Very high-resolution morphometry using mass-preserving deformations and HAMMER elastic registration.
This article presents a very high-resolution voxel-based morphometric method, by using a mass-preserving deformation mechanism and a fully automated spatial normalization approach, referred to as HAMMER. By using a hierarchical attribute-based deformation strategy, HAMMER partly overcomes limitations of several existing spatial normalization methods, and it achieves a level of accuracy that makes possible morphometric measurements of spatial specificity close to the voxel dimensions. The proposed method is validated by a series of experiments, with both simulated and real brain images.
Shen
Dinggang
D
Section of Biomedical Image Analysis, Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA.
Davatzikos
Christos
C
D000328:Adult; D000368:Aged; D000375:Aging / Q000502:physiology*; D000465:Algorithms; D001284:Atrophy; D015142:Baltimore; D001921:Brain / Q000473:pathology*; D002540:Cerebral Cortex / Q000473:pathology; D002552:Cerebral Ventricles / Q000473:pathology; D001330:Electronic Data Processing / Q000379:methods; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional; D008137:Longitudinal Studies; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D008875:Middle Aged; D012016:Reference Values