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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.chibi.ubc.ca/WhiteText/

Freely available corpus of manually annotated brain region mentions created to facilitate text mining of neuroscience literature. The corpus contains 1,377 abstracts with 18,242 brain region annotations. Interannotator agreement was evaluated for a subset of the documents, and was 90.7% and 96.7% for strict and lenient matching respectively. We observed a large vocabulary of over 6,000 unique brain region terms and 17,000 words. For automatic extraction of brain region mentions we evaluated simple dictionary methods and complex natural language processing techniques. The dictionary methods based on neuroanatomical lexicons recalled 36% of the mentions with 57% precision. The best performance was achieved using a conditional random field (CRF) with a rich feature set. Features were based on morphological, lexical, syntactic and contextual information. The CRF recalled 76% of mentions at 81% precision, by counting partial matches recall and precision increase to 86% and 92% respectively. We suspect a large amount of error is due to coordinating conjunctions, previously unseen words and brain regions of less commonly studied organisms. We found context windows, lemmatization and abbreviation expansion to be the most informative techniques. We encourage you to test new methods and applications of the dataset. Please contact us if you do, we would like to hear about and link to your work. The abstracts are from PubMed/Medline, specifically The Journal of Comparative Neurology.

Proper citation: Automated recognition of brain region mentions in neuroscience literature. (RRID:SCR_002731) Copy   

•   Source: SciCrunch Registry

http://biodev.ece.ucsb.edu/projects/bisquik/wiki

A scalable web-based system for biological image analysis, management and exploration. The Bisque system incorporates many features useful to imaging researchers from image capture to extensible image analysis and querying. At the core, bisque maintains a flexible database of images and experimental metadata. Image analyses can be incorporated into the system and deployed on clusters and desktops. Search and comparison of datasets by image data and content is supported. Novel semantic analyses are integrated into the system allowing high level semantic queries and comparison of image content. New features and testing of Bisque version: 0.5.1, among many others are: # Parallel execution of datasets # Rich interfaces for autogenerated module UI # Abstracted storage system for local, irods, etc.. They are using Mercurial for their source control system. This should be installed before proceeding. Browse source on-line, http://biodev.ece.ucsb.edu/projects/bisquik/browser Bisque Installation, http://biodev.ece.ucsb.edu/projects/bisquik/wiki/InstallationInstructions05 Bisque DOWNLOAD, http://biodev.ece.ucsb.edu/projects/bisquik/wiki/download, THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Bisque (RRID:SCR_005564) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/cs_schizbull08/

This project hosts data for CANDI Share Schizophrenia Bulletin 2008 (reference below) as part of the CANDI Neuroimaging Access Point. This set includes preprocessed MRI images and segmentation results of all 4 diagnostic groups (Healthy Controls, N=29; Schizophrenia Spectrum, N=20; Bipolar Disorder with Psychosis, N=19; and Bipolar Disorder without Psychosis, N=35). Frazier JA, Hodge SM, Breeze JL, Giuliano AJ, Terry JE, Moore CM, Kennedy DN, Lopez-Larson MP, Caviness VS, Seidman LJ, Zablotsky B, Makris N. Diagnostic and sex effects on limbic volumes in early-onset bipolar disorder and schizophrenia. Schizophr Bull. 2008 Jan;34(1):37-46.

Proper citation: CANDI Share: Schizophrenia Bulletin 2008 (RRID:SCR_009451) Copy   

•   Source: SciCrunch Registry

http://www.radiologyresearch.org/HippocampusSegmentation.aspx

This dataset contains T1-weighted MR images of 50 subjects, 40 of whom are patients with temporal lobe epilepsy and 10 are nonepileptic subjects. Hippocampus labels are provided for 25 subjects for training. The users may submit their segmentation outcomes for the remaining 25 testing images to get a table of segmentation metrics.

Proper citation: MRI Dataset for Hippocampus Segmentation (RRID:SCR_009597) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/me-icr/

Data set of an AFNI GroupInCorr session for multi-echo independent component regression (ME-ICR) for a cohort of 52 subjects. This dataset provides a high-quality atlas of seed-based functional connectivity with strong statistical conditioning.

Proper citation: Multi-Echo Independent Component Regression Group-Level Connectivity Dataset (RRID:SCR_009508) Copy   

•   Source: SciCrunch Registry

http://fcon_1000.projects.nitrc.org/indi/pro/nki.html

A phenotypically rich neuroimaging sample, consisting of data obtained from individuals between the ages of 4 and 85 years-old. All individuals included in the sample undergo semi-structured diagnostic psychiatric interviews, and complete a battery of psychiatric, cognitive and behavioral assessments in order to provide comprehensive phenotypic information for the purpose of exploring brain / behavior relationships.

Proper citation: NKI/Rockland Sample (RRID:SCR_009435) Copy   

•   Source: SciCrunch Registry

http://www.umassmed.edu/psychiatry/candi/

A series of structural brain images, as well as their anatomic segmentations, demographic and behavioral data and a set of related morphometric resources (static and dynamic atlases) made avaialble from the Child and Adolescent NeuroDevelopment Initiative (CANDI) at UMass Medical School. Schiz Bull 2008 data is now available on NITRC-IR. Please register for access: http://www.nitrc.org/project/request.php?group_id=377

Proper citation: CANDI Neuroimaging Access Point (RRID:SCR_009542) Copy   

•   Source: SciCrunch Registry

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

Sample data in MINC format and collection of scripts to verify correct installation of minc-toolkit.

Proper citation: minc-toolkit-testsuite (RRID:SCR_014139) Copy   

•   Source: SciCrunch Registry

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

A project which contains data and analysis pipelines for a set of 53 subjects in a cross-sectional Parkinsons disease (PD) study. The dataset contains diffusion-weighted images (DWI) of 27 PD patients and 26 age, sex, and education-matched control subjects. The DWIs were acquired with 120 unique gradient directions, b=1000 and b=2500 s/mm2, and isotropic 2.4 mm3 voxels. The acquisition used a twice-refocused spin echo sequence in order to avoid distortions induced by eddy currents.

Proper citation: High-quality diffusion-weighted imaging of Parkinsons disease (RRID:SCR_014121) Copy   

•   Source: SciCrunch Registry

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

A longitudinal study of late-life depression at Duke University. There are 281 depressed subjects and 154 controls included. An MR scan of each subject was obtained every 2 years for up to 8 years (total of 1093 scans). Clinical assessments occurred more frequently and consists of a battery of psychiatric tests, including several depression-specific tests.

Proper citation: Efficient Longitudinal Upload of Depression in the Elderly (ELUDE) (RRID:SCR_014103) Copy   

•   Source: SciCrunch Registry