Data used to train the algorithms were obtained from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database. The ADNI was launched in 2003 as a public-private partnership, led by Principal Investigator Michael W. Weiner, MD.The primary goal of ADNI has been to test whether serial magnetic resonance imaging (MRI), positron emission tomography (PET), other biological markers, and clinical and neuropsychological assessment can be combined to measure the progression of mild cognitive impairment (MCI) and early Alzheimer’s disease (AD).For up-to-date information, see www.adni-info.org
Related Scientific Publications
- Simulating Alzheimer’s disease progression with personalised digital brain models, I. Koval, A. Bône, M. Louis, S. Bottani, A. Marcoux, J. Samper-Gonzalez, N. Burgos, B. Charlier, A. Bertrand, S. Epelbaum, O. Colliot, S. Allassonnière, S. Durrleman , preprint
- Spatiotemporal propagation of the cortical atrophy during the course of Alzheimer’s Disease: Population and individual patterns, I. Koval, J.-B. Schiratti, A. Routier, M. Bacci, O. Colliot, S. Allassonnière, S. Durrleman, Frontiers in Neurology, section Neurodegeneration, 2018
- Learning distributions of shape trajectories from longitudinal datasets: a hierarchical model on a manifold of diffeomorphisms, A. Bône, O. Colliot, S. Durrleman, In Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2018)
- A Bayesian mixed-effects model to learn trajectories of changes from repeated manifold-valued observations, J.-B. Schiratti, S. Allassonnière, O. Colliot, S. Durrleman, Journal of Machine Learning Research, 18(133):1−33, 2017
Results have been obtained using the software Deformetrica (for hippocampus atrophy) and Leaspy (for other modalities, to be released soon).