Quantitative comparison of AIR, SPM, and the fully deformable model for atlas-based segmentation of functional and structural MR images

Minjie Wu, Owen Carmichael, Pilar Lopez-Garcia, Cameron S. Carter, Howard J. Aizenstein
2006 Human Brain Mapping  
Typical packages used for coregistration in functional image analyses include automated image registration (AIR) and statistical parametric mapping (SPM). However, both methods have limiteddimension deformation models. A fully deformable model, which combines the piecewise linear registration for coarse alignment with demons algorithm for voxel-level refinement, allows a higher degree of spatial deformation. This leads to a more accurate colocalization of the functional signal from different
more » ... jects and therefore can produce a more reliable group average signal. We quantitatively compared the performance of the three different registration approaches through a series of experiments and we found that the fully deformable model consistently produces a more accurate structural segmentation and a more reliable functional signal colocalization than does AIR or SPM.
doi:10.1002/hbm.20216 pmid:16463385 pmcid:PMC2886594 fatcat:exexak3lcrffxf6duchjxzlus4