Riemannian Geometric Statistics in Medical Image Analysis

Xavier Pennec’s research interest is at the intersection of statistics, differential geometry, computer science and medicine. He is particularly interested in the mathematics involved in computational anatomy: geometric statistics involving statistical computing on Riemannian manifolds and other geometric structures . He has contributed mathematically grounded methods and algorithms for medical image registration, statistics on shapes, and their translation to clinical research applications. Stefan Sommer’s research focus is on modeling and statistics of non-linear data with application to shape spaces, functional data analysis, and image registration. This includes foundational and algorithmic aspects of statistics on manifold valued data, and computational modeling and statistical analysis of deformations occurring in computational anatomy. Tom Fletcher’s research focus is on solving problems in medical image analysis and computer vision through the combination of statistics and differential geometry

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