Population analysis of the cingulum bundle using the tubular surface model for schizophrenia detection

Vandana Mohan, Ganesh Sundaramoorthi, Marek Kubicki, Douglas Terry, Allen Tannenbaum

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

1 Scopus citations

Abstract

We propose a novel framework for population analysis of DW-MRI data using the Tubular Surface Model. We focus on the Cingulum Bundle (CB)-a major tract for the Limbic System and the main connection of the Cingulate Gyrus, which has been associated with several aspects of Schizophrenia symptomatology. The Tubular Surface Model represents a tubular surface as a center-line with an associated radius function. It provides a natural way to sample statistics along the length of the fiber bundle and reduces the registration of fiber bundle surfaces to that of 4D curves. We apply our framework to a population of 20 subjects (10 normal, 10 schizophrenic) and obtain excellent results with neural network based classification (90% sensitivity, 95% specificity) as well as unsupervised clustering (k-means). Further, we apply statistical analysis to the feature data and characterize the discrimination ability of local regions of the CB, as a step towards localizing CB regions most relevant to Schizophrenia.

Original languageEnglish (US)
Title of host publicationMedical Imaging 2010
Subtitle of host publicationComputer-Aided Diagnosis
EditorsRonald M. Summers, Nico Karssemeijer
PublisherSPIE
ISBN (Electronic)9780819480255
DOIs
StatePublished - Jan 1 2010
EventMedical Imaging 2010: Computer-Aided Diagnosis - San Diego, United States
Duration: Feb 16 2010Feb 18 2010

Publication series

NameProgress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume7624
ISSN (Print)1605-7422

Other

OtherMedical Imaging 2010: Computer-Aided Diagnosis
CountryUnited States
CitySan Diego
Period02/16/1002/18/10

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Atomic and Molecular Physics, and Optics
  • Biomaterials
  • Radiology Nuclear Medicine and imaging

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