Top

Journal of Imaging Informatics in Medicine

Published in:

Open Access 01-06-2018

Container-Based Clinical Solutions for Portable and Reproducible Image Analysis

Authors: Jordan Matelsky, Gregory Kiar, Erik Johnson, Corban Rivera, Michael Toma, William Gray-Roncal

Published in: Journal of Imaging Informatics in Medicine | Issue 3/2018

Abstract

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.

Tanenbaum AS: Modern operating system. Pearson Education, Inc, 2009

Soltesz S, Pötzl H, Fiuczynski ME, Bavier A, Peterson L: Container-based operating system virtualization: a scalable, high-performance alternative to hypervisors.. In: ACM SIGOPS Operating Systems Review, vol 41. ACM, 2007, pp 275–287

Docker Accessed: 2018-03-15. https://www.docker.com

Singularity Accessed: 2018-03-15. http://singularity.lbl.gov

Virtual Environment virtualenv Documentation Accessed: 2018-03-15. https://virtualenv.pypa.io/en/stable/

Clark C, Fraser K, Hand S, Hansen JG, Jul E, Limpach C, et al: Live migration of virtual machines.. In: Proceedings of the 2nd Conference on Symposium on Networked Systems Design & Implementation-Volume 2. USENIX Association, 2005, pp 273–286

Amazon Web Services AMIs Accessed: 2018-03-15. https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/AMIs.html

Goldberg RP: Survey of virtual machine research. Computer 7(6): 34–45, 1974

Amazon Web Services FarGate Accessed: 2018-03-15. https://aws.amazon.com/fargate/

10.

Google Cloud Accessed: 2018-03-15. https://cloud.google.com/compute/docs/containers/

11.

Microsoft Azure Accessed: 2018-03-15. https://azure.microsoft.com/en-us/overview/containers/

12.

Kiar G, Gorgolewski KJ, Kleissas D, Roncal WG, Litt B, Wandell B, et al: Science in the cloud (SIC): A use case in MRI connectomics. GigaScience 6(5): 1–10, 2017. Available from: https://doi.org/10.1093/gigascience/gix013

13.

Sherif T, Rioux P, Rousseau ME, Kassis N, Beck N, Adalat R, et al: CBRAIN: A web-based, distributed computing platform for collaborative neuroimaging research. Frontiers in Neuroinformatics 8: 54, 2014

14.

Glatard T, Lartizien C, Gibaud B, Da Silva RF, Forestier G, Cervenansky F, et al: A virtual imaging platform for multi-modality medical image simulation. IEEE Trans Med Imaging 32(1): 110–118, 2013

15.

Merkel D: Docker: Lightweight Linux Containers for Consistent Development and Deployment. Linux J 2014(239):76–91, 2014. Available from: http://dl.acm.org/citation.cfm?id=2600239.2600241

16.

Kurtzer GM, Sochat V, Bauer MW: Available from: https://doi.org/10.1371/journal.pone.0177459. PLOS ONE 12(5): e0177459, 2017

17.

Di Tommaso P, Palumbo E, Chatzou M, Prieto P, Heuer ML, Notredame C: The impact of Docker containers on the performance of genomic pipelines. PeerJ 3: e1273, 2015. Available from: https://doi.org/10.7717/peerj.1273

18.

Hindman B, Konwinski A, Zaharia M, Ghodsi A, Joseph AD, Katz R, et al: Mesos: A Platform for Fine-grained Resource Sharing in the Data Center.. In: Proceedings of the 8th USENIX Conference on Networked Systems Design and Implementation. NSDI’11. USENIX Association, Berkeley, 2011, pp 295–308. Available from: http://dl.acm.org/citation.cfm?id=1972457.1972488

19.

Burns B, Grant B, Oppenheimer D, Brewer E, Wilkes J: Borg, Omega, and Kubernetes. ACM Queue 14: 70–93, 2016. Available from: http://queue.acm.org/detail.cfm?id=2898444

20.

Afgan E, Baker D, Van den Beek M, Blankenberg D, Bouvier D, ČEch M, et al: The Galaxy platform for accessible, reproducible and collaborative biomedical analyses: 2016 update. Nucleic Acids Res 44 (W1): W3–W10, 2016

21.

Awesome Pipelines: Accessed: 2018-03-15. https://github.com/pditommaso/awesome-pipeline/

22.

Mason D: SU-E-T-33: Pydicom: An Open Source DICOM Library. Med Phys 38 (6Part10): 3493–3493, 2011. Available from: https://doi.org/10.1118/1.3611983

23.

Docker Hub: Accessed: 2018-03-15. https://hub.docker.com/

24.

Docker Hub: Accessed: 2018-03-15. https://github.com/singularityware/docker2singularity

25.

Gronenschild EHBM, Habets P, Jacobs HIL, Mengelers R, Rozendaal N, van Os J, et al: The Effects of FreeSurfer Version, Workstation Type, and Macintosh Operating System Version on Anatomical Volume and Cortical Thickness Measurements. PLoS ONE 7(6): e38234, 2012. Available from: https://doi.org/10.1371/journal.pone.0038234

26.

Fischl B: Freesurfer. Neuroimage 62(2): 774–781, 2012

27.

Plesser HE: Reproducibility vs. Replicability: A Brief History of a Confused Terminology. Frontiers in neuroinformatics 11: 76, 2018

28.

Towns J, Cockerill T, Dahan M, Foster I, Gaither K, Grimshaw A, et al: XSEDE: Accelerating Scientific discovery. Computing in Science & Engineering 16(5): 62–74, 2014

29.

Baldwin S: Compute Canada: Advancing Computational Research.. In: Journal of Physics: Conference Series, vol 341. IOP Publishing, 2012, p 012001

Title: Container-Based Clinical Solutions for Portable and Reproducible Image Analysis
Authors: Jordan Matelsky
Gregory Kiar
Erik Johnson
Corban Rivera
Michael Toma
William Gray-Roncal
Publication date: 01-06-2018
Publisher: Springer International Publishing
Published in: Journal of Imaging Informatics in Medicine / Issue 3/2018
Print ISSN: 2948-2925
Electronic ISSN: 2948-2933
DOI: https://doi.org/10.1007/s10278-018-0089-4

At a glance: The ONWARDS insulin icodec trials

Springer Medicine

Container-Based Clinical Solutions for Portable and Reproducible Image Analysis

Abstract

At a glance: The ONWARDS insulin icodec trials

Springer Medicine

Abstract

Please log in to get access to this content

Other articles of this Issue 3/2018

Patient-Centered Radiology with FHIR: an Introduction to the Use of FHIR to Offer Radiology a Clinically Integrated Platform

SimpleITK Image-Analysis Notebooks: a Collaborative Environment for Education and Reproducible Research

DICOMweb™: Background and Application of the Web Standard for Medical Imaging

The Orthanc Ecosystem for Medical Imaging

A Platform for Innovation and Standards Evaluation: a Case Study from the OpenMRS Open-Source Radiology Information System

Standard Lexicons, Coding Systems and Ontologies for Interoperability and Semantic Computation in Imaging