Locally orderless registration for diffusion weighted images

3 Citations (Scopus)

Abstract

Registration of Diffusion Weighted Images (DWI) is challenging as the data, in contrast to scalar-valued images, is a composition of both directional and intensity information. The DWI signal is known to be influenced by noise and a wide range of artifacts. Therefore, it is attractive to use similarity measures with invariance properties, such as Mutual Information. However, density estimation from DWI is complicated by directional information. We address this problem by extending Locally Orderless Registration (LOR), a density estimation framework for image similarity, to include directional information. We construct a spatio-directional scale-space formulation of marginal and joint density distributions between two DWI, that takes the projective nature of the directional information into account. This accounts for orientation and magnitude and enables us to use a wide range of similarity measures from the LOR framework. Using Mutual Information, we examine the properties of the scale-space induced by the choice of kernels and illustrate the approach by affine registration.

Original languageEnglish
Title of host publicationMedical Image Computing and Computer-Assisted Intervention -- MICCAI 2015 : 18th international conference, Munich, Germany, October 5-9, 2015, Proceedings, Part II
EditorsNassir Navab, Joachim Hornegger, William M. Wells, Alejandro F. Frangi
Number of pages8
PublisherSpringer
Publication date2015
Pages305-312
ISBN (Print)978-3-319-24570-6
ISBN (Electronic)978-3-319-24571-3
DOIs
Publication statusPublished - 2015
EventInternational Conference on Medical Image Computing and Computer Assisted Intervention 2015 - Munich, Germany
Duration: 5 Oct 20159 Oct 2015
Conference number: 18

Conference

ConferenceInternational Conference on Medical Image Computing and Computer Assisted Intervention 2015
Number18
Country/TerritoryGermany
CityMunich
Period05/10/201509/10/2015
SeriesLecture notes in computer science
Volume9350
ISSN0302-9743

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