Web based tools for visualizing imaging data and development of XNATView, a zero footprint image viewer

David A. Gutman; William D. Dunn; Jake Cobb; Richard M. Stoner; Jayashree Kalpathy-Cramer; Bradley Erickson

doi:10.3389/fninf.2014.00053

Web based tools for visualizing imaging data and development of XNATView, a zero footprint image viewer

David A. Gutman, William D. Dunn, Jake Cobb, Richard M. Stoner, Jayashree Kalpathy-Cramer, Bradley Erickson

Research output: Contribution to journal › Review article › peer-review

7 Scopus citations

Abstract

Advances in web technologies now allow direct visualization of imaging data sets without necessitating the download of large file sets or the installation of software. This allows centralization of file storage and facilitates image review and analysis. XNATView is a light framework recently developed in our lab to visualize DICOM images stored in The Extensible Neuroimaging Archive Toolkit (XNAT). It consists of a PyXNAT-based framework to wrap around the REST application programming interface (API) and query the data in XNAT. XNATView was developed to simplify quality assurance, help organize imaging data, and facilitate data sharing for intra- and inter-laboratory collaborations. Its zero-footprint design allows the user to connect to XNAT from a web browser, navigate through projects, experiments, and subjects, and view DICOM images with accompanying metadata all within a single viewing instance.

Original language	English (US)
Article number	53
Journal	Frontiers in Neuroinformatics
Volume	8
Issue number	MAY
DOIs	https://doi.org/10.3389/fninf.2014.00053
State	Published - May 27 2014
Externally published	Yes

Keywords

Biomedical imaging
DICOM-viewer
MRI
PyXNAT
Radiology
Web-based image viewer
XNAT

ASJC Scopus subject areas

Neuroscience (miscellaneous)
Biomedical Engineering
Computer Science Applications

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10.3389/fninf.2014.00053

Cite this

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title = "Web based tools for visualizing imaging data and development of XNATView, a zero footprint image viewer",

abstract = "Advances in web technologies now allow direct visualization of imaging data sets without necessitating the download of large file sets or the installation of software. This allows centralization of file storage and facilitates image review and analysis. XNATView is a light framework recently developed in our lab to visualize DICOM images stored in The Extensible Neuroimaging Archive Toolkit (XNAT). It consists of a PyXNAT-based framework to wrap around the REST application programming interface (API) and query the data in XNAT. XNATView was developed to simplify quality assurance, help organize imaging data, and facilitate data sharing for intra- and inter-laboratory collaborations. Its zero-footprint design allows the user to connect to XNAT from a web browser, navigate through projects, experiments, and subjects, and view DICOM images with accompanying metadata all within a single viewing instance.",

keywords = "Biomedical imaging, DICOM-viewer, MRI, PyXNAT, Radiology, Web-based image viewer, XNAT",

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year = "2014",

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doi = "10.3389/fninf.2014.00053",

language = "English (US)",

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AU - Dunn, William D.

AU - Cobb, Jake

AU - Stoner, Richard M.

AU - Kalpathy-Cramer, Jayashree

AU - Erickson, Bradley

PY - 2014/5/27

Y1 - 2014/5/27

N2 - Advances in web technologies now allow direct visualization of imaging data sets without necessitating the download of large file sets or the installation of software. This allows centralization of file storage and facilitates image review and analysis. XNATView is a light framework recently developed in our lab to visualize DICOM images stored in The Extensible Neuroimaging Archive Toolkit (XNAT). It consists of a PyXNAT-based framework to wrap around the REST application programming interface (API) and query the data in XNAT. XNATView was developed to simplify quality assurance, help organize imaging data, and facilitate data sharing for intra- and inter-laboratory collaborations. Its zero-footprint design allows the user to connect to XNAT from a web browser, navigate through projects, experiments, and subjects, and view DICOM images with accompanying metadata all within a single viewing instance.

AB - Advances in web technologies now allow direct visualization of imaging data sets without necessitating the download of large file sets or the installation of software. This allows centralization of file storage and facilitates image review and analysis. XNATView is a light framework recently developed in our lab to visualize DICOM images stored in The Extensible Neuroimaging Archive Toolkit (XNAT). It consists of a PyXNAT-based framework to wrap around the REST application programming interface (API) and query the data in XNAT. XNATView was developed to simplify quality assurance, help organize imaging data, and facilitate data sharing for intra- and inter-laboratory collaborations. Its zero-footprint design allows the user to connect to XNAT from a web browser, navigate through projects, experiments, and subjects, and view DICOM images with accompanying metadata all within a single viewing instance.

KW - Biomedical imaging

KW - DICOM-viewer

KW - MRI

KW - PyXNAT

KW - Radiology

KW - Web-based image viewer

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Web based tools for visualizing imaging data and development of XNATView, a zero footprint image viewer

Abstract

Keywords

ASJC Scopus subject areas

Access to Document

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