Segmentation-free measurement of cortical thickness from MRI

Iman Aganj, Guillermo Sapiro, Neelroop Parikshak, Sarah K. Madsen, Paul M. Thompson

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

Estimating the thickness of cerebral cortex is a key step in many MR brain imaging studies, revealing valuable information on development or disease progression. In this work we present a new approach to measure the cortical thickness, based on minimizing line integrals over the probability map of the gray matter in the MRI volume. Previous methods often perform a binary-valued segmentation of the gray matter before measuring the thickness. Because of image noise and partial voluming, such a hard classification ignores the underlying class probabilities assigned to each voxel, discarding potentially useful information. We describe our proposed method and demonstrate its performance on both artificial volumes and real 3D brain MRI data from subjects with Alzheimer's disease and healthy individuals.

Original languageEnglish
Title of host publication2008 5th IEEE International Symposium on Biomedical Imaging
Subtitle of host publicationFrom Nano to Macro, Proceedings, ISBI
Pages1625-1628
Number of pages4
DOIs
StatePublished - 2008
Externally publishedYes
Event2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI - Paris, France
Duration: 14 May 200817 May 2008

Publication series

Name2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, Proceedings, ISBI

Conference

Conference2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI
Country/TerritoryFrance
CityParis
Period14/05/0817/05/08

Keywords

  • Cortical thickness measurement
  • Gray matter density
  • Magnetic resonance imaging
  • Soft classification

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