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Grey matter sublayer thickness estimation in the mouse cerebellum

Ma, D; Cardoso, MJ; Zuluaga, MA; Modat, M; Powell, N; Wiseman, F; Tybulewicz, V; ... Ourselin, S; + view all (2015) Grey matter sublayer thickness estimation in the mouse cerebellum. In: Navab, N and Hornegger, J and Wells, WM and Frangi, AF, (eds.) Proceedings of 18th International Conference in Medical Image Computing and Computer-Assisted Intervention – MICCAI 2015. (pp. pp. 644-651). Springer International Publishing Switzerland: Munich, Germany. Green open access

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Abstract

The cerebellar grey matter morphology is an important feature to study neurodegenerative diseases such as Alzheimer’s disease or Down’s syndrome. Its volume or thickness is commonly used as a surrogate imaging biomarker for such diseases. Most studies about grey matter thickness estimation focused on the cortex, and little attention has been drawn on the morphology of the cerebellum. Using ex vivo highresolution MRI, it is now possible to visualise the different cell layers in the mouse cerebellum. In this work, we introduce a framework to extract the Purkinje layer within the grey matter, enabling the estimation of the thickness of the cerebellar grey matter, the granular layer and molecular layer from gadolinium-enhanced ex vivo mouse brain MRI. Application to mouse model of Down’s syndrome found reduced cortical and layer thicknesses in the transchromosomic group.

Type: Proceedings paper
Title: Grey matter sublayer thickness estimation in the mouse cerebellum
Event: 18th International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI)
Location: Munich, GERMANY
Dates: 05 October 2015 - 09 October 2015
ISBN-13: 9783319245737
Open access status: An open access version is available from UCL Discovery
DOI: 10.1007/978-3-319-24574-4_77
Publisher version: http://dx.doi.org/10.1007/978-3-319-24574-4_77
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Science & technology, technology, life sciences & biomedicine, computer science, artificial intelligence, computer science, interdisciplinary applications, computer science, theory & methods, radiology, nuclear medicine & medical imaging, computer science, down-syndrome, phenotypes.
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 Brain Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology > Department of Neuromuscular Diseases
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology > UK Dementia Research Institute
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/1469301
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