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

Research output: Contribution to journalConference paper

Eliza Orasanu, Pierre Louis Bazin, Andrew Melbourne, Marco Lorenzi, Herve Lombaert, Nicola J. Robertson, Giles Kendall, Nikolaus Weiskopf, Neil Marlow, Sebastien Ourselin

Original languageEnglish
Pages (from-to)255-263
Number of pages9
JournalLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9900 LNCS
Publication statusPublished - 2 Oct 2016
Event1st International Workshop on Simulation and Synthesis in Medical Imaging, SASHIMI 2016 held in conjunction with 19th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2016 - Athens, Greece
Duration: 21 Oct 201621 Oct 2016



King's Authors


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.

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