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.ĭata management challenges regularly pose problems among imaging laboratories. XNATView was developed to simplify quality assurance, help organize imaging data, and facilitate data sharing for intra- and inter-laboratory collaborations. It consists of a PyXNAT-based framework to wrap around the REST application programming interface (API) and query the data in XNAT. XNATView is a light framework recently developed in our lab to visualize DICOM images stored in The Extensible Neuroimaging Archive Toolkit (XNAT). This allows centralization of file storage and facilitates image review and analysis. 5Department of Radiology, Mayo Clinic, Rochester, MN, USAĪdvances in web technologies now allow direct visualization of imaging data sets without necessitating the download of large file sets or the installation of software.4Harvard-MIT Division of Health Sciences and Technology, Martinos Center for Biomedical Imaging, Charlestown, MA, USA.
3Department of Neurosciences, University of California San Diego School of Medicine, La Jolla, CA, USA.2Georgia Institute of Technology, College of Computing, Atlanta, GA, USA.1Department of Biomedical Informatics, Emory University, Atlanta, GA, USA.Stoner 3, Jayashree Kalpathy-Cramer 4 and Bradley Erickson 5
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