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Proceedings Paper

A homomorphic filtering framework for DT-MRI
Author(s): Carlos-Alberto Castaño-Moraga; Carl-Fredrik Westin; Juan Ruiz-Alzola
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Paper Abstract

In this paper we develop a new filtering framework for tensor signal processing using the theory of vector spaces. From this point of view, signals are regarded as elements of vector spaces and operators as mappings from the input space to the output space. Hence, it is possible to generalize the principle of superposition to any operator defined on the signal spaces. Systems that obey that generalization of the principle of superposition are referred to as homomorphic and they can be decomposed in a cascade of three homomorphic subsystems: the first one operates on the input signal space, the second one is a linear system in the usual sense and the third one operates on the output signal space. Thus, suitable input and output subsystems can be chosen to deal with input signals, which defines a whole family of homomorphic filters. To apply this idea for DT-MRI signals, which consist of positive semi-definite matrices, we identify input and output signal spaces as the set of those real symmetric positive semi-definite matrices. Our homomorphic filtering framework not only guarantees a positive-semidefinite output tensor field whatever linear filter is used to regularize the noisy input, but also reduces the swelling effect produced by a faster regularization of diffusivities rather than orientations, as demonstrate the encouraging results that have been obtained.

Paper Details

Date Published: 10 March 2006
PDF: 8 pages
Proc. SPIE 6144, Medical Imaging 2006: Image Processing, 61441A (10 March 2006); doi: 10.1117/12.652094
Show Author Affiliations
Carlos-Alberto Castaño-Moraga, Univ. of Las Palmas de Gran Canaria (Spain)
Carl-Fredrik Westin, Brigham and Women's Hosptial, Harvard Medical School (United States)
Juan Ruiz-Alzola, Univ. of Las Palmas de Gran Canaria (Spain)


Published in SPIE Proceedings Vol. 6144:
Medical Imaging 2006: Image Processing
Joseph M. Reinhardt; Josien P. W. Pluim, Editor(s)

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