Global spatial normalization of human brain using convex hulls

Global spatial normalization transforms a brain image so that its principal global spatial features (position, orientation and dimensions) match those of a standard or atlas brain supporting consistent analysis and referencin g Df brain locations. The convex hull (CH), derived from the brain's surfac e, was selected as the basis for automating and standardizing global spatia l normalization. The accuracy and precision of CH global spatial normalizat ion of PET and MR brain images were evaluated in normal human subjects, Met hods: Software was developed to extract CHs of brain surfaces from tomograp hic brain images. Pelizzari's hat-to-head least-square-error surface-fittin g method was modified to fit individual CHs thats) to a template CH (head) and calculate a nine-parameter coordinate transformation to perform spatial normalization. A template CH was refined using MR images from 12 subjects to optimize-global spatial feature conformance to the 1988 Talairach Atlas brain. The template was tested in 12 additional subjects. Three major perfo rmance characteristics were evaluated: (a) quality of spatial normalization with anatomical MR images, (b) optimal threshold for PET and (c) quality o f spatial normalization for functional PET images. Results: As a surface mo del of the human brain, the CH was shown to be highly consistent across: su bjects and imaging modalities. In MR images (n = 24), mean errors for anter ior and posterior commissures generally were < 1 mm,with SDs < 1.5 mm. Mean brain-dimension errors generally were < 1.3 mm, and bounding limits were w ithin 1-2 mm of the Talairach Atlas values. The optimal threshold for defin ing brain boundaries in both F-18-fluorodeoxyglucose (n = 8) and O-15-water (n = 12) PET images was 40% of the brain maximum value. The accuracy of gl obal spatial normalization of PET images was shown to be Similar to that of MR images; Conclusion: The:global features of CH-spatially normalized brai n images (position, orientation and size?) were consistently transformed to match the Talairach Atlas in both MR and PET images. The CH method support s intermodality and intersubject global;spatial normalization of tomographi c brain images.