Geodesic Tubes for Uncertainty Quantification in Diffusion MRI

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

Abstract

Based on diffusion tensor imaging (DTI), one can construct a Riemannian manifold in which the dual metric is proportional to the DTI tensor. Geodesic tractography then amounts to solving a coupled system of nonlinear differential equations, either as initial value problem (given seed location and initial direction) or as boundary value problem (given seed and target location). We propose to furnish the tractography framework with an uncertainty quantification paradigm that captures the behaviour of geodesics under small perturbations in (both types of) boundary conditions. For any given geodesic this yields a coupled system of linear differential equations, for which we derive an exact solution. This solution can be used to construct a geodesic tube, a volumetric region around the fiducial geodesic that captures the behaviour of perturbed geodesics in the vicinity of the original one.

Original languageEnglish
Title of host publicationInformation Processing in Medical Imaging - 27th International Conference, IPMI 2021, Proceedings
EditorsAasa Feragen, Stefan Sommer, Julia Schnabel, Mads Nielsen
PublisherSpringer Science and Business Media B.V.
Pages279-290
Number of pages12
ISBN (Print)9783030781903
DOIs
Publication statusPublished - 2021
Event27th International Conference on Information Processing in Medical Imaging, IPMI 2021 - Virtual, Online
Duration: 28 Jun 202130 Jun 2021

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12729 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference27th International Conference on Information Processing in Medical Imaging, IPMI 2021
CityVirtual, Online
Period28/06/2130/06/21

Bibliographical note

Funding Information:
This work is part of the research programme ?Diffusion MRI Tractography with Uncertainty Propagation for the Neurosurgical Workflow? with project number 16338, which is (partly) financed by the Netherlands Organisation for Scientific Research (NWO). The work of A. Fuster is part of the research program of the Foundation for Fundamental Research on Matter (FOM), which is financially supported by the Netherlands Organisation for Scientific Research (NWO). We would like to thank neurosurgeon Geert-Jan Rutten for sharing the two clinical datasets used in our experiments at the Elisabeth TweeSteden Hospital (ETZ) in Tilburg, The Netherlands, and for fruitful discussions.

Keywords

  • Diffusion tensor imaging
  • Geodesic deviation
  • Geodesic tractography
  • Riemannian geometry
  • Uncertainty quantification

Fingerprint

Dive into the research topics of 'Geodesic Tubes for Uncertainty Quantification in Diffusion MRI'. Together they form a unique fingerprint.

Cite this