Detecting outlying subjects in high-dimensional neuroimaging datasets with regularized minimum covariance determinant

Virgile Fritsch, Gael Varoquaux, Benjamin Thyreau, Jean Baptiste Poline, Bertrand Thirion

Research output: Chapter in Book/Report/Conference proceedingConference contribution

10 Citations (Scopus)

Abstract

Medical imaging datasets used in clinical studies or basic research often comprise highly variable multi-subject data. Statistically-controlled inclusion of a subject in a group study, i.e. deciding whether its images should be considered as samples from a given population or whether they should be rejected as outlier data, is a challenging issue. While the informal approaches often used do not provide any statistical assessment that a given dataset is indeed an outlier, traditional statistical procedures are not well-suited to the noisy, high-dimensional, settings encountered in medical imaging, e.g. with functional brain images. In this work, we modify the classical Minimum Covariance Determinant approach by adding a regularization term, that ensures that the estimation is well-posed in high-dimensional settings and in the presence of many outliers. We show on simulated and real data that outliers can be detected satisfactorily, even in situations where the number of dimensions of the data exceeds the number of observations.

Original languageEnglish
Title of host publicationMedical Image Computing and Computer-Assisted Intervention, MICCAI 2011 - 14th International Conference, Proceedings
PublisherSpringer Verlag
Pages264-271
Number of pages8
EditionPART 3
ISBN (Print)9783642236259
DOIs
Publication statusPublished - 2011
Event14th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2011 - Toronto, ON, Canada
Duration: 2011 Sep 182011 Sep 22

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 3
Volume6893 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference14th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2011
CountryCanada
CityToronto, ON
Period11/9/1811/9/22

Keywords

  • Minimum Covariance Determinant
  • Outlier detection
  • fMRI
  • neuroimaging
  • regularization
  • robust estimation

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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