Large-scale MRI studies of brain development or disease progression require processing of large amount of datasets. Often, acquired in longitudinal fashion, where each subject is followed over period of several years and each dataset contain multiple image modalities.


Our group have developed number of methods to automatically process MRI scans from such projects, taking into account the fact that data from the same subject might be spread across multiple time points. These methods are optimized to increase sensitivity to the longitudinal changes in the subject’s brain and to minimize amount of manual interventions required to completely process datasets. Where the input data consists of the raw mri scans and output is the anatomical measurements that are useful for bio-statisticians.


  1. Aubert-Broche B, Fonov VS, García-Lorenzo D, Mouiha A, Guizard N, Coupé P, Eskildsen SF, Collins DL. A new method for structural volume analysis of longitudinal brain MRI data and its application in studying the growth trajectories of anatomical brain structures in childhood. Neuroimage. 2013 Nov 15;82:393-402. doi: 10.1016/j.neuroimage.2013.05.065


Software for longitudinal processing of MRI data is currently only available for collaborators.