Automatic statistical identification of neuroanatomical abnormalities between different populations

Alexandre Guimond, Svetlana Egorova, Ronald J. Killiany, Marilyn S. Albert, Charles R.G. Guttmann

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

Abstract

We present a completely automatic method to identify abnormal anatomical configurations of the brain resulting from various pathologies. The statistical framework developed here is applied to identify regions that significant differ from normal anatomy in two groups of patients, namely subjects who subsequently converted to Alzheimer’s Disease (AD) and subjects with mild AD. The regions identified are consistent with post-mortem pathological findings in AD.

Original languageEnglish (US)
Title of host publicationMedical Image Computing and Computer-Assisted Intervention - MICCAI 2002 - 5th International Conference, Proceedings
EditorsTakeyoshi Dohi, Ron Kikinis
PublisherSpringer Verlag
Pages785-792
Number of pages8
ISBN (Print)9783540457862
DOIs
StatePublished - 2002
Externally publishedYes
Event5th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2002 - Tokyo, Japan
Duration: Sep 25 2002Sep 28 2002

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume2488
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other5th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2002
CountryJapan
CityTokyo
Period9/25/029/28/02

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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