Population-based imaging biobanks as source of big data.
Advances of computational sciences over the last decades have enabled the introduction of novel methodological approaches in biomedical research. Acquiring extensive and comprehensive data about a research subject and subsequently extracting significant information has opened new possibilities in gaining insight into biological and medical processes. This so-called big data approach has recently found entrance into medical imaging and numerous epidemiological studies have been implementing advanced imaging to identify imaging biomarkers that provide information about physiological processes, including normal development and aging but also on the development of pathological disease states. The purpose of this article is to present existing epidemiological imaging studies and to discuss opportunities, methodological and organizational aspects, and challenges that population imaging poses to the field of big data research.
Department of Radiology, University of Tübingen, Hoppe-Seyler-Str. 3, 72076, Tübingen, Germany.
Sergios
S
Gatidis
Department of Radiology, University of Tübingen, Hoppe-Seyler-Str. 3, 72076, Tübingen, Germany.
Sophia D
SD
Heber
Department of Radiology, University of Tübingen, Hoppe-Seyler-Str. 3, 72076, Tübingen, Germany.
Corinna
C
Storz
Department of Radiology, University of Tübingen, Hoppe-Seyler-Str. 3, 72076, Tübingen, Germany. fabian.bamberg@med.uni-tuebingen.de.
Fabian
F
Bamberg
D018070:Biological Specimen Banks; D057225:Data Mining; D003952:Diagnostic Imaging; D006801:Humans
Big data; Epidemiology; Imaging; MRI