@inbook{5888647ae5e54b9cadf3eb3d98409f09,
title = "Non-rigid spatio-temporal alignment of 4D cardiac MR images",
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.",
author = "Dimitrios Perperidis and Anil Rao and Raad Mohiaddin and Daniel Rueckert",
year = "2003",
doi = "10.1007/978-3-540-39701-4_20",
language = "English",
isbn = "3540203435",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "191--200",
editor = "Gee, {James C.} and Maintz, {J. B. Antoine} and Vannier, {Michael W.}",
booktitle = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
}