Non-rigid spatio-temporal alignment of 4D cardiac MR images

Dimitrios Perperidis, Anil Rao, Raad Mohiaddin, Daniel Rueckert

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

6 Scopus citations

Abstract

In this paper we further develop of a 4D registration algorithm for the spatio-temporal alignment of cardiac MR image sequences. The registration algorithm has the ability not only to correct any spatial misalignment between the image sequences but also any temporal misalignment which maybe the result of differences in the cardiac cycle between subjects and differences in the temporal acquisition parameters. The algorithm uses a 4D transformation model which is separated into a spatial and a temporal component. In this approach the spatial part of transformation is composed by a global affine transformation and a local free-form deformation based on B-splines. The spatial part not only corrects spatial differences of a global nature but also local spatial differences of the cardiac shape. The temporal component uses an affine transformation which corrects the temporal misalignment caused by differences in the initial acquisition offset and length of the two cardiac cycles. The method was applied to a number of cardiac MR image sequences from healthy volunteers. The registration was qualitatively evaluated by visual inspection and quantitatively by measuring overlap of anatomical regions between the sequences. The results are compared with the results of the previously developed 4D registration method. A significant improvement in the alignment of the images is achieved by the use of free-form deformation models.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
EditorsJames C. Gee, J. B. Antoine Maintz, Michael W. Vannier
PublisherSpringer Verlag
Pages191-200
Number of pages10
ISBN (Print)3540203435, 9783540203438
DOIs
StatePublished - 2003
Externally publishedYes

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume2717
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

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