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Software repository for comparing structural (MRI) and functional neuroimaging (fMRI, PET, EEG, MEG) software tools and resources. NITRC collects and points to standardized information about structural or functional neuroimaging tool or resource.
Proper citation: NeuroImaging Tools and Resources Collaboratory (NITRC) (RRID:SCR_003430) Copy
http://www.nitrc.org/projects/gpu-areg/
This tool can be used as a command line module with 3D Slicer (version 3 and above) for the affine registration of image volumes. The registration toolbox has 2 options: 1) a Mutual Information based registration, 2) a Sum-of-Square differences registration method. The final output is in the same space as the fixed image. You do require to have CUDA v2.2 or greater installed on your system with atleast 256MB Nvidia GPU memmory card. All operating systems are supported, but take a look at the CMakeLists.txt file for how to compile for you system.
Proper citation: GPU based affine registration (RRID:SCR_009486) Copy
http://www.nitrc.org/projects/multixplore/
Graphical user interface that has been implemented as a 3D Slicer plugin (scripted module). It serves to display a corresponding set of cortical regions from functional connectivity matrix in an explorable 3D scene that represents brain anatomical environment. In addition to grey matter regions, MultiXplore automatically finds and extracts deterministic fiber bundles which exist between selected region(s) and adds them to the 3D environment. This feature helps in generating region-based fiber bundles given a desired whole-brain tractography data.
Proper citation: MultiXplore (RRID:SCR_014814) Copy
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
https://www.slicer.org/slicerWiki/index.php/Slicer4:VMTK
Provides series of modules which enable functions of Vascular Modeling Toolkit in 3D Slicer. Functionality includes vessel enhancement filtering, level set segmentation, centerline computation, network extraction and branch splitting.VMTK is available through the extension manager for 3D Slicer from version 4.6.2. Main difference to Slicer3 version is that now all VMTK modules come as one extension bundle. This should enhance the installation experience for users.
Proper citation: VMTK in 3D Slicer (RRID:SCR_002579) Copy
http://www.nitrc.org/projects/finslertract/
This module implements the Finsler tractography method with HARDI data described by J. Melonakos et al. From a set of seeding and target points, the paths are estimated as the shortest path taking into account a local, directional dependent cost. The output provided is the connectivity map from each voxel in the volume to the seeding points, plus a vector volume with the directions tangent to the fiber bundles at each point. If the Backtracing module within is built, these directions can be traced back to actually compute the fiber bundles (VTK required). The software can be built as either a stand-alone or a CLI plugin for 3D Slicer.
Proper citation: Finsler tractography module for Slicer (RRID:SCR_009477) Copy
http://www.nitrc.org/projects/gambit/
An end-to-end application allowing Group-wise Automatic Mesh-Based analysis of cortIcal Thickness as well as other surface area measurements. This cross-platform tool can be run within 3D Slicer as an external module, or directly as a command line.
Proper citation: GAMBIT (RRID:SCR_009483) Copy
http://www.nitrc.org/projects/lupuslesion/
Slicer3 module to provide a capability for performing white matter lesion classification and summary.
Proper citation: 3DSlicerLupusLesionModule (RRID:SCR_000853) 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.
