Abstract
One of the most challenging problems in modern neuroimaging is detailed characterization of neurodegeneration. Quantifying spatial and longitudinal atrophy patterns is an important component of this process. These spatiotemporal signals will aid in discriminating between related diseases, such as frontotemporal dementia (FTD) and Alzheimer’s disease (AD), which manifest themselves in the same at-risk population. We evaluate a novel symmetric diffeomorphic image registration method for automatically providing detailed anatomical measurement over the aged and neurodegenerative brain. Our evaluation will compare gold standard, human segmentation with our method’s atlas-based segmentation of the cerebral cortex, cerebellum and the frontal lobe. The new method compares favorably to an open-source, previously evaluated implementation of Thirion’s Demons algorithm.
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Avants, B.B., Grossman, M., Gee, J.C. (2006). Symmetric Diffeomorphic Image Registration: Evaluating Automated Labeling of Elderly and Neurodegenerative Cortex and Frontal Lobe. In: Pluim, J.P.W., Likar, B., Gerritsen, F.A. (eds) Biomedical Image Registration. WBIR 2006. Lecture Notes in Computer Science, vol 4057. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11784012_7
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DOI: https://doi.org/10.1007/11784012_7
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