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. 2018 May 3;31(3):304–314. doi: 10.1007/s10278-018-0080-0

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© The Author(s) 2018

Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

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Fig. 4 — The working flow of image processing tasks using VUIIS CCI medical image data storage and processing infrastructure. (1) RedCap triggers DAX to start image processing based on a pre-defined “.yaml” configuration file, specifying which spider to execute (code is available on https://github.com/MASILab/Containerized_DAX). (2) DAX defines data retrieval, computing environment, and software dependencies from a python based spider (code is provided in APPENDIX). (3) Computational infrastructure (e.g., ACCRE) downloads the input data from XNAT. (4) Computational infrastructure executes the related processing algorithms (e.g., “Deep_MultiOrganSeg,” whose Docker image is available on https://hub.docker.com/r/masidocker/spiders/). (5) The results (e.g., segmentation volumes and final report in Fig. 3e) are pushed back to XNAT database