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Population-based imaging biobanks as source of big data

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Abstract

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.

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Authors and Affiliations

  1. Department of Radiology, University of Tübingen, Hoppe-Seyler-Str. 3, 72076, Tübingen, Germany

    Sergios Gatidis, Sophia D. Heber, Corinna Storz & Fabian Bamberg

Authors
  1. Sergios Gatidis
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  2. Sophia D. Heber
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  3. Corinna Storz
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  4. Fabian Bamberg
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Correspondence to Fabian Bamberg.

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Author S. Gatidis declares that he has no conflict of interest. Author S. D. Heber declares that she has no conflict of interest. Author C. Storz declares that she has no conflict of interest. Author F. Bamberg declares that he has no conflict of interest.

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This article does not contain any studies with human participants or animals performed by any of the authors.

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Gatidis, S., Heber, S.D., Storz, C. et al. Population-based imaging biobanks as source of big data. Radiol med 122, 430–436 (2017). https://doi.org/10.1007/s11547-016-0684-8

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  • DOI: https://doi.org/10.1007/s11547-016-0684-8

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