CerebroMatic: A Versatile Toolbox for Spline-Based MRI Template Creation.

ABSTRACT: Brain image spatial normalization and tissue segmentation rely on prior tissue probability maps. Appropriately selecting these tissue maps becomes particularly important when investigating "unusual" populations, such as young children or elderly subjects. When creating such priors, the disadvantage of applying more deformation must be weighed against the benefit of achieving a crisper image. We have previously suggested that statistically modeling demographic variables, instead of simply averaging images, is advantageous. Both aspects (more vs. less deformation and modeling vs. averaging) were explored here. We used imaging data from 1914 subjects, aged 13 months to 75 years, and employed multivariate adaptive regression splines to model the effects of age, field strength, gender, and data

SUBMITTER: Wilke M 

PROVIDER: S-EPMC5321046 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature