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http://www.egi.com/clinical-division/clinical-division-geodesic-eeg-components/clinical-division-net-station

APIs for Net Station data files. APIs are available for C++, C#, and Java.

Proper citation: Net Station API (RRID:SCR_000867) Copy   

•   Source: SciCrunch Registry

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

This matlab script and associated files will take resultant statistical images and essentially output everything you could ever want to know. It can work off of images that were previously corrected for multiple comparisons, but it can actually do the correction itself. This is because the cluster_correct script is incorporated within. It will iterate through atlases (borrowed from other software) to tell you the location of significant results. It outputs an extremely detailed report as well as a summary table for quick investigation. In addition, it will output statistics for each surviving cluster, and the image as a whole. Feedback would be much appreciated.

Proper citation: Cluster reporter (RRID:SCR_002218) Copy   

•   Source: SciCrunch Registry

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

Software for the analysis of multiple diffusion properties along fiber bundle as functions in an infinite dimensional space and their association with a set of covariates of interest, such as age, diagnostic status and gender, in real applications. The resulting analysis pipeline can be used for understanding normal brain development, the neural bases of neuropsychiatric disorders, and the joint effects of environmental and genetic factors on white matter fiber bundles.

Proper citation: Functional Regression Analysis of DTI Tract Statistics (RRID:SCR_002293) Copy   

•   Source: SciCrunch Registry

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

Vervet (Chlorocebus aethiops sabaeus) probabilistic atlas that defines an anatomical space (template) with associated tissue and regional prior probability maps. The atlas was produced from whole head MRI of 10 normal adult animal subjects. The package consists of two atlases. The Biased directory contains the average template and probabilistic atlases for selected tissue classes constructed by registering the training population to one subject. The Unbiased directory contains the atlas constructed using unbiased estimation. The atlas is suitable for use in any segmentation tool using a probabilistic atlas, for example those in Slicer.

Proper citation: Vervet Probabilistic Atlas (RRID:SCR_000426) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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

This script will take any .img file and correct it based on a cluster extent, cluster definition and voxelwise threshold. The threshold entered will be applied to positive and negative values separately, and separate pos and neg corrected images will be output. This script requires a license for the matlab image processing toolbox.

Proper citation: Cluster Extent Correction (RRID:SCR_002226) Copy   

•   Source: SciCrunch Registry

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

A software toolbox that can automatically identify many of the artifact components that are often present in independent component analysis (ICA) of functional MRI (fMRI). The method: * Does not require temporal information about the fMRI paradigm. * Does not require the user to train the algorithm. * Requires only the EPI images (additional acquisition of anatomical images is not required). * Is able to identify a high proportion of artifact-related ICs without removing components that are likely to be of neuronal origin. * Can be applied to resting-state fMRI. * Is automated, requiring minimal or no human intervention.

Proper citation: SOCK (RRID:SCR_002544) Copy   

•   Source: SciCrunch Registry

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

Slicer3 modules for quantitative diffusion analysis. Modules include tools for clustering fiber tracts, summarizing measures over tract clusters, etc.

Proper citation: Quantitative Diffusion Tools (RRID:SCR_002527) Copy   

•   Source: SciCrunch Registry

http://www.bic.mni.mcgill.ca/software/minc/

A medical imaging data format and an associated set of tools and libraries including a 3 level API for medical image analysis with a particular focus on the needs of research. There are also a number of tools including Registration and Non-Uniformity correction.

Proper citation: MINC (RRID:SCR_002391) Copy   

•   Source: SciCrunch Registry

https://www.nitrc.org/projects/threedicsi/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 13,2026. Software program for multi-dimensional CSI data visualization, spectral processing, localization, quantification and multi-variate analysis.

Proper citation: 3D Interactive Chemical Shift Imaging (RRID:SCR_002581) Copy   

•   Source: SciCrunch Registry

http://fmri.wfubmc.edu/cms/software#WFU_Pipeline

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 14, 2026. A fully automated software application for the processing of fMRI data using SPM. It is fully automated from the point of data acquisition at the MRI scanner. It incorporates tools for automated data transfer, archiving, real-time SPM5 batch script generation with distributed grid processing, automated error-recovery procedures, full data-provenance, email notifications, optional conversion back to DICOM (Digital Imaging and Communications in Medicine), and picture archiving and communications systems (PACS) insertion. The architecture allows for an infinite number of easily definable analyses that are fully automated from the point of acquisition. Requirements: * MATLAB 7.3 or greater with the Image Processing Toolbox * SPM5

Proper citation: WFU Pipeline (RRID:SCR_002614) Copy   

•   Source: SciCrunch Registry

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

A command line voxel-wise statistical analysis software program for images. Images can be gray matter density, jacobian images, etc. The linear model is implemented, i.e. designs that can be modeled as Y=AB, where Y is a vector or matrix of dependent variables, B is a vector or matrix of parameters to be estimated, and A is a design matrix. Why use valmap? # Do not need a Matlab license to run. # Can incorporate a spatially varying independent variable (e.g., you have a perfusion map as your dependent variable, and you want to co-vary for gray matter at each voxel, so use a gray matter map as an independent variable). # Can use spatially invariant independent variables (e.g., you can have a cognitive test score as the dependent variable, and use jacobian maps as the independent variable). # Can have multiple dependent variables and do multivariate analyses (e.g., want to know the overall effect of disease on perfusion and structure, so use perfusion maps and jacobian maps as dependent variables).

Proper citation: ValMap: simple statistical mapping tool (RRID:SCR_002610) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

http://www.softpedia.com/get/Science-CAD/MeshValmet.shtml

A tool that measures surface to surface distance between two triangle meshes using user-specified uniform sampling. Thus, users can choose finer sampling level to calculate errors to gain more accuracy in theerror space, or sparser sampling to gain speed and get an approximate feeling of error distribution between boundaries. Besides its pleasant visualization using the VTK library, MeshValmet also provides useful histogram and statistical information based on the sample errors, such as mean and median distance, root mean square distance, mean square distance, mean absolute distance, Hausdorff distance, 95 percentile, 68 percentile, etc. MeshValmet is based on the work of Nicolas Aspert, etc.: MESH: Measuring Errors between Surfaces using the Hausdorff distance in the proceedings of the IEEE Int. Conf. on Multimedia and Expo 2002 (ICME), vol. I, pp. 705-708. The calculation of the Dice's Coefficient is calculated by Joshua Stough using the concept of a Riemannian sum.

Proper citation: MeshValmet: Validation Metric for Meshes (RRID:SCR_006622) Copy   

•   Source: SciCrunch Registry

http://www.bic.mni.mcgill.ca/ServicesAtlases/Macaque

A reference atlas of standard macaque monkey magnetic resonance images. The template brain volume that offers a common stereotaxic reference frame to localize anatomical and functional information in an organized and reliable way for comparison across individual macaque monkeys and studies. We have used MRI volumes from a group of 25 normal adult macaque monkeys (18 Macaca fascicularis, 7 Macaca mulatta) to create the individual atlas. Thus, the atlas does not rely on the anatomy of a single subject, but instead depends on nonlinear normalization of numerous macaque brains mapped to an average template image that is faithful to the location of anatomical structures. Tools for registering a native MRI to the MNI macaque atlas can be found in the Software section. Viewing the atlas and associated volumes online requires Java browser support. Additionally, you may download the atlas and associated files in your chosen format.

Proper citation: McConnell Brain Imaging Center MNI Macaque Atlas (RRID:SCR_005265) Copy   

•   Source: SciCrunch Registry

http://eeg.sourceforge.net/

Software toolbox to facilitate quick and easy import, visualization and measurement for Event Related Potential (ERP) data. The toolbox can open and visualise ERP averaged data (Neuroscan, ascii formats), 2D/3D electrode coordinates and 3D cerebral tissue tesselations (meshes). All the features can be explored quickly and easily using the example data provided in the toolbox. The GUI interface is simple and intuitive.

Proper citation: Bioelectromagnetism Matlab Toolbox (RRID:SCR_006090) Copy   

•   Source: SciCrunch Registry

http://neurosynth.org

Platform for large-scale, automated synthesis of functional magnetic resonance imaging (fMRI) data extracted from published articles. It''s a website wrapped around a set of open-source Python and JavaScript packages. Neurosynth lets you run crude but useful analyses of fMRI data on a very large scale. You can: * Interactively visualize the results of over 3,000 term-based meta-analyses * Select specific locations in the human brain and view associated terms * Browse through the nearly 10,000 studies in the database Their ultimate goal is to enable dynamic real-time analysis, so that you''ll be able to select foci, tables, or entire studies for analysis and run a full-blown meta-analysis without leaving your browser. You''ll also be able to do things like upload entirely new images and obtain probabilistic estimates of the cognitive states most likely to be associated with the image.

Proper citation: NeuroSynth (RRID:SCR_006798) Copy   

•   Source: SciCrunch Registry

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

A native Java-based imaging processing environment similar to the ITK/VTK paradigm. Initially developed as an extension to MIPAV (CIT, NIH, Bethesda, MD), the JIST processing infrastructure provides automated GUI generation for application plug-ins, graphical layout tools, and command line interfaces. This repository maintains the current multi-institutional JIST development tree and is recommended for public use and extension. JIST was originally developed at IACL and MedIC (Johns Hopkins University) and is now also supported by MASI (Vanderbilt University).

Proper citation: JIST: Java Image Science Toolkit (RRID:SCR_008887) Copy   

•   Source: SciCrunch Registry

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

Interactive Matlab toolbox for processing continuous and event-related EEG, MEG and other electrophysiological data incorporating independent component analysis (ICA), time/frequency analysis, artifact rejection, event-related statistics, and several useful modes of visualization of the averaged and single-trial data. First developed on Matlab 5.3 under Linux, EEGLAB runs on Matlab v5 and higher under Linux, Unix, Windows, and Mac OS X (Matlab 7+ recommended). EEGLAB provides an interactive graphic user interface (GUI) allowing users to flexibly and interactively process their high-density EEG and other dynamic brain data using independent component analysis (ICA) and/or time/frequency analysis (TFA), as well as standard averaging methods. EEGLAB also incorporates extensive tutorial and help windows, plus a command history function that eases users'' transition from GUI-based data exploration to building and running batch or custom data analysis scripts. EEGLAB offers a wealth of methods for visualizing and modeling event-related brain dynamics, both at the level of individual EEGLAB ''datasets'' and/or across a collection of datasets brought together in an EEGLAB ''studyset.'' For experienced Matlab users, EEGLAB offers a structured programming environment for storing, accessing, measuring, manipulating and visualizing event-related EEG data. For creative research programmers and methods developers, EEGLAB offers an extensible, open-source platform through which they can share new methods with the world research community by publishing EEGLAB ''plug-in'' functions that appear automatically in the EEGLAB menu of users who download them. For example, novel EEGLAB plug-ins might be built and released to ''pick peaks'' in ERP or time/frequency results, or to perform specialized import/export, data visualization, or inverse source modeling of EEG, MEG, and/or ECOG data. EEGLAB Features * Graphic user interface * Multiformat data importing * High-density data scrolling * Defined EEG data structure * Open source plug-in facility * Interactive plotting functions * Semi-automated artifact removal * ICA & time/frequency transforms * Many advanced plug-in toolboxes * Event & channel location handling * Forward/inverse head/source modeling

Proper citation: EEGLAB (RRID:SCR_007292) Copy   

•   Source: SciCrunch Registry

https://scicrunch.org/scicrunch/data/source/nlx_154697-10/search?q=*&l=

A virtual database currently indexing software and tools from the SciCrunch Registry, Neuroimaging Informatics Tools and Resources Clearinghouse (NITRC), Visiome Platform, Cerebellar Platform, Brain Machine Interface Platform, and Genetic Analysis Software (GAS).

Proper citation: Integrated Software (RRID:SCR_004745) Copy   

•   Source: SciCrunch Registry