Abstract
Image and data processing plays an increasingly important role in medical research. Improvements in acquisition techniques and collaborations across traditionally separate research fields, such as fusing genomics and radiological information in decision making, lead to an ever increasing, in number as well as in size, amount of data. Managing and sharing this amount of data remains an important area of study. One well-known solution to this problem is the extensible neuroimaging archive toolkit (XNAT) [1], which provides a storage and management solution for large amounts of disparate data. However the processing of data remains largely separate and requires a lot of manual interaction.
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Goch, C.J., Metzger, J., Nolden, M. (2017). Abstract: Medical Research Data Management Using MITK and XNAT. In: Maier-Hein, geb. Fritzsche, K., Deserno, geb. Lehmann, T., Handels, H., Tolxdorff, T. (eds) Bildverarbeitung für die Medizin 2017. Informatik aktuell. Springer Vieweg, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-54345-0_68
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DOI: https://doi.org/10.1007/978-3-662-54345-0_68
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