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XNAT Central is a publicly accessible medical imaging data repository based on the XNAT open-source imaging informatics platform. It hosts a wide variety of research imaging data sets. The primary motivation for creating XNAT Central was to provide a central repository to host and provide access to a wide variety of neuroimaging data. In this capacity, XNAT Central hosts a number of data sets from research labs and investigative efforts from around the world, including the OASIS Brains imaging studies, the NUSDAST study of schizophrenia, and more. Over time, XNAT Central has expanded to include imaging data from many different fields of research, including oncology, orthopedics, cardiology, and animal studies, but continues to emphasize neuroimaging data. Through the use of XNAT's DICOM metadata extraction capabilities, XNAT Central provides a searchable repository of imaging data that can be referenced by groups, labs, or individuals working in many different areas of research. The future development of XNAT Central will be geared towards greater ease of use as a reference library of heterogeneous neuroimaging data and associated synthetic data. It will also become a tool for making data available supporting published research and academic articles. [ABSTRACT FROM AUTHOR]

Since the early 2000's, much of the neuroimaging work at Washington University (WU) has been facilitated by the Central Neuroimaging Data Archive (CNDA), an XNAT-based imaging informatics system. The CNDA is uniquely related to XNAT, as it served as the original codebase for the XNAT open source platform. The CNDA hosts data acquired in over 1000 research studies, encompassing 36,000 subjects and more than 60,000 imaging sessions. Most imaging modalities used in modern human research are represented in the CNDA, including magnetic resonance (MR), positron emission tomography (PET), computed tomography (CT), nuclear medicine (NM), computed radiography (CR), digital radiography (DX), and ultrasound (US). However, the majority of the imaging data in the CNDA are MR and PET of the human brain. Currently, about 20% of the total imaging data in the CNDA is available by request to external researchers. CNDA's available data includes large sets of imaging sessions and in some cases clinical, psychometric, tissue, or genetic data acquired in the study of Alzheimer's disease, brain metabolism, cancer, HIV, sickle cell anemia, and Tourette syndrome. [ABSTRACT FROM AUTHOR]

ConnectomeDB is a database for housing and disseminating data about human brain structure, function, and connectivity, along with associated behavioral and demographic data. It is the main archive and dissemination platform for data collected under the WU-Minn consortium Human Connectome Project. Additional connectome-style study data is and will be made available in the database under current and future projects, including the Connectome Coordination Facility. The database currently includes multiple modalities of magnetic resonance imaging (MRI) and magnetoencephalograpy (MEG) data along with associated behavioral data. MRI modalities include structural, task, resting state and diffusion. MEG modalities include resting state and task. Imaging data includes unprocessed, minimally preprocessed and analysis data. Imaging data and much of the behavioral data are publicly available, subject to acceptance of data use terms, while access to some sensitive behavioral data is restricted to qualified investigators under a more stringent set of terms. ConnectomeDB is the public side of the WU-Minn HCP database platform. As such, it is geared towards public distribution, with a web-based user interface designed to guide users to the optimal set of data for their needs and a robust backend mechanism based on the commercial Aspera fasp service to enable high speed downloads. HCP data is also available via direct shipment of hard drives and Amazon S3. [ABSTRACT FROM AUTHOR]

Abstract: The Human Connectome Project (HCP) has developed protocols, standard operating and quality control procedures, and a suite of informatics tools to enable high throughput data collection, data sharing, automated data processing and analysis, and data mining and visualization. Quality control procedures include methods to maintain data collection consistency over time, to measure head motion, and to establish quantitative modality-specific overall quality assessments. Database services developed as customizations of the XNAT imaging informatics platform support both internal daily operations and open access data sharing. The Connectome Workbench visualization environment enables user interaction with HCP data and is increasingly integrated with the HCP's database services. Here we describe the current state of these procedures and tools and their application in the ongoing HCP study. [Copyright &y& Elsevier]