About our group:
The Medical-image Analysis and Statistical Interpretation (MASI) lab wa established by Dr. Bennett Landman in 2010. The MASI research laboratory concentrates on analyzing large-scale cross-sectional and longitudinal neuroimaging data. Specifically, we are interested in population characterization with magnetic resonance imaging (MRI), multi-parametric studies (DTI, sMRI, qMRI), and shape modeling.
The VUIIS Center for Human Studies provides facilities and technical support for structural, metabolic and functional imaging of human subjects. Facilities include two state-of-the-art 3T MRI scanners (Philips Healthcare), one of only a handful of 7T scanners worldwide (also Philips Healthcare), Near Infra-red Optical Topography (NIROT), and Event-related potential (ERP) electroencephalography. VUIIS faculty members also have access to extensive clinical imaging resources including PET, PET-CT, and 1.5T MRI.
About our XNAT project(s):
All data from human MRI scanners is automatically routed to a DCM4CHEE PACS and then into XNAT.Additionally, we have four beta-testing groups with large, dedicated research projects. We are working to integrate multi-site, multi-modality information with XNAT, RedCAP, and other data sources. We are working to transition our automated processing infrastructure from the existing custom server to use XNAT as a data source. We intended to include extensive processing support as part of infrastructure service of the imaging institute.
As of June 2012, we have 323 projects, 1477 subjects, and 2115 imaging sessions with 65 TB of online storage. I expect to double the number of subjects and sessions in the next 12 months. For 2013-2018, we project 20% annual growth.
Our goals for the XNAT Workshop:
We would like to resolve outstanding issues with PyXNAT and prepare to upgrade from 1.5.3 to 1.6.