BigData Analysis for Medical Imaging

There is no consensus in literature about lifespan brain maturation and senescence, mainly because previous lifespan studies have been performed on restricted age periods and/or with a limited number of scans, making results instable and their comparison very difficult. Moreover, the use of non-harmonized tools and different volumetric measurements lead to a great discrepancy in reported results. Thanks to the new paradigm of BigData sharing in neuroimaging and the last advances in image processing enabling to process baby as well as elderly scans with the same tool, new insights on brain maturation and aging can be obtained.

In this field our main contributions are: i) the development of new tools able to robustly process massive datasets, ii ) the first analysis of brain structure volume over the entire lifespan and iii) its application to Alzheimer’s Disease.