Lohmann, Gabriele and von Cramon, D. Yves and Colchester, Alan C. F. (2005) Construction of an averaged representation of human cortical gyri using non-linear principal component analysis. In: Duncan, James S. and Gerig, Guido, eds. Medical Image Computing and Computer-Assisted Intervention – MICCAI 2005 8th International Conference. Lecture Notes in Computer Science . Springer, Berlin, Germany, pp. 749-756. ISBN 978-3-540-29326-2. E-ISBN 978-3-540-32095-1. (doi:10.1007/11566489_92) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:12190)
The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. | |
Official URL: http://dx.doi.org/10.1007/11566489_92 |
Abstract
Because of the complex shape of human cortical gyri and great variation between individuals, development of effective representation schemes which allow establishment of correspondence between individuals, extraction of average structure of a Population, and co-registration has proved very difficult. We introduce an approach which extracts line representations of gyri at different depths from high resolution MRI, labels main gyri semi-automatically, and extracts a template from a population using non-linear principal component analysis. The method has been tested on data from 96 healthy human volunteers. The model captures the most salient shape features of all major cortical gyri, and can be used for inter-subject registration, for investigating regionalized inter-subject variability, and for inter-hemispheric comparisons.
Item Type: | Book section |
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DOI/Identification number: | 10.1007/11566489_92 |
Subjects: | R Medicine > R Medicine (General) |
Divisions: | Divisions > Division for the Study of Law, Society and Social Justice > School of Social Policy, Sociology and Social Research |
Depositing User: | M.P. Stone |
Date Deposited: | 08 Aug 2009 19:27 UTC |
Last Modified: | 05 Nov 2024 09:45 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/12190 (The current URI for this page, for reference purposes) |
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