Container-Based Clinical Solutions for Portable and Reproducible Image Analysis.

Medical imaging analysis depends on the reproducibility of complex computation. Linux containers enable the abstraction, installation, and configuration of environments so that software can be both distributed in self-contained images and used repeatably by tool consumers. While several initiatives...

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Published in:Journal of Digital Imaging Vol. 31; no. 3; pp. 315 - 321
Main Authors: Matelsky, Jordan, Johnson, Erik, Rivera, Corban, Toma, Michael, Gray-Roncal, William, Kiar, Gregory
Format: computer program tables/charts Journal Article
Published: Springer Nature Jun2018
Online Access:View this record in EBSCOhost
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      pub: Springer Nature
      place: New York, New York
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        atl: Container-Based Clinical Solutions for Portable and Reproducible Image Analysis.
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          Matelsky, Jordan
          Johnson, Erik
          Rivera, Corban
          Toma, Michael
          Gray-Roncal, William
          Kiar, Gregory
        affil: Applied Physics Laboratory, Johns Hopkins University, 11100 Johns Hopkins Road, 20723-6099, Laurel, MD, USA
      sug:
        subj:
          Radiographic Image Interpretation, Computer-Assisted
          Software
          Systems Design
      ab: Medical imaging analysis depends on the reproducibility of complex computation. Linux containers enable the abstraction, installation, and configuration of environments so that software can be both distributed in self-contained images and used repeatably by tool consumers. While several initiatives in neuroimaging have adopted approaches for creating and sharing more reliable scientific methods and findings, Linux containers are not yet mainstream in clinical settings. We explore related technologies and their efficacy in this setting, highlight important shortcomings, demonstrate a simple use-case, and endorse the use of Linux containers for medical image analysis.
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        tables/charts
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    language: English
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