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

Expertly collected, well-curated data sets consisting of comprehensive clinical characterization and raw structural, functional and diffusion-weighted DICOM images in schizophrenia patients and gender and age-matched controls are now accessible to the scientific community through an on-line data repository (coins.mrn.org). This data repository will be useful to 1) educators in the fields of neuroimaging, medical image analysis and medical imaging informatics who need exemplar data sets for courses and workshops; 2) computer scientists and software algorithm developers for testing and validating novel registration, segmentation, and other analysis software; and 3) scientists who can study schizophrenia by further analysis of this cohort and/or by pooling with other data.

Proper citation: MCIC (RRID:SCR_002310) Copy   

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http://www.loni.usc.edu/

Biomedical technology resource center specializing in novel approaches and tools for neuroimaging. It develops novel strategies to investigate brain structure and function in their full multidimensional complexity. There is a rapidly growing need for brain models comprehensive enough to represent brain structure and function as they change across time in large populations, in different disease states, across imaging modalities, across age and sex, and even across species. International networks of collaborators are provided with a diverse array of tools to create, analyze, visualize, and interact with models of the brain. A major focus of these collaborations is to develop four-dimensional brain models that track and analyze complex patterns of dynamically changing brain structure in development and disease, expanding investigations of brain structure-function relations to four dimensions.

Proper citation: Laboratory of Neuro Imaging (RRID:SCR_001922) Copy   

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

An on-demand, cloud based computational virtual machine pre-installed with popular NITRC neuroimaging tools built using NeuroDebian. For a listing of current NITRC-CE packages visit: http://www.nitrc.org/ce-packages. You can also use the "public Amazon Machine Interface (AMI)" to conduct your analyses on the Amazon EC2 platform.

Proper citation: NITRC Computational Environment (RRID:SCR_002171) Copy   

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

This project is meant for planning the NITRC Grantee meetings. A website for organizing meetings for the Neuroimaging Informatics Tools and Resources Clearinghouse, to facilitate participants meeting one another, and promote discussion of common interests and collaboration.

Proper citation: Grantees Meeting for NITRC (RRID:SCR_000419) Copy   

•   Source: SciCrunch Registry

http://neuromorphometrics.com/?page_id=23

Collection of neuroanatomically labeled MRI brain scans, created by neuroanatomical experts. Regions of interest include the sub-cortical structures (thalamus, caudate, putamen, hippocampus, etc), along with ventricles, brain stem, cerebellum, and gray and white matter and sub-divided cortex into parcellation units that are defined by gyral and sulcal landmarks.

Proper citation: Manually Labeled MRI Brain Scan Database (RRID:SCR_009604) Copy   

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http://pingstudy.ucsd.edu/

A large multi-site pediatric MRI and genetics data resource to facilitate studies of the genomic landscape of the developing human brain. It includes information about the developing mental and emotional functions of the children to understand the genetic basis of individual differences in brain structure and connectivity, cognition, and personality. Investigators on the project are studying 1400 children between the ages of 3 and 20 years so that links between genetic variation and developing patterns of brain connectivity can be examined. Investigators interested in the effects of a particular gene will be able to search the database for any brain areas or connections between areas that differ as a function of variation in a particular gene, and also to determine if the genes appear to affect the course of brain development at some point during childhood. A data exploration tool has been created for mapping and analyzing MRI data sets collected for PING and related developmental studies. Approved investigators will be able to view raw image sets and derived 3D brain maps of MRI and DTI data, conduct hypothesis testing, and graph brain area measures as they change across the time course of development. PING Cores * Coordinating Core: Functions include project management, screening of participants and maintaining the database * Neuroimaging Core: applying a standardized high-resolution structural MRI protocol involving 3-D T1-weighted scans, a T2-weighted volume, and a set of diffusion-weighted scans with multiple b values and diffusion directions, scans to estimate MRI relaxation rates, and gradient echo EPI scans for resting state fMRI. Importantly, adaptive motion compensation, using ����??PROMO����??, a novel real-time motion correction algorithm will be used. Specific PING protocols for each scanner manufacturer: ** PING MRI Protocol - GE ** PING MRI Protocol - Philips ** PING MRI Protocol - Siemens * Assessment Core: Cognitive assessments for the PING project are conducted using the NIH Toolbox for Cognition. * Genomics Core: functions as a central repository for receipt of saliva samples collected for each study participant. Once received, samples are catalogued, maintained, and DNA is extracted using state-of-the-field laboratory techniques. Ultimately, genome-wide genotyping is performed on the extracted DNA using the Illumina Human660W-Quad BeadChip. PING involves 10 sites throughout the country including UCSD, University of Hawaii, Scripps Genomics, UCLA, UC Davis, Kennedy Krieger Institute/Johns Hopkins, Sacker Institute/Cornell University, University of Massachusetts, Massachusetts General Hospital/Harvard, and Yale. Families who may want to participate in the study, or others who want to know more about it, may email questions to ping (at) ucsd.edu.

Proper citation: Pediatric Imaging Neurocognition and Genetics (RRID:SCR_008953) Copy   

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

An effort to provide a set of quasi-probabilistic atlases for established functional ROIs in the human neuroimaging literature. Many atlases exist for various anatomical parcellation schemes, such as the Brodmann areas, the structural atlases, tissue segmentation atlases, etc. To date, however, there is no atlas for so-called functional ROIs. Such fROIs are typically associated with an anatomical label of some kind (e.g. the _fusiform_ face area), but these labels are only approximate and can be misleading inasmuch as fROIs are not constrained by anatomical landmarks, whether cytoarchitectonic or based on sulcal and gyral landmarks. The goal of this project is to provide quasi-probabilistic atlases for fROIs that are based on published coordinates in the neuroimaging literature. This is an open-ended enterprise and the atlas can grow as needed. Members of the neuroscience and neuroimaging community interested in contributing to the project are encouraged to do so.

Proper citation: Functional ROI Atlas (RRID:SCR_009481) Copy   

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

This atlas takes advantage of ultra-high resolution 7T MRI to provide unprecedented levels of detail on structures of the basal ganglia in-vivo. The atlas includes probability maps of the Subthalamic Nucleus (STh) using T2*-imaging. For now it has been created on 13 young healthy participants with a mean age of 24.38 (range: 22-28, SD: 2.36). We recently also created atlas STh probability maps from 8 middle-aged participants with a mean age of 50.67 (range: 40-59, SD: 6.63), and 9 elderly participants with a mean age of 72.33 (range: 67-77, SD: 2.87). You can find more details about the creation of these maps in the following papers: Young: http://www.ncbi.nlm.nih.gov/pubmed/22227131 Middle-aged & Elderly: http://www.ncbi.nlm.nih.gov/pubmed/23486960 Participating institutions are the Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany, and the Cognitive Science Center Amsterdam, University of Amsterdam, the Netherlands.

Proper citation: Atlasing of the basal ganglia (RRID:SCR_009431) Copy   

•   Source: SciCrunch Registry

http://fcon_1000.projects.nitrc.org/indi/retro/cobre.html

Data set of raw anatomical and functional MR data from 72 patients with Schizophrenia and 75 healthy controls (ages ranging from 18 to 65 in each group). All subjects were screened and excluded if they had: history of neurological disorder, history of mental retardation, history of severe head trauma with more than 5 minutes loss of consciousness, history of substance abuse or dependence within the last 12 months. Diagnostic information was collected using the Structured Clinical Interview used for DSM Disorders (SCID). A multi-echo MPRAGE (MEMPR) sequence was used with the following parameters: TR/TE/TI = 2530/(1.64, 3.5, 5.36, 7.22, 9.08)/900 ms, flip angle = 7��, FOV = 256x256 mm, Slab thickness = 176 mm, Matrix = 256x256x176, Voxel size =1x1x1 mm, Number of echos = 5, Pixel bandwidth =650 Hz, Total scan time = 6 min. With 5 echoes, the TR, TI and time to encode partitions for the MEMPR are similar to that of a conventional MPRAGE, resulting in similar GM/WM/CSF contrast. Rest data was collected with single-shot full k-space echo-planar imaging (EPI) with ramp sampling correction using the intercomissural line (AC-PC) as a reference (TR: 2 s, TE: 29 ms, matrix size: 64x64, 32 slices, voxel size: 3x3x4 mm3). Slice Acquisition Order: Rest scan - collected in the Axial plane - series ascending - multi slice mode - interleaved MPRAGE - collected in the Sag plane - series interleaved - multi slice mode - single shot The following data are released for every participant: * Resting fMRI * Anatomical MRI * Phenotypic data for every participant including: gender, age, handedness and diagnostic information.

Proper citation: COBRE (RRID:SCR_010482) Copy   

•   Source: SciCrunch Registry

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

Behavioral and imaging data from about 120 participants aged 18-89. Data were collected as part of a grant to use high-resolution imaging and advanced behavioral tasks to understand how aging affects the hippocampus and how this is related to age-related cognitive decline. The full dataset includes traditional neuropsycholgical measures, hippocampal-specific behavioral measures, whole-brain DTI, high-resolution DTI of the medial temporal lobes, and structural MRI including segmentation of grey/white/CSF, of cortical regions and of hippocampal subfields.

Proper citation: Stark Cross-Sectional Aging (RRID:SCR_014171) Copy   

•   Source: SciCrunch Registry

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

A pure JavaScript medical research image viewer, compatible across a range of popular web browsers. The orthogonal viewer supports NIFTI and DICOM files, overlays and atlas labels. It requires Firefox (7+), Chrome (7+), Safari (6+), MobileSafari (iOS 6+), or IE (10+).

Proper citation: Papaya (RRID:SCR_014188) Copy   

•   Source: SciCrunch Registry

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

A Matlab implementation for efficient permutation testing by using matrix completion.

Proper citation: Efficient Permutation Testing (RRID:SCR_014104) Copy   

•   Source: SciCrunch Registry

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

A dataset which contains diffusion tensor images of 93 healthy, young male subjects.

Proper citation: YMDTI: Diffusion Tensor Images of Healthy Young Males (RRID:SCR_014183) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/hfh_t1_hp_seg1/

Shared dataset which consists of skull-stripped T1 MRI images and segmented hippocampi of 163 Temporal Lobe Epilepsy (TLE) patients. The T1 and hippocampal segmentation data of TLE patients are uploaded in three separate datasets which can be accessed from the main site.

Proper citation: Epilepsy T1 and Hippocampal Segmentation Datasets (RRID:SCR_014926) Copy   

•   Source: SciCrunch Registry

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

So far there is a lack for Random Field Theory (RFT) -based multiple comparison correction for surfaces generated in Freesurfer software package. This set of Matlab-based functions can be used for that purpose. They are based on Worsley?s SurfStat toolbox. You also need to have installed Freesurfer software package and included the Freesurfer?s matlab subdirectory in the Matlab?s search path. In addition, this tool implements the RFT-FDR hierarchical correction that can be used for optimizing the amount of smoothing in cortical thickness analyses (Neuroimage 52, 158-171).

Proper citation: RFT FDR (RRID:SCR_002533) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/nirx2nirs/

A matlab script which takes near-infrared spectroscopy data recorded by NIRx system(s) and converts it to a .nirs file format for use with the HOMER2 NIRS processing pacakge.

Proper citation: NIRx2nirs: A NIRx to .nirs data converter (RRID:SCR_002492) Copy   

•   Source: SciCrunch Registry

http://www.mbfbioscience.com/stereo-investigator

Stereo Investigator system includes microscope, computer, and Stereo Investigator software. Software works with Brightfield, Multi-Channel Fluorescence, Confocal, and Structured Illumination Microscopes. System used to provide estimates of number, length, area, and volume of cells or biological structures in tissue specimen in areas of neuroscience including neurodegenerative diseases, neuropathy, memory, and behavior, pulmonary research, spinal cord research, and toxicology.

Proper citation: MBF BioScience: Stereo Investigator (RRID:SCR_002526) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/slicer3examples/

Example Slicer3 plugins that can be built against a Slicer3 build or a Slicer3 installation. Note: these are for 3D Slicer version 3. There is now a version 4 of 3D Slicer available. Information about extensions for version 4 can be found at the following links: http://www.slicer.org/slicerWiki/index.php/Documentation/Nightly/SlicerApplication/ExtensionsManager http://www.slicer.org/slicerWiki/index.php/Documentation/Nightly/Developers/Tutorials/BuildTestPackageDistributeExtensions

Proper citation: Slicer3 Example Modules (RRID:SCR_002559) Copy   

•   Source: SciCrunch Registry

http://imaging.indyrad.iupui.edu/projects/SPHARM/

A matlab-based 3D shape modeling and analysis toolkit, and is designed to aid statistical shape analysis for identifying morphometric changes in 3D structures of interest related to different conditions. SPHARM-MAT is implemented based on a powerful 3D Fourier surface representation method called SPHARM, which creates parametric surface models using spherical harmonics.

Proper citation: SPHARM-MAT (RRID:SCR_002545) Copy   

•   Source: SciCrunch Registry

https://sites.google.com/a/brain.org.au/ctp/

Software package with functions that will help researchers plan how many subjects per group need to be included in an MRI-based cortical thickness study to ensure a thickness difference is detected. The package requires cortical thickness mapping and co-registration to be carried out using Freesurfer. The power analyses are implemented in the R software package., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: cortex (RRID:SCR_002467) Copy   

•   Source: SciCrunch Registry