Invertible orientation scores of 3D images

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

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

5 Citations (Scopus)
1 Downloads (Pure)


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)
Original languageEnglish
Title of host publicationScale Space and Variational Methods in Computer Vision (5th International Conference, SSVM 2015, Lège-Cap Ferret, France, May 31-June 4, 2015, Proceedings)
EditorsJ.-F. Aujol, M. Nikolova, N. Papadakis
ISBN (Print)978-3-319-18460-9
Publication statusPublished - 2015

Publication series

NameLecture Notes in Computer Science
ISSN (Print)0302-9743


Dive into the research topics of 'Invertible orientation scores of 3D images'. Together they form a unique fingerprint.

Cite this