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Statistical Analysis of Functions on Surfaces, with an application to Medical Imaging

Presented by: 
Eardi Lila
Thursday 22nd March 2018 - 16:00 to 17:00
INI Seminar Room 1
Co-author: John Aston (University of Cambridge)

In Functional Data Analysis, data are commonly assumed to be smooth functions on a fixed interval of the real line. In this work, we introduce a comprehensive framework for the analysis of functional data, whose domain is a two-dimensional manifold and the domain itself is subject to variability from sample to sample. We formulate a statistical model for such data, that we call Functions on Surfaces, which enables a joint representation of the geometric and functional aspects, and propose an associated estimation framework. We apply the proposed framework to the analysis of neuroimaging data of cortical thickness, acquired from the brains of different subjects, and thus lying on domains with different geometries.
University of Cambridge Research Councils UK
    Clay Mathematics Institute London Mathematical Society NM Rothschild and Sons