Tissue segmentation in MRI as an informative indicator of disease activity in the brain

Simon Vinitski, Carlos Gonzalez, Claudio Burnett, Feroze Mohamed, Tad Iwanaga, Hector Ortega, Scott Faro

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

Abstract

The presented tissue segmentation technique is based on a multispectral analysis approach. The input data were derived from high resolution MR images. Usually, only two inputs, proton density (PD) and T2-weighted images, are utilized to calculate the 2D feature map. In our method, we introduced a third input, T1-weighted MR image, for segmentation based on 3D feature map. k-Nearest Neighborhood segmentation algorithm was utilized. Tissue segmentation was performed in phantoms, normal humans and those with brain tumors and MS. Our technique utilizing all three inputs provided the best segmentation (p<0.001). The inclusion of T1 based images into segmentation produced dramatic improvement in tissue identification. Using our method, we identified the two distinctly different classes of tissue within the same MS plaque. We presume that these tissues represent the different stages involved in the evolution of the MS lesions. Further, our methodology for measuring MS lesion burden was also used to obtain its regional distribution as well as to follow its changes over time. The segmentation results were in full accord with neuropsychological findings.

Original languageEnglish (US)
Title of host publicationImage Analysis and Processing - 8th International Conference, ICIAP 1995, Proceedings
EditorsCarlo Braccini, Leila DeFloriani, Gianni Vernazza
PublisherSpringer Verlag
Pages265-270
Number of pages6
ISBN (Print)3540602984, 9783540602989
DOIs
StatePublished - Jan 1 1995
Event8th International Conference on Image Analysis and Processing, ICIAP 1995 - San Remo, Italy
Duration: Sep 13 1995Sep 15 1995

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume974
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other8th International Conference on Image Analysis and Processing, ICIAP 1995
CountryItaly
CitySan Remo
Period9/13/959/15/95

Keywords

  • 3D feature map
  • Brain tumor
  • MRI
  • Multiple sclerosis
  • Tissue segmentation

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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