter is faster, it is less accurate, and lacks rotation invariance.
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Kiwanuka, F.N., Ouzounis, G.K., Wilkinson, M.H.F. (2009). Surface-Area-Based Attribute Filtering in 3D. In: Wilkinson, M.H.F., Roerdink, J.B.T.M. (eds) Mathematical Morphology and Its Application to Signal and Image Processing. ISMM 2009. Lecture Notes in Computer Science, vol 5720. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03613-2_7
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DOI: https://doi.org/10.1007/978-3-642-03613-2_7
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