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http://www.nitrc.org/projects/rmdtitemplate/
A population-specific DTI template for young adolescent Rhesus Macaque (Macaca mulatta) monkeys using 271 high-quality scans. Using such a large number of animals in generating a template allows it to account for variability in the species. Their DTI template is based on the largest number of animals ever used in generating a computational brain template. It is anticipated that their DTI template will help facilitate voxel-based and tract specific WM analyses in non-human primate species, which in turn may increase our understanding of brain function, development, and evolution.
Proper citation: DTI-TEMPLATE-RHESUS-MACAQUES (RRID:SCR_002482) Copy
https://github.com/bids-standard/bids-validator
Software validation tool that checks submitted folder structure for compliance to BIDS data standard. Validates Brain Imaging Data Structure.
Proper citation: BIDS Validator (RRID:SCR_017255) Copy
http://www.reproducibleimaging.org
Center to help neuroimaging researchers to find and share data in FAIR fashion, to describe their data and analysis workflows in replicable fashion, to manage their computational resource options so that outcomes of neuroimaging research are more reproducible.
Proper citation: ReproNim: A Center for Reproducible Neuroimaging Computation (RRID:SCR_016001) Copy
http://www.nitrc.org/projects/nitrcext/
Software repository of custom extensions to the GForge collaborative environment.
Proper citation: NITRC GForge Extensions (RRID:SCR_002495) Copy
The MiND: Metadata in NIfTI for DWI framework enables data sharing and software interoperability for diffusion-weighted MRI. This site provides specification details, tools, and examples of the MiND mechanism for representing important metadata for DWI data sets at various stages of post-processing. MiND framework provides a practical solution to the problem of interoperability between DWI analysis tools, and it effectively expands the analysis options available to end users. To assist both users and developers in working with MiND-formatted files, we provide a number of software tools for download. * MiNDHeader A utility for inspecting MiND-extended files. * I/O Libraries Programming libraries to simplify writing and parsing MiND-formatted data. * Sample Files Example files for each MiND schema. * DIRAC LONI''s Diffusion Imaging Reconstruction and Analysis Collection is a DWI processing suite which utilizes the MiND framework.
Proper citation: LONI MiND (RRID:SCR_004820) Copy
http://www.mri-resource.kennedykrieger.org/
Biomedical technology research center that provides expertise for the design of quantitative magnetic resonance imaging (MRI) and spectroscopy (MRS) data acquisition and processing technologies that facilitate the biomedical research of a large community of clinicians and neuroscientists in Maryland and throughout the USA. These methods allow noninvasive assessment of changes in brain anatomy as well as in tissue metabolite levels, physiology, and brain functioning while the brain is changing size during early development and during neurodegeneration, i.e. the changing brain throughout the life span. The Kirby Center has 3 Tesla and 7 Tesla state of the art scanners equipped with parallel imaging (8, 16, and 32-channel receive coils) and multi-transmit capabilities. CIS has an IBM supercomputer that is part of a national supercomputing infrastructure. Resources fall into the following categories: * MRI facilities, image acquisition, and processing * Computing facilities and image analysis * Novel statistical methods for functional brain imaging * Translating laboratory discoveries to patient treatment
Proper citation: National Resource for Quantitative Functional MRI (RRID:SCR_006716) Copy
http://www.loni.usc.edu/Software/DiD
Software application for removing patient-identifying information from medical image files. Removing this information is often necessary for enabling investigators to share image files in a HIPAA compliant manner.
Proper citation: LONI De-identification Debablet (RRID:SCR_009593) Copy
http://www.nitrc.org/projects/dicomconvert/
A DICOM image converter based on the ITK IO mechanism for reading and writing images. The formats currently supported by the converter are DICOM to: Analyze (*.hdr); MetaImage (*.mhd); Nrrd (*.nhdr, *.nrrd).
Proper citation: DICOMConvert (RRID:SCR_014100) Copy
http://www.nitrc.org/projects/moca_2015/
Collection of software tools for the computational analysis of brain anatomy with MRI data. It includes automated software tools from surface reconstruction to their mapping via metric optimization in the Laplace-Beltrami embedding space. It is general and can be applied to a wide range of anatomical structures including cortical, sub-cortical, and fiber bundle surfaces.
Proper citation: MOCA (RRID:SCR_015524) Copy
https://github.com/denisecailab/minian
Software miniscope analysis pipeline that requires low memory and computational demand so it can be run without specialized hardware. Offers interactive visualization that allows users to see how parameters in each step of pipeline affect output.
Proper citation: Minian (RRID:SCR_022601) Copy
A database of digital reconstructions of the human brain arterial arborizations from 61 healthy adult subjects along with extracted morphological measurements. The arterial arborizations include the six major trees stemming from the circle of Willis, namely: the left and right Anterior Cerebral Arteries (ACAs), Middle Cerebral Arteries (MCAs), and Posterior Cerebral Arteries (PCAs).
Proper citation: BraVa (RRID:SCR_001407) Copy
https://github.com/ReproNim/reproschema
Software standardized framework for creating, sharing, and reusing cognitive and clinical assessments. Standardized form generation and data collection schema to harmonize results by design across projects. Used for enhancing research reproducibility through standardized survey data collection.
Proper citation: ReproSchema (RRID:SCR_027848) Copy
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Welcome to the Neuroscience Information Framework Project, designed to serve the biomedical research community. NIF maintains the largest searchable collection of neuroscience data, the largest catalog of biomedical resources, and the largest ontology for neuroscience on the web. We welcome all feedback and suggestions and are actively looking for resource providers to make their resources accessible through NIF. Learn about the tools available to help you share your data and discover a dynamic inventory of Web-based neuroscience resources.
