Numerical schemes for linear and non-linear enhancement of DW-MRI

E.J. Creusen, R. Duits, T.C.J. Dela Haije

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

10 Citations (Scopus)

Abstract

We consider left-invariant di??usion processes on DTI data by embedding the data into the space R3 o S2 of 3D positions and orientations. We then define and solve the diffusion equation in a moving frame of reference defined using left-invariant derivatives. The diffusion process is made adaptive to the data in order to do Perona-Malik-like edge preserving smoothing, which is necessary to handle fiber structures near regions of large isotropic diffusion such as the ventricles of the brain. The corresponding partial differential systems are solved using finite difference stencils. We include experiments both on synthetic data and on DTI-images of the brain.
Original languageEnglish
Title of host publicationScale Space and Variational Methods in Computer Vision (Third International Conference, SSVM 2011, Ein-Gedi, Israel, May 29-June 2, 2011. Revised Selected Papers)
EditorsA.M. Bruckstein, B.M. Haar Romeny, ter, A.M. Bronstein, M.M. Bronstein
Place of PublicationBerlin
PublisherSpringer
Pages14-25
ISBN (Print)978-3-642-24784-2
DOIs
Publication statusPublished - 2012

Publication series

NameLecture Notes in Computer Science
Volume6667
ISSN (Print)0302-9743

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