Research output

A time-saving and facilitating approach for segmentation of anatomically defined cortical regions: MRI volumetry

Research output: Contribution to journalArticleAcademicpeer-review

Associated researcher

  • Gronenschild, E. H. B. M.
  • Burgmans, S.
  • Smeets, F. G. B.
  • Vuurman, Eric F.

  • Uylings, H. B.
  • Jolles, J.

Associated organisations

Abstract

In this study, we present an accurate, reliable, robust, and time-efficient technique for a semi-automatic segmentation of neuroanatomically defined cortical structures in Magnetic Resonance Imaging (MRI) scans. It involves manual drawing of the border of a region of interest (ROI), supported by three-dimensional (3D) visualization techniques (rendering), and a subsequent automatic tracing of the gray matter voxels inside the ROI by means of an automatic tissue classifier. The approach has been evaluated on a set of MRI scans of 75 participants selected from the Maastricht Aging Study (MAAS) and applied to cortical brain structures for both the left and right hemispheres, viz., the inferior prefrontal cortex (PFC); the orbital PFC; the dorsolateral PFC; the anterior cingulate cortex; and the posterior cingulate cortex. The use of a 3D surface-rendered brain can be rotated in any direction was invaluable in identifying anatomical landmarks on the basis of gyral and sulcal topography. This resulted in a high accuracy (anatomical correctness) and reliability: the intra-rater intra-class correlation coefficient (ICC) was between 0.96 and 0.99. Furthermore, the obtained time savings were substantial, i.e., up to a factor of 7.5 compared with fully manual segmentations.

    Research areas

  • Human brain, Prefrontal areas, Cingulate cortex, Image processing, Manual editing, INTENSITY NONUNIFORMITY CORRECTION, VOXEL-BASED MORPHOMETRY, AUTOMATED SEGMENTATION, PARCELLATION METHOD, ALZHEIMERS-DISEASE, CAUDATE-NUCLEUS, TEMPORAL-LOBE, BRAIN MRI, HIGH-RISK, HIPPOCAMPUS
View graph of relations

Details

Original languageEnglish
Pages (from-to)211-218
Number of pages8
JournalPsychiatry Research-Neuroimaging
Volume181
Issue number3
DOIs
Publication statusPublished - 30 Mar 2010