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Longitudinal analysis of the preterm cortex using multi-modal spectral matching

Orasanu, E; Bazin, PL; Melbourne, A; Lorenzi, M; Lombaert, H; Robertson, NJ; Kendall, G; ... Ourselin, S; + view all (2016) Longitudinal analysis of the preterm cortex using multi-modal spectral matching. In: Ourselin, S and Joskowicz, J and Sabuncu, MR and Unal, G and Wells, W, (eds.) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2016. (pp. pp. 255-263). Springer International Publishing AG Green open access

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Abstract

Extremely preterm birth (less than 32 weeks completed gestation) overlaps with a period of rapid brain growth and development. Investigating longitudinal brain changes over the preterm period in these infants may allow the development of biomarkers for predicting neurological outcome. In this paper we investigate longitudinal changes in cortical thickness,cortical fractional anisotropy and cortical mean diffusivity in a groupwise space obtained using a novel multi-modal spectral matching technique. The novelty of this method consists in its ability to register surfaces with very little shape complexity,like in the case of the early developmental stages of preterm infants,by also taking into account their underlying biology. A multi-modal method also allows us to investigate interdependencies between the parameters. Such tools have great potential in investigating in depth the regions affected by preterm birth and how they relate to each other.

Type: Proceedings paper
Title: Longitudinal analysis of the preterm cortex using multi-modal spectral matching
Event: MICCAI 2016 - 19th International Conference on Medical Image Computing and Computer Assisted Intervention
Location: Athens, Greece
Dates: 17 October 2016 - 21 October 2016
ISBN-13: 9783319467191
Open access status: An open access version is available from UCL Discovery
DOI: 10.1007/978-3-319-46720-7_30
Publisher version: http://doi.org/10.1007/978-3-319-46720-7_30
Language: English
Additional information: Copyright © Springer International Publishing AG 2016. The final publication is available at Springer via http://doi.org/10.1007/978-3-319-46720-7_30.
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > UCL EGA Institute for Womens Health
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > UCL EGA Institute for Womens Health > Neonatology
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Med Phys and Biomedical Eng
URI: https://discovery.ucl.ac.uk/id/eprint/1531857
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