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http://www.nitrc.org/projects/fopa/

A standardized framework for communication and data exchange between medical imaging applications, with particular focus on neuroimaging technologies. FOPA is an attempt to design and implement a common protocol for network and command line communication with either file-system or imbedded data structures. Initial reference implementations will support interoperability between ITK, VTK, and Java platforms. Contributions are welcome from other neuroimaging development communities.

Proper citation: Framework for Open Programmatic Access (RRID:SCR_009479) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/dentaltools/

Software package that provides 3D imaging resources such as multimodal imaging, volume and mesh processing or segmentation for Dental Research. DentalTools package intends to contribute to the free exchange of information and methods in the dentistry research community.

Proper citation: DentalTools (RRID:SCR_009463) Copy   

•   Source: SciCrunch Registry

https://wiki.nci.nih.gov/display/caGWAS/caGWAS

Too that allows researchers to integrate, query, report, and analyze significant associations between genetic variations and disease, drug response or other clinical outcomes. SNP array technologies make it possible to genotype hundreds of thousands of single nucleotide polymorphisms (SNPs) simultaneously, enabling whole genome association studies. Within the Clinical Genomic Object Model (CGOM), the caIntegrator team created a domain model for Whole Genome Association Study Analysis. CGOM-caGWAS is a A semantically annotated domain model that captures associations between Study, Study Participant, Disease, SNP Association Analysis, SNP Population Frequency and SNP annotations. caGWAS APIs and web portal provide: * a semantically annotated domain model, database schema with sample data, seasoned middleware, APIs, and web portal for GWAS data; * platform and disease agnostic CGOM-caGWAS model and associated APIs; * the opportunity for developers to customize the look and feel of their GWAS portal; * a foundation of open source technologies; * a well-tested and performance-enhanced platform, as the same software is being used to house the CGEMS data portal; * accelerated analysis of results from various biomedical studies; and * a single application through which researchers and bioinformaticians can access and analyze clinical and experimental data from a variety of data types, as caGWAS objects are part of the CGOM, which includes microarray, genomic, immunohistochemistry, imaging, and clinical data.

Proper citation: caGWAS (RRID:SCR_009617) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/neuroweb/

Infrastructure for data aggregation, processing, and management in multi-dimensional medical imaging research (i.e., MRI, CT, PET). NeuroWeb is designed for rapid deployment on a small/moderate scale with limited hardware.

Proper citation: NeuroWeb - NeuroImaging Database (RRID:SCR_009610) Copy   

•   Source: SciCrunch Registry

http://www.magventure.com

A complete line of non-invasive magnetic stimulation systems designed for clinical examinations and for research in the areas of neurophysiology, neurology, cognitive neuroscience, rehabilitation and psychiatry.

Proper citation: MagPro Magnetic Stimulator (RRID:SCR_009601) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/magdande

A variety of MEG- and fMRI-compatible hardware for research use including typical response collection devices such as joysticks, response pads, mice, as well as stimulation devices such as vibrotactile stimulators, olfactometers, and pressure/force generators. The company also offers custom design and production services for many different applications.

Proper citation: Mag Design and Engineering (RRID:SCR_009600) Copy   

•   Source: SciCrunch Registry

http://www.distributome.org/

An open-source, open content-development project for exploring, discovering, navigating, learning, and computational utilization of diverse probability distributions.

Proper citation: Distributome (RRID:SCR_009564) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/probbiascor/

A multichannel capable tool for probabilistic inhomogeneity correction implemented as both a standalone command line tool and a Slicer3 module.

Proper citation: ProbabilisticBiasCorrection (RRID:SCR_009638) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/pobe/

Computer program that provides a graphical user interface for fMRI researchers to easily and efficiently design their blocked experiments. The computer program POBE calculates the optimal number of subjects and the optimal scanning time for user specified experimental factors and model parameters so that the statistical efficiency is maximised for a given study budget. POBE can also be used to determine the minimum budget for a given power. Furthermore, a maximin design can be determined as efficient design for a possible range of values for the unknown model parameters.

Proper citation: Program for optimal design of blocked fMRI experiments (RRID:SCR_009639) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/dl_dataset/

Script which points browser to Nathan Kline Institute (NKI) Rockland Sample.

Proper citation: Rockland Download Link Script (RRID:SCR_009513) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/cogicat/

While the traditional temporally concatenated Group ICA (TC-GICA) adopting three steps of PCA reduction, it could result in inconsistent and variable components when different subject orders were used, both for the group- and individual-level results. Such instability can further cause instable and thus unreliable statistical results. Subject Order-Independent Group ICA (SOI-GICA) aims to fix this problem by producing stable and reliable GICA results. For details please see the paper Subject Order-Independent Group ICA (SOI-GICA) for Functional MRI Data Analysis (Zhang et al., 2010, NeuroImage)(http://dx.doi.org/10.1016/j.neuroimage.2010.03.039). MICA is the toolbox inplemented SOI-GICA for convenience of usage.

Proper citation: Subject Order-Independent Group ICA (RRID:SCR_009514) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/pnve/

A self-contained virtual machine that can be executed on a common laptop or desktop, enabling the Pipeline to run virtually anywhere. Neophytes to the Pipeline can have their own private server running in minutes, software engineers and workflow designers can use the PNVE as a sandbox, and those without access to grid computing facilities can now take full advantage of the Pipeline processing environment.

Proper citation: Pipeline Neuroimaging VirtualEnvironment (RRID:SCR_009635) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/brainnet_2013/

Tool that associates localized white matter (WM) lesions with disruptions in gray matter connectivity as a step toward understanding the lesions? functional implications. A Tractogram Reference Set (TRS), i.e. collections of white matter fibers, is constructed from 73 normal healthy individuals and coregistered to a common space (MNI). The NeMo Tool uses the TRS to assess structural network disruption due to a particular WM lesion mask on a region and network-wise level. This tool is an easy way for researchers and clinicians to investigate changes in the structural brain network without having to perform tractography on their own normal data or on diseased/injured brains where the results may not represent the underlying physiology.

Proper citation: Network Modification Tool Lite (RRID:SCR_009511) Copy   

•   Source: SciCrunch Registry

http://www.unicog.org/pm/pmwiki.php/MEG/RemovingArtifactsWithADJUST

A completely automatic algorithm for artifact identification and removal in EEG data. ADJUST is based on Independent Component Analysis (ICA), a successful but unsupervised method for isolating artifacts from EEG recordings. ADJUST identifies artifacted ICA components by combining stereotyped artifact-specific spatial and temporal features. Features are optimised to capture blinks, eye movements and generic discontinuities. Once artifacted IC are identified, they can be simply removed from the data while leaving the activity due to neural sources almost unaffected.

Proper citation: ADJUST (RRID:SCR_009526) Copy   

•   Source: SciCrunch Registry

https://cran.r-project.org/src/contrib/Archive/brainwaver/

Characterization of small-world networks constructed from wavelet analysis of resting fMRI. This package is currently available as an R library. Futrure development will take place within the CamBA software repository

Proper citation: Brainwaver (RRID:SCR_009540) Copy   

•   Source: SciCrunch Registry

http://www.harvard.edu/

Institution of higher education in the United States. Private Ivy League research university in Cambridge, Massachusetts.

Proper citation: Harvard University; Cambridge; United States (RRID:SCR_011273) Copy   

•   Source: SciCrunch Registry

http://www.nlm.nih.gov/

NLM collects, organizes, and makes available biomedical science information to scientists, health professionals, and the public. The Library's Web-based databases, including PubMed/Medline and MedlinePlus, are used extensively around the world. NLM conducts and supports research in biomedical communications; creates information resources for molecular biology, biotechnology, toxicology, and environmental health; and provides grant and contract support for training, medical library resources, and biomedical informatics and communications research. Celebrating its 175th anniversary in 2011, the National Library of Medicine (NLM), in Bethesda, Maryland, is a part of the National Institutes of Health, U.S. Department of Health and Human Services (HHS). Since its founding in 1836 as the library of the U.S. Army Surgeon General, NLM has played a pivotal role in translating biomedical research into practice. It is the world's largest biomedical library and the developer of electronic information services that deliver trillions of bytes of data to millions of users every day. Scientists, health professionals, and the public in the United States and around the globe search the Library's online information resources more than 1 billion times each year. The Library is open to all and has many services and resources for scientists, health professionals, historians, and the general public. NLM has over 17 million books, journals, manuscripts, audiovisuals, and other forms of medical information on its shelves, making it the largest health-science library in the world. In today's increasingly digital world, NLM carries out its mission of enabling biomedical research, supporting health care and public health, and promoting healthy behavior by: * Acquiring, organizing, and preserving the world's scholarly biomedical literature; * Providing access to biomedical and health information across the country in partnership with the 5,800-member National Network of Libraries of Medicine (NN/LM); * Serving as a leading global resource for building, curating and providing sophisticated access to molecular biology and genomic information, including those from the Human Genome Project and NIH Common Fund; * Creating high-quality information services relevant to toxicology and environmental health, health services research, and public health; * Conducting research and development on biomedical communications systems, methods, technologies, and networks and information dissemination and utilization among health professionals, patients, and the general public; * Funding advanced biomedical informatics research and serving as the primary supporter of pre- and post-doctoral research training in biomedical informatics at 18 U.S. universities.

Proper citation: National Library of Medicine (RRID:SCR_011446) Copy   

•   Source: SciCrunch Registry

http://enigma.ini.usc.edu/

Network that brings together researchers in imaging genomics, to understand brain structure and function, based on MRI, DTI, fMRI and genomewide association scan (GWAS) data. The ENIGMA Network has several goals: * to create a network of like-minded individuals, interested in pushing forward the field of imaging genetics * to ensure promising findings are replicated via member collaborations, in order to satisfy the mandates of most journals * to share ideas, algorithms, data, and information on promising findings or methods * to facilitate training, including workshops and conferences on key methods and emerging directions in imaging genetics. Data sharing with other members of the ENIGMA Network is optional and by no means a requirement of joining the network. Genetics and Imaging Protocols are available.

Proper citation: ENIGMA: Enhancing Neuro Imaging Genetics Through Meta-Analysis (RRID:SCR_005515) Copy   

•   Source: SciCrunch Registry

http://treestoolbox.org/

Software package, written in Matlab (Mathworks, Natick, MA), providing tools to automatically reconstruct neuronal branching from microscopy image stacks and to generate synthetic axonal and dendritic trees. It provides the basic tools to edit, visualize and analyze dendritic and axonal trees, methods for quantitatively comparing branching structures between neurons, and tools for exploring how dendritic and axonal branching depends on local optimization of total wiring and conduction distance.

Proper citation: TREES toolbox (RRID:SCR_010457) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/medvr/

This resouce will centralize development of tools for interaction with medical imaging data in immersive virtual environments (based on the Vizard platform).

Proper citation: Medical Image Processing and Visualization in Virtual Environments (RRID:SCR_001751) Copy   

•   Source: SciCrunch Registry