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http://www.nitrc.org/ir/

Data repository for neuroimaging data in DlCOM and NIFTI formats. It allows users to search for and freely download publicly available data sets relating to normal subjects and those with diagnoses such as: schizophrenia, ADHD, autism, and Parkinson's disease.XNAT-based image registry that supports both NIfTI and DICOM images to promote re-use and integration of NIH funded data.

Proper citation: NITRC-IR (RRID:SCR_004162) Copy   

•   Source: SciCrunch Registry

https://nda.nih.gov/

The National Institute of Mental Health Data Archive (NDA) makes available human subjects data collected from hundreds of research projects across many scientific domains. Research data repository for data sharing and collaboration among investigators. Used to accelerate scientific discovery through data sharing across all of mental health and other research communities, data harmonization and reporting of research results. Infrastructure created by National Database for Autism Research (NDAR), Research Domain Criteria Database (RDoCdb), National Database for Clinical Trials related to Mental Illness (NDCT), and NIH Pediatric MRI Repository (PedsMRI).

Proper citation: NIMH Data Archive (RRID:SCR_004434) Copy   

•   Source: SciCrunch Registry

http://neuromorpho.org/index.jsp

Centrally curated inventory of digitally reconstructed neurons associated with peer-reviewed publications that contains some of the most complete axonal arborizations digitally available in the community. Each neuron is represented by a unique identifier, general information (metadata), the original and standardized ASCII files of the digital morphological reconstruction, and a set of morphometric features. It contains contributions from over 100 laboratories worldwide and is continuously updated as new morphological reconstructions are collected, published, and shared. Users may browse by species, brain region, cell type or lab name. Users can also download morphological reconstructions for research and analysis. Deposition and distribution of reconstruction files ultimately prevents data loss. Centralized curation and annotation aims at minimizing the effort required by data owners while ensuring a unified format. It also provides a one-stop entry point for all available reconstructions, thus maximizing data visibility and impact.

Proper citation: NeuroMorpho.Org (RRID:SCR_002145) Copy   

•   Source: SciCrunch Registry

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

Software tool that provides a convenient environment to simulate NMR diffusion in closed pores. It builds on the eigenfunction expansion of the magnetization.

Proper citation: Multiple Correlation Function Tool (RRID:SCR_002321) Copy   

•   Source: SciCrunch Registry

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

A powerful and modular medical image viewer/editor. It should be particularly useful to Undergraduates, Postdocs and Researchers in Medical Imaging to visualize data and to easily make attractive figures (for papers or presentations). It will also in a near future offer a number of advanced algorithms for medical image processing. Look at the video to get an idea ! http://www.benoitscherrer.com/MisterI/videos.html

Proper citation: MisterI (RRID:SCR_002317) Copy   

•   Source: SciCrunch Registry

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

A Matlab-based software library to perform independent component analysis on group white matter skeleton generated by FSL TBSS. The script produces stable estimates of the white matter tract or tract segments that resemble highly correlated variation profiles across a group of subjects.

Proper citation: Microstructural correlation toolbox (RRID:SCR_002316) Copy   

•   Source: SciCrunch Registry

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

Software toolkit that provides the following libraries and functions on linux platform: # Multi-resolution registration of MR images include T1, multimodality, and DTI images. # The registration model is B-spline, and users can custermize their own image similarity measures by writing a plugin function and recompile the program.

Proper citation: MIAS Registration Toolkit (RRID:SCR_002312) Copy   

•   Source: SciCrunch Registry

http://cogpo.org

Ontology used to describe the experimental conditions within cognitive and behavioral experiments, primarily in humans for application and use in the functional neuroimaging community. CogPO has been developed through the integration of the Functional Imaging Biomedical Informatics Research Network (FBIRN) Human Imaging Database (HID) and the BrainMap Database. The design of CogPO concentrates on what can be observed directly: categorization of each paradigm in terms of (1) the stimulus presented to the subjects, (2) the requested instructions, and (3) the returned response.

Proper citation: Cognitive Paradigm Ontology (RRID:SCR_002235) Copy   

•   Source: SciCrunch Registry

http://brainproducts.com/productdetails.php?id=17

Software to manage the daily work of analyzing various neurophysiological data. Features include a history tree, automated analysis, various data format readers, and more.

Proper citation: BrainVision Analyzer (RRID:SCR_002356) Copy   

•   Source: SciCrunch Registry

http://rtimage.sourceforge.net/

Software application to visualize, segment, and quantify three-dimensional images. Multiple datasets may be loaded, displayed, fused, processed, and quantitatively analyzed simultaneously. Data may be imported from any DICOM-compatible three dimensional imaging modality. Regions-of-interest may be defined using a number of manual, semi-automatic, and automated tools to segment three-dimensional pixel volumes. They may also be imported from and exported to DICOM structure sets. This software has been applied to preclinical and clinical computed tomography (CT), positron emission tomography (PET), single photon emission computed tomography (SPECT), magnetic resonance imaging (MRI), and optical imaging data.

Proper citation: RT Image (RRID:SCR_002535) Copy   

•   Source: SciCrunch Registry

http://www.jeiglesias.com

An automatic whole-brain extraction tool for T1-weighted MRI data (commonly known as skull stripping). Whole-brain segmentation is often the first component in neuroimage pipelines and therefore, its robustness is critical for the overall performance of the system. Many methods have been proposed in the literature, but they often: * work well on certain datasets but fail on others. * require case-specific parameter tuning ROBEX aims for robust skull-stripping across datasets with no parameter settings. It fits a triangular mesh, constrained by a shape model, to the probabilistic output of a supervised brain boundary classifier. Because the shape model cannot perfectly accommodate unseen cases, a small free deformation is subsequently allowed. The deformation is optimized using graph cuts.

Proper citation: ROBEX (RRID:SCR_002534) Copy   

•   Source: SciCrunch Registry

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

A stand-alone MATLAB-based toolkit for the rapid and flexible exploration of Region of Interest (ROI) response waveforms and other signals from across large fMRI datasets. An alpha-release is currently available for use with an example dataset and tutorial.

Proper citation: REX (RRID:SCR_002532) Copy   

•   Source: SciCrunch Registry

https://code.google.com/p/niak/

Software library of modules and pipelines for fMRI processing with Octave or Matlab(r) that can run in parallel either locally or in a supercomputing environment. Linux OS and MINC file format are supported. NIAK currently includes a preprocessing, a region growing and a connectome pipelines. NIAK features powerful pipeline management capabilities, including parallel computing, generation of detailed logs and automatic handling of pipeline failures or updates.

Proper citation: NeuroImaging Analysis Kit (NIAK) (RRID:SCR_002497) Copy   

•   Source: SciCrunch Registry

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

The package dti provides methods for structural adaptive smoothing of diffusion weighted data in the context of the diffusion tensor model. Through its edge preserving properties they reduce data noise without compromizing significant structures.

Proper citation: R-package for adaptive DWI analysis (RRID:SCR_002528) Copy   

•   Source: SciCrunch Registry

http://sccn.ucsd.edu/wiki/SIFT

A GUI-enabled EEGLAB plugin for modeling and visualizing dynamical interactions between electrophysiological signals (EEG, ECoG, MEG, etc), preferably after transforming signals into the source domain. The toolbox consists of four modules: (1) Data Preprocessing, (2) Model Fitting and Connectivity Estimation, (3) Statistical Analysis, (4) Visualization, with a fifth Group Analysis module in development. Module 2 currently includes several adaptive multivariate autoregressive modeling (AMVAR) algorithms, including segmentation AMVAR and Kalman filtering. This subsequently allows the user to validate the model and estimate (in the time-frequency domain) a wide range of multivariate Granger-causal and coherence measures published to date. Module 3 includes routines for parametric and non-parametric significance testing. Module 4 contains routines for interactive visualization of dynamical interactions across time, frequency and anatomical source location.

Proper citation: Source Information Flow Toolbox (RRID:SCR_002561) Copy   

•   Source: SciCrunch Registry

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

Segmentation tool that uses image analysis and machine learning techniques (Support Vector Machines). Image intensities from multiple MR acquisition protocols, after coregistration, are used to form a voxel-wise attribute vector which is used to perform the segmentation. Computer algorithms have started to complement expert-readings of MRI as they may improve throughput and consistency, in addition to providing more accurate quantitative measures of lesion type and volume. Computerized segmentation methods can also offer more precise measurements of longitudinal change of a lesion with disease progression or treatment response.

Proper citation: Brain lesion segmentation tool using SVM (RRID:SCR_002583) Copy   

•   Source: SciCrunch Registry

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

A fast and robust software implementation of the popular Nonlocal Means for MRI-Rician denoising. It works by computing the non-local weights based on distances in a features space comprising the local mean value and gradients of the image. It can reach an acceleration factor of 20x over the original implementation, with an improved performance for medium-low SNR images. They use a bias correction step for Rician noise based on the well-known Conventional Approach. This software can be compiled either as a Slicer module or a stand-alone: http://www.nitrc.org/snapshots.php?group_id=518

Proper citation: Fast Nonlocal Means for MRI denoising (RRID:SCR_002586) Copy   

•   Source: SciCrunch Registry

http://tools.robjellis.net/

Simple, menu-driven software toolbox for SPM 5/8 for exploratory data analysis for functional or structural images (.img / .nii) provides the user with several options: # a histogram of all non-zero voxel values in a brain image; # a scatter plot, Q-Q plot, or Bland-Altman plots comparing two images; # a surface plot of all voxel values at a particular axial slice; # easy Region of Interst (ROI)-based extraction of voxel values. Note: the toolbox calls various SPM 5/8 functions. The Q-Q plot function requires the MATLAB stats toolbox.

Proper citation: vis: SPM Visualized Statistics toolbox (RRID:SCR_002619) Copy   

•   Source: SciCrunch Registry

http://sccn.ucsd.edu/wiki/NFT

A MATLAB Toolbox for generating realistic head models from available data (MRI and/or electrode locations), for computing numerical solutions for the forward problem of electromagnetic source imaging and for single dipole source localization. The NFT includes tools for segmenting scalp, skull, cerebrospinal fluid (CSF) and brain tissues from T1-weighted magnetic resonance (MR) images. The Boundary Element Method (BEM) and Finite Element Method (FEM) are used for the numerical solution of the forward problem. When a subject MR image is not available a template head model can be warped to measured electrode locations to obtain an individualized head model. Toolbox functions may be called either from a graphic user interface compatible with EEGLAB or from the MATLAB command line.

Proper citation: NFT (RRID:SCR_002450) Copy   

•   Source: SciCrunch Registry

https://github.com/incf-nidash/XCEDE

Data management software that provides an extensive metadata hierarchy for describing and documenting research and clinical studies. The schema organizes information into five general hierarchical levels: a complete project, studies within a project, subjects involved in the studies, visits for each of the subjects, the full description of the subject's participation during each visit.

Proper citation: XCEDE Schema (RRID:SCR_002571) Copy   

•   Source: SciCrunch Registry