Abstract
As neuroimaging databases grow in size and complexity, the time researchers spend investigating and managing the data increases to the expense of data analysis. As a result, investigators rely more and more heavily on scripting using high-level languages to automate data management and processing tasks. For this, a structured and programmatic access to the data store is necessary. Web services are a first step toward this goal. They however lack in functionality and ease of use because they provide only low-level interfaces to databases. We introduce here PyXNAT, a Python module that interacts with The Extensible Neuroimaging Archive Toolkit (XNAT) through native Python calls across multiple operating systems. The choice of Python enables PyXNAT to expose the XNAT Web Services and unify their features with a higher level and more expressive language. PyXNAT provides XNAT users direct access to all the scientific packages in Python. Finally PyXNAT aims to be efficient and easy to use, both as a back-end library to build XNAT clients and as an alternative front-end from the command line.
Highlights
The neuroimaging community is producing imaging and related data at an increasing rate
We introduce here PyXNAT, a Python module that interacts with The Extensible Neuroimaging ArchiveToolkit (XNAT) through native Python calls across multiple operating systems
The USA-based Biomedical Informatics Research Network (BIRN) has during the past 10 years developed a number of tools to facilitate collaborative research and data sharing in neuroimaging
Summary
The neuroimaging community is producing imaging and related data at an increasing rate. Other consortia and initiatives have emerged to facilitate the handling and sharing of neuroimaging data such as Neurolog (Montagnat and Gaignard, 2008) and CABIG (Kakazu et al, 2004) Projects such as the ADNI (Petersen et al, 2010) make available high quality large datasets to the community, and the number of large multi-modal databases is growing very fast (Van Essen, 2002; Van Horn and Toga, 2009). It is installed in many major institutions and enjoys an increasing adoption in the community
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