Invertible orientation scores of 3D images

M.H.J. Janssen, R. Duits, M. Breeuwer

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureConferentiebijdrageAcademicpeer review

3 Citaten (Scopus)
1 Downloads (Pure)

Samenvatting

The enhancement and detection of elongated structures in noisy image data is relevant for many biomedical applications. To handle complex crossing structures in 2D images, 2D orientation scores U:R2×S1¿R were introduced, which already showed their use in a variety of applications. Here we extend this work to 3D orientation scores U:R3×S2¿R . First, we construct the orientation score from a given dataset, which is achieved by an invertible coherent state type of transform. For this transformation we introduce 3D versions of the 2D cake-wavelets, which are complex wavelets that can simultaneously detect oriented structures and oriented edges. For efficient implementation of the different steps in the wavelet creation we use a spherical harmonic transform. Finally, we show some first results of practical applications of 3D orientation scores. Keywords: Orientation scores; Reproducing kernel spaces; 3D wavelet design; Scale spaces on SE(3); Coherence enhancing Diffusion on SE(3)
Originele taal-2Engels
TitelScale Space and Variational Methods in Computer Vision (5th International Conference, SSVM 2015, Lège-Cap Ferret, France, May 31-June 4, 2015, Proceedings)
RedacteurenJ.-F. Aujol, M. Nikolova, N. Papadakis
UitgeverijSpringer
Pagina's563-575
ISBN van geprinte versie978-3-319-18460-9
DOI's
StatusGepubliceerd - 2015

Publicatie series

NaamLecture Notes in Computer Science
Volume9087
ISSN van geprinte versie0302-9743

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  • Citeer dit

    Janssen, M. H. J., Duits, R., & Breeuwer, M. (2015). Invertible orientation scores of 3D images. In J-F. Aujol, M. Nikolova, & N. Papadakis (editors), Scale Space and Variational Methods in Computer Vision (5th International Conference, SSVM 2015, Lège-Cap Ferret, France, May 31-June 4, 2015, Proceedings) (blz. 563-575). (Lecture Notes in Computer Science; Vol. 9087). Springer. https://doi.org/10.1007/978-3-319-18461-6_45