Speaker - X. Pennec (Senior Research Scientist, INRIA, France)

www-sop.inria.fr/members/Xavier.Pennec/

Title - Riemannian and Affine Structures for Statistics on Shapes and Deformations in Computational Anatomy.

Abstract - Computational anatomy is an emerging discipline at the interface of geometry, statistics, image analysis and medicine that aims at analyzing and modeling the biological variability of the organs shapes and their dynamics at the population level. The goal is to model the mean anatomy, its normal variation, its motion / evolution and to discover morphological differences between normal and pathological groups. Since shapes and deformations live in non-linear spaces, this requires a consistent statistical framework on manifolds and Lie groups. The geometric structure considered so far was that of Riemannian geometry, for instance with (right) invariant metrics on groups of transformation. In parallel, efficient image processing methods based on diffeomorphisms parameterized by stationary velocity fields (SVF) have been developed with a great success from the practical point of view but with less theoretical support. This talk will detail and partially extend the Riemannian framework for geometric statistics to affine connection spaces and more particularly to Lie groups provided with the canonical Cartan-Schouten connection (a non-metric connection). In finite dimension, this provides strong theoretical bases for the use of one-parameter subgroups. The generalization to infinite dimensions would grounds the SVF-framework. From the practical point of view, we show that it leads to quite simple and very efficient models of atrophy of the brain in Alzheimer's disease.

Short CV - Dr Pennec is a Senior research Scientist (Directeur de recherche) at the ASCLEPIOS team at INRIA Sophia-Antipolis (France). He holds an Engineering degree from the French Ecole Polytechnique in 1992 and a PhD degree in Computer Science from the same institution in 1996. He was a post-doctoral associate at MIT AI Lab (Mass. USA) in 1997, before joining INRIA in 1998. His main research axes are about statistics on geometric data, in particular for medical image analysis, and biomedical image registration. Over the last years, these fields have gradually converged towards computational anatomy, which aims at statistically describing the normal and abnormal shape and anatomy of organs across populations. X. Pennec co-authored more than 60 Journal papers, including in J. of Human Evolution, Neuroimage, Magnetic Resonance in Medicine, IJCV, and 130 peer-reviewed and archived international conference articles in these fields. 14 of these papers received an award, including 3 MICCAI Young investigator awards and the Elsevier MedIA-MICCAI best paper award in 2006. He gave 25 invited keynotes and distinguished lectures, including at Field Institute (Toronto, CA), the Royal Statistical Society (London, UK), MFO (Oberwolfach, DE), Hausdorff Institute (Bonn, DE), etc. X. pennec co-advised 16 PhD students in the past, 4 of which were awarded a distinguished dissertation award. He is founder and chair of the Mathematical Foundations of Computational Anatomy workshop series, and serving as associate editor for the Medical Image Analysis journal, the International Journal of Computer Vision, the Journal of Mathematical Imaging and Vision, and the SIAM Journal on Imaging Sciences. He was a member of the board of the Medical Image Computing and Computer Assisted Interventions (MICCAI) scientific society from 2011 to 2015.