Representative brain selection using a group-specific tissue probability map

PURPOSE: To determine the anatomy of a standard brain reflecting well-defined group characteristics based on probabilistic information from group-specific anatomical variations. MATERIALS AND METHODS: We constructed a group-specific tissue probabilistic map for 20 subjects and used it to extract voxel-wise probabilistic information for each subject through regional spatial normalization using Automated Image Registration software (AIR 5.2.5). Extracted probabilistic information was then used to determine standard properties of the subjects. For comparison, we employed an empirical scoring function - a measure of entropy - in ordering the data set. A brain with minimum entropy was then selected for a group standard. The evaluation of our proposed method was performed using two different selection schemes: deformation analysis and similarity index measurements. RESULTS: This method showed highly correlated result with previous method by Kochunov et al., with fewer computational tasks. CONCLUSION: This method can thus be used to determine an appropriate standard model to compare with disease-affected brains.