Methods for inverting dense displacement fields: Evaluation in brain image registration

Research output: Chapter in Book/Report/Conference proceedingConference paper

22 Citations (Scopus)

Abstract

In medical image analysis there is frequently a need to invert dense displacement fields which map one image space to another. In this paper we describe inversion techniques and determine their accuracy in the context of 18 inter-subject brain image registrations. Scattered data interpolation (SDI) is used to initialise locally and globally consistent iterative techniques. The inverse-consistency error, E-IC is computed over the whole image and over 10 specific brain regions. SDI produced good results with mean (max) E-IC similar to 0.02mm (2.0mm). Both iterative method produced mean errors of similar to 0.005mm but the globally consistent method resulted in a smaller maximum error (1.9mm compared with 1.4mm). The largest errors were in the cerebral cortex with large outlier errors in the ventricles. Simple iterative techniques are, on this evidence, able to produce reasonable estimates of inverse displacement fields provided there is good initialisation.

Original languageEnglish
Title of host publicationMedical Image Computing and Computer-Assisted Intervention - MICCAI 2007, Pt 1, Proceedings
EditorsN Ayache, S Ourselin, A Maeder
Place of PublicationBERLIN
PublisherSpringer
Pages900-907
Number of pages8
Volume4791 LNCS
EditionPART 1
ISBN (Print)978-3-540-75756-6
Publication statusPublished - 2007
Event10th International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI 2007) - Brisbane
Duration: 29 Oct 20072 Nov 2007

Conference

Conference10th International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI 2007)
CityBrisbane
Period29/10/20072/11/2007

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