A diffeomorphic aging model for adult human brain from cross-sectional data.

Normative aging trends of the brain can serve as an important reference in the assessment of neurological structural disorders. Such models are typically developed from longitudinal brain image data-follow-up data of the same subject over different time points. In practice, obtaining such longitudinal data is difficult. We propose a method to develop an aging model for a given population, in the absence of longitudinal data, by using images from different subjects at different time points, the so-called cross-sectional data. We define an aging model as a diffeomorphic deformation on a structural template derived from the data and propose a method that develops topology preserving aging model close to natural aging. The proposed model is successfully validated on two public cross-sectional datasets which provide templates constructed from different sets of subjects at different age points.

Construction of Indian human brain atlas.

CONTEXT: A brain magnetic resonanace imaging (MRI) atlas plays an important role in many neuroimage analysis tasks as it provides an atlas with a standard coordinate system which is needed for spatial normalization of a brain MRI. Ideally, this atlas should be as near to the average brain of the population being studied as possible. AIMS: The aim of this study is to construct and validate the Indian brain MRI atlas of young Indian population and the corresponding structure probability maps. SETTINGS AND DESIGN: This was a population-specific atlas generation and validation process. MATERIALS AND METHODS: 100 young healthy adults (M/F = 50/50), aged 21-30 years, were recruited for the study. Three different 1.5-T scanners were used for image acquisition. The atlas and structure maps were created using nonrigid groupwise registration and label-transfer techniques. COMPARISON AND VALIDATION: The generated atlas was compared against other atlases to study the population-specific trends. RESULTS: The atlas-based comparison indicated a signifi cant difference between the global size of Indian and Caucasian brains. This difference was noteworthy for all three global measures, namely, length, width, and height. Such a comparison with the Chinese and Korean brain templates indicate all 3 to be comparable in length but signifi cantly different (smaller) in terms of height and width. CONCLUSIONS: The findings confirm that there is significant difference in brain morphology between Indian, Chinese, and Caucasian populations.