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Proceedings Paper

Extending the XNAT archive tool for image and analysis management in ophthalmology research
Author(s): Andreas Wahle; Kyungmoo Lee; Adam T. Harding; Mona K. Garvin; Meindert Niemeijer; Milan Sonka; Michael D. Abràmoff
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Paper Abstract

In ophthalmology, various modalities and tests are utilized to obtain vital information on the eye’s structure and function. For example, optical coherence tomography (OCT) is utilized to diagnose, screen, and aid treatment of eye diseases like macular degeneration or glaucoma. Such data are complemented by photographic retinal fundus images and functional tests on the visual field. DICOM isn’t widely used yet, though, and frequently images are encoded in proprietary formats. The eXtensible Neuroimaging Archive Tool (XNAT) is an open-source NIH-funded framework for research PACS and is in use at the University of Iowa for neurological research applications. Its use for ophthalmology was hence desirable but posed new challenges due to data types thus far not considered and the lack of standardized formats. We developed custom tools for data types not natively recognized by XNAT itself using XNAT’s low-level REST API. Vendor-provided tools can be included as necessary to convert proprietary data sets into valid DICOM. Clients can access the data in a standardized format while still retaining the original format if needed by specific analysis tools. With respective project-specific permissions, results like segmentations or quantitative evaluations can be stored as additional resources to previously uploaded datasets. Applications can use our abstract-level Python or C/C++ API to communicate with the XNAT instance. This paper describes concepts and details of the designed upload script templates, which can be customized to the needs of specific projects, and the novel client-side communication API which allows integration into new or existing research applications.

Paper Details

Date Published: 29 March 2013
PDF: 14 pages
Proc. SPIE 8674, Medical Imaging 2013: Advanced PACS-based Imaging Informatics and Therapeutic Applications, 86740M (29 March 2013); doi: 10.1117/12.2007966
Show Author Affiliations
Andreas Wahle, Iowa Institute for Biomedical Imaging, The Univ. of Iowa (United States)
Kyungmoo Lee, Iowa Institute for Biomedical Imaging, The Univ. of Iowa (United States)
Adam T. Harding, The Univ. of Iowa (United States)
Mona K. Garvin, Iowa Institute for Biomedical Imaging, The Univ. of Iowa (United States)
U.S. Dept. of Veterans Affairs (United States)
Meindert Niemeijer, Iowa Institute for Biomedical Imaging, The Univ. of Iowa (United States)
Milan Sonka, Iowa Institute for Biomedical Imaging, The Univ. of Iowa (United States)
Michael D. Abràmoff, Iowa Institute for Biomedical Imaging, The Univ. of Iowa (United States)
U.S. Dept. of Veterans Affairs (United States)


Published in SPIE Proceedings Vol. 8674:
Medical Imaging 2013: Advanced PACS-based Imaging Informatics and Therapeutic Applications
Maria Y. Law; William W. Boonn, Editor(s)

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