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Erschienen in:
2015 | OriginalPaper | Buchkapitel
Grey Matter Sublayer Thickness Estimation in the Mouse Cerebellum
verfasst von : Da Ma, Manuel J. Cardoso, Maria A. Zuluaga, Marc Modat, Nick Powell, Frances Wiseman, Victor Tybulewicz, Elizabeth Fisher, Mark F. Lythgoe, Sébastien Ourselin
Erschienen in: Medical Image Computing and Computer-Assisted Intervention – MICCAI 2015
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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
high-resolution 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.