A new rapid landmark-based regional MRI segmentation method of the brain

ALW Bokde, S.J Teipel, Y Zebuhr, G Leinsinger, L. Gootjes, R Schwartz, K Buerger, P. Scheltens, HJ Moeller, H. Hampel, R. Schwarz

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Background: Neurodegenerative and cerebrovascular diseases show a distinct distribution of regional atrophy and subcortical lesions. Objective: To develop an easily applicable landmark-based method for segmentation of the brain into the four cerebral lobes from MRI images. Method: The segmentation method relies on a combination of anatomical landmarks and geometrical definitions. It is applied on the surface reconstruction of the MRI volume. The internal borders between the lobes are defined on the axial slices of the brain. The reliability of this method was determined from MRI scans of 10 subjects. To illustrate the use of the method, it was applied to MRI scans of an independent group of 10 healthy elderly subjects and 10 patients with vascular dementia to determine the regional distribution of white matter hyperintensities (WMH). Results: The intra-rater relative error (and intra-class correlation coefficient) of the lobe segmentation ranged from 1.6% to 6.9% (from 0.91 to 0.99). The inter-rater relative error (and intra-class correlation coefficient) ranged from 1.4% to 5.2% (from 0.96 to 0.99). Density of WMH was significantly higher in all four lobes in VD patients compared to controls (p<0.05). Within each group, WMH density was significantly higher in frontal and parietal than in temporal and occipital lobes (p<0.05). Conclusion: This landmark based method can accommodate age and disease-related changes in brain morphology. It may be particularly useful for the study of neurodegenerative and cerebrovascular disease and for the validation of template-based automated techniques. Copyright © 2002 Elsevier Science B.V.
Original languageEnglish
Pages (from-to)35-40
Number of pages6
JournalJournal of the neurological sciences
Issue number1
Publication statusPublished - 15 Feb 2002


  • Anatomical landmark
  • Brain lobes
  • Regional segmentation
  • White matter hyperintensities

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