Riemannian Geometric Statistics in Medical Image Analysis

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Bias on estimation in quotient space and correction methods

Applications to statistics on organ shapes

Nina Miolane^a,b; Loic Devilliers^a; Xavier Pennec^a    aUniversité Côte d'Azur and Inria, Epione team, Sophia Antipolis, France^bStanford University, Department of Statistics, Stanford, CA, United States

Abstract

Riemannian geometry and the theory of quotient spaces facilitate the analysis of medical imaging algorithms dealing with organ shapes. These algorithms often start with the computation of a template organ shape that serves as a reference for normalizing the measurements of each individual data into a common space. The template represents the organ's “prototype” for further analysis. The template is modeled as a parameter of a generative ...