Unknown

Dataset Information

0

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


ABSTRACT: 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.

SUBMITTER: Thottupattu A 

PROVIDER: S-EPMC9314342 | biostudies-literature |

REPOSITORIES: biostudies-literature

Similar Datasets

| S-EPMC7670406 | biostudies-literature
| S-EPMC9921328 | biostudies-literature
| S-EPMC6503038 | biostudies-literature
| S-EPMC9537599 | biostudies-literature
| S-EPMC5548603 | biostudies-literature
| PRJEB50407 | ENA
| S-EPMC8184524 | biostudies-literature
| S-EPMC6049036 | biostudies-literature
2014-10-15 | E-MTAB-1977 | biostudies-arrayexpress
| S-EPMC9131142 | biostudies-literature