You have just received an ERC grant, how do you intend to use it? We call them "longitudinal data". Durrleman, A Bayesian mixed-effects model to learn trajectories of changes from repeated manifold-valued observations, Journal of Machine Learning Research, 18 Durrleman, Parallel transport in shape analysis: Colliot, Amyloidosis and neurodegeneration result in distinct structural connectivity patterns in mild cognitive impairment, Neurobiology of Aging, Vol 55, pp, doi: This has enabled me to bring to light earlier amygdala growth in autistic children.
During my career, I have studied databases of longitudinal cerebral images: We are going to have to invent new statistical tools that will automatically match similar events such as the appearance of a lesion in a certain area of the brain, for example that happen at different times for each patient, thereby replacing the disease in the life and history of the patient.
There are numerous applications for these digital models: This data provides a mass of information that is essential in order to understand the brain and neurological diseases.
Within this context, I have developed a methodology capable of establishing a scenario for the average growth of the amygdala a deep structure in the brainin children.
Population and individual patterns,Frontiers in Neurology, section Neurodegeneration,to appear H. Firstly, I would like to expand my team by recruiting at least three PhD students and one or two post-docs.
Using this data, my aim is to reveal constants in the brain development or ageing. In order to establish average scenarios from observations of individuals repeated over time, we need to compare what is comparable.
These models are built thanks to computer programs that average the information contained in the medical images of a group of subjects or patients. Gerig, A framework for longitudinal data analysis via shape regression, Proc. Application to fossil data?
Ayache, Toward a comprehensive framework for the spatiotemporal statistical analysis of longitudinal shape data, International Journal of Computer Vision,1: What does your research consist of?
My first experience with Inria was back when I did my thesis, following a Masters in applied mathematics.
Braga, How to build an average model when samples are variably incomplete? Durrleman, Prediction of amyloidosis from neuropsychological and MRI data for cost effective inclusion of pre-symptomatic subjects in clinical trials, In Proc.Curriculum Vitae Guido Gerig Update: February 4, Address Guido Gerig tation thesis "Segmentierung zur symbolischen Beschreibung von Grauwert- Stanley Durrleman Ph.D.INRIA Sophia Antipolis,FR Hui Sun Ph.D.
MarchU-Penn Joshua Cates Ph.D.
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Specialist in neuroimaging data, Stanley Durrleman is a researcher with Aramis, a joint team between Inria-Paris and the French Brain and Spine Institute (ICM). His work on digital models of the brain development and ageing has enabled him to win an ERC grant, awarded by the European Commission.
T H E S E pour obtenir le grade de Docteur ès Sciences Mention: AUTOMATIQUE, TRAITEMENT DU SIGNAL ET DES IMAGES presentée et soutenue par Stanley DURRLEMAN Statistical models of currents for measuring the variability of anatomical curves, surfaces and their evolution.
Spatio-Temporal Shape Modeling and Analysis Guido Gerig James Fishbaugh, Marcel Prastawa Martin Styner, Stephen Pizer, UNC Stanley Durrleman, Xavier Pennec, INRIA. Content • Motivation Longitudinal Modeling • Overview Correspondence • Currents: Correspondence-free Modeling Durrleman, PhD thesis, Shape.
Thesis S. Durrleman Geometrical Approaches in Statistical Learning for the Construction of Digital Models of the Human Brain, University Pierre and Marie Curie, Junepdf.Download