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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://openneu.ro/metasearch

Web application search tool intended to help users find MRI data shared publicly on the Web, particularly from projects organized under the 1000 Functional Connectomes Project (FCP) and International Neuroimaging Data-sharing Initiative (INDI). Users can perform queries visually to select a cohort of participants with brain imaging data based on their demographics and phenotypic information and then link out to imaging measures.

Proper citation: MetaSearch (RRID:SCR_014751) Copy   

•   Source: SciCrunch Registry

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

Data set of manually-guided expert segmentation results along with magnetic resonance brain image data. Its purpose is to encourage the development and evaluation of segmentation methods by providing raw test and image data, human expert segmentation results, and methods for comparing segmentation results. Please see the MediaWiki for more information. This repository is meant to contain standard test image data sets which will permit a standardized mechanism for evaluation of the sensitivity of a given analysis method to signal to noise ratio, contrast to noise ratio, shape complexity, degree of partial volume effect, etc. This capability is felt to be essential to further development in the field since many published algorithms tend to only operate successfully under a narrow range of conditions which may not extend to those experienced under the typical clinical imaging setting. This repository is also meant to describe and discuss methods for the comparison of results.

Proper citation: Internet Brain Segmentation Repository (RRID:SCR_001994) Copy   

•   Source: SciCrunch Registry

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

Public datasets that have been transcoded into multiple formats. This library of valid file format conversions (DICOM->NIFTI, DICOM->PAR/REC, etc.) will provide a reference for tool developers seeking to support multiple sources of data.

Proper citation: Rosetta Bit (RRID:SCR_001906) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

http://fcon_1000.projects.nitrc.org/indi/abide/

Resting state functional magnetic resonance imaging (R-fMRI) datasets from 539 individuals with autism spectrum disorder (ASD) and 573 typical controls. This initiative involved 16 international sites, sharing 20 samples yielding 1112 datasets composed of both MRI data and an extensive array of phenotypic information common across nearly all sites. This effort is expected to facilitate discovery science and comparisons across samples. All datasets are anonymous, with no protected health information included.

Proper citation: ABIDE (RRID:SCR_003612) Copy   

•   Source: SciCrunch Registry

http://www.remedyinformatics.com/

Software to harmonize the data that you have in different Excel files, databases, repositories, biospecimen applications, etc. and maps it to one common registry. Remedy Informatics' platform aggregates data from multiple sources, harmonizes the data via Ontology, and provides data visualization and pattern recognition and querying tools.

Proper citation: Registry Builder Data Harmonization and Aggregation Tool (RRID:SCR_006559) Copy   

•   Source: SciCrunch Registry

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

A free collection of MRI brain images for testing segmentation algorithms. It is available for download to assess the accuracy, reproducibility and sensitivity of MRI segmentation software. It includes data from infants and adults as well as patients with Alzheimer's disease.

Proper citation: Brain Segmentation Testing Protocol (RRID:SCR_009445) Copy   

•   Source: SciCrunch Registry

https://github.com/BRAINSia/BRAINSTools/tree/master/TestData

About 1.2GB of anonymized imaging data of many different file formats used by the BRAINS suite of tools (BRAINSFit, GTRACT, BRAINS, BRAINSTracer... and others) as a common set of anonymized data for nightly regression testing.

Proper citation: BRAINSTestData (RRID:SCR_009517) Copy   

•   Source: SciCrunch Registry

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

A collection of 32-channel data from 14 subjects (7 males, 7 females) acquired using the Neuroscan software. Subjects are performing a go-nogo categorization task and a go-no recognition task on natural photographs presented very briefly (20 ms). Each subject responded to a total of 2500 trials. Data is CZ referenced and is sampled at 1000 Hz (total data size is 4Gb; more details are given later).

Proper citation: EEG human categorization data (RRID:SCR_009468) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/diffusion-data

An open-data initiative for the distributation of common datasets for the evaluation and validation of diffusion MRI processing methods. http://www.dkfz.de/en/medphysrad/projectgroups/dwi/DTI_projects.html#inhalt3

Proper citation: Diffusion MRI - In-vivo and Phantom Data (RRID:SCR_009464) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/l-neuron

A program which creates anatomically realistic virtual neurons using the formalism of the Lyndenmayer systems to implement sets of neuroanatomical rules discovered by several research groups. The program algorithms read in experimental data - in the form of statistical distributions - to generate virtual structures. L-Neuron samples the values of the parameters within these statistical distributions in a stochastic (random) fashion during dendritic growth.

Proper citation: L-Neuron (RRID:SCR_014132) Copy   

•   Source: SciCrunch Registry

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

A lightweight framework for setting up dependency-driven processing pipelines. The tool is essentially a configurable shell script (sh/bash), which can be included in other scripts and primarily provides a small number of utility functions for dependency checking and NFS-safe file locking for cluster processing.

Proper citation: Lightweight Data Pipeline (RRID:SCR_014135) Copy   

•   Source: SciCrunch Registry

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

A collection of software tools developed for medical image synthesis of typically magnetic resonance (MR) brain images. The approaches have been used to create computed tomography (CT) images from MR input. The goal of image synthesis is to recover MR images with a desired optimal contrast for further processing by either registration or segmentation.

Proper citation: Image Synthesis Tools (RRID:SCR_014123) Copy   

•   Source: SciCrunch Registry

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

A Matlab tool for simulating extracellular potential recordings in spiking neural network (SNN) models. VERTEX is designed to facilitate the simulation of extracellular potentials generated by activity in SNNs; in particular, spatially-organised networks containing thousands or hundreds of thousands of neurons. It has a limited scope but has a simpler user interface so that a simulation can be specified simply by setting some parameters and run using a few function calls.

Proper citation: Virtual Electrode Recording Tool for EXtracellular potentials (VERTEX) (RRID:SCR_014178) Copy   

•   Source: SciCrunch Registry

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

Standardizes file formats for the storage of connectivity data. These formats are developed by the Human Connectome Project and other interested parties. Use the MEDIAWIKI entry in the menu on the left for more information about the CIFTI file formats. Access the CIFTI discussion forum using the Forums entry in the menu on the left. Subscribe to the discussion forum and you will be informed about issues involving the CIFTI file formats via email.

Proper citation: CIFTI Connectivity File Format (RRID:SCR_000852) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/dcm2nii/

A tool for converting images from the complicated formats used by scanner manufacturers (DICOM, PAR/REC) to the NIfTI format used by various scientific tools. dcm2nii works for all modalities (CT, MRI, PET, SPECT) and sequence types.

Proper citation: dcm2nii (RRID:SCR_014099) Copy   

•   Source: SciCrunch Registry

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

Structure from motion algorithms repository. Common interface for various sfm algorithms.

Proper citation: SFMProject (RRID:SCR_014166) Copy   

•   Source: SciCrunch Registry

http://www.birncommunity.org/current-users/morphometry-birn/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 4th,2023. Calibration data set of spoiled gradient-recalled echo magnetic resonance imaging data from five healthy volunteers (four males and one female) scanned twice at four sites having 1.5T systems from different vendors (Siemens, GE, Marconi Medical Systems) pooled by the Morphometry Testbed's (MBIRN). Some subjects were also scanned a single time at another site. One subject was only scanned twice at three sites (subject 73213384) and once at another site. For each subject, four Fast Low-Angle Shot (FLASH) scans with flip angles of 3, 5, 20, and 30 degrees were obtained in a single scan session, from which tissue proton density and T1 maps can be derived. These data were acquired to investigate various metrics of within-site and across-site reproducibility. The images have been defaced so that no facial features can be reconstructed from these data. The Morphometry Testbed (MBIRN) of the Biomedical Informatics Research Network (BIRN) focused on pooling and analyzing of neuroimaging data acquired at multiple sites. Specific applications include potential relationships between anatomical differences and specific memory dysfunctions, such as Alzheimer's disease. With the completion of the initial BIRN testbed phase, each of the original BIRN testbeds have now been retired in order to focus on new users in other biomedical domains.

Proper citation: Morphometry BIRN (RRID:SCR_000155) Copy   

•   Source: SciCrunch Registry

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

A reference MINC set of files that currently includes human head images only of standard modalities. The goal is to build a well curated collection of files that demonstrate the capabilities of MINC

Proper citation: MINC Example files (RRID:SCR_000859) Copy   

•   Source: SciCrunch Registry