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http://www.alivelearn.net/xjview8/

A viewing program for Statistical Parametric Mapping (SPM2, SPM5 and SPM8). p-value slider, displays multiple images at a time and can be used to build Region of Interest (ROI) masks. For a given region you can find the anatomical name and search the selected region in online database (wiki, Google scholar and PubMed).

Proper citation: xjView: A Viewing Program For SPM (RRID:SCR_008642) Copy   

•   Source: SciCrunch Registry

http://humanconnectome.org/

Consortium to comprehensively map long-distance brain connections and their variability. It is acquiring data and developing analysis pipelines for several modalities of neuroimaging data plus behavioral and genetic data from healthy adults.

Proper citation: Human Connectome Coordination Facility (RRID:SCR_008749) Copy   

•   Source: SciCrunch Registry

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

A fast, scalable tool developed at the Johns Hopkins University to automatically segment the major anatomical fiber tracts within the human brain from clinical quality diffusion tensor MR imaging. With an atlas-based Markov Random Field representation, DOTS directly estimates the tract probabilities, bypassing tractography and associated issues. Overlapping and crossing fibers are modeled and DOTS can also handle white matter lesions. DOTS is released as a plug-in for the MIPAV software package and as a module for the JIST pipeline environment. They are therefore cross-platform and compatible with a wide variety of file formats.

Proper citation: DOTS WM tract segmentation (RRID:SCR_009459) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/c8c8/

A small, stand-alone MatLab toolbox that measures sagittal cross-section thickness and area of the human corpus callosum from high-resolution T1 in vivo MR images. C8 takes as input affine normalized white matter segmentations derived from high-resolution (in-plane) T1 images and outputs both regional callosal thicknesses in three different formats and geometrically-defined regional areas in three different configurations. It is a small package that is easily configurable and modifiable and it measures callosa at the rate of several per minute.

Proper citation: C8: Corpus Callosum Computations (RRID:SCR_009449) Copy   

•   Source: SciCrunch Registry

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

Software toolkit developed for the fbrain project that consists of several image processing tools: image reconstruction, image denoising, image segmentation, tractography etc., for a better understanding of fetal brain development.

Proper citation: Baby Brain Toolkit (RRID:SCR_009440) Copy   

•   Source: SciCrunch Registry

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

An efficient framework for building and analyzing graphs called epsilon radial networks (ERNs) using tractography data in a normalized space. Currently there is no agreed-upon method for constructing the brain anatomical connectivity graphs out of large number of white matter tracts. The key challenge in defining brain networks is node delineation and their method defines nodes in the graph using tract-end points clustered in a sphere of a given radius (epsilon). Using a kd-tree based search algorithm they can identify the nodes computationally efficiently and in a fully automatic way. These networks can be used not only to analyze topo-physical properties of the structural brain networks but also to perform classical region-of-interest (ROI) analyses in a very efficient way. Thus ERNs can be used as a novel image processing lens for statistical and machine learning based analyses.

Proper citation: Epsilon Radial Networks (RRID:SCR_009470) Copy   

•   Source: SciCrunch Registry

http://www.3dbar.org

Software package for reconstructing three-dimensional models of brain structures from 2-D delineations using a customizable and reproducible workflow. 3dBAR also works as an on-line service (http://service.3dbar.org) offering a variety of functions for the hosted datasets: * downloading reconstructions of desired brain structures in predefined quality levels in various supported formats as well as created using customizable settings, * previewing models as bitmap thumbnails and (for webGL enabled browsers) interactive manipulation (zooming, rotating, etc.) of the structures, * downloading slides from available datasets as SVG drawings. 3dBAR service can also be used by other websites or applications to enhance their functionality. * Operating System: Linux * Programming Language: Python * Supported Data Format: NIfTI-1, Other Format, VRML

Proper citation: 3DBar (RRID:SCR_008896) Copy   

•   Source: SciCrunch Registry

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

This central project points to all open-source and open-data initiatives provided by the German Cancer Research Center in the field of diffusion MRI.

Proper citation: Diffusion MRI at DKFZ Heidelberg (RRID:SCR_009465) Copy   

•   Source: SciCrunch Registry

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

Software tools appropriate for the registration of diffusion tensor images to an average coordinate system. The tools include image registration methods and algorithms for the correct alignment of the diffusion tensor when applying the resulting transformation. The program uses the Slicer3 execution model framework to define the command line arguments, and can be fully integrated using the module discovery capabilities of Slicer3.

Proper citation: Diffusion Warp (RRID:SCR_009466) Copy   

•   Source: SciCrunch Registry

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

Open-source turnkey software for automatic hippocampus segmentation. Its primary use is for delineating hippocampus in T1-weighted MRI images. AHEAD is developed by Jung W. Suh, Hongzhi Wang, Sandhitsu Das, Brian Avants, Philip Cook, John Pluta and Paul Yushkevich, and colleagues at the Penn Image Computing and Science Laboratory (PICSL) at the University of Pennsylvania.

Proper citation: AHEAD (RRID:SCR_008890) Copy   

•   Source: SciCrunch Registry

http://www.cancerimagingarchive.net/

Archive of medical images of cancer accessible for public download. All images are stored in DICOM file format and organized as Collections, typically patients related by common disease (e.g. lung cancer), image modality (MRI, CT, etc) or research focus. Neuroimaging data sets include clinical outcomes, pathology, and genomics in addition to DICOM images. Submitting Data Proposals are welcomed.

Proper citation: Cancer Imaging Archive (TCIA) (RRID:SCR_008927) Copy   

•   Source: SciCrunch Registry

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

Journals addressing functional and structural neuroimaging topics.

Proper citation: Functional and Structural Neuroimaging Journals Listing (RRID:SCR_009482) Copy   

•   Source: SciCrunch Registry

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

A community for the discussion of functional connectivity and all related topics. This includes discussion of related tools, data sets, methodological discussion, related websites and publications, etc.

Proper citation: Functional Connectivity Community (RRID:SCR_009480) Copy   

•   Source: SciCrunch Registry

http://www.slicer.org/slicerWiki/index.php/Slicer3:Module:Rician_Noise_Removal

Two Slicer3 modules removing rician noise in diffusion tensor MRI

Proper citation: Slicer3 Module Rician noise filter (RRID:SCR_009614) Copy   

•   Source: SciCrunch Registry

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

Geometry format under the Neuroimaging Informatics Technology Initiative (NIfTI). Basically, it is the surface-file format complement to the NIfTI volume-file format .nii. Programs which support the Gifti format, intended to allow exchange of each others surface files, include: Freesurfer, Caret, BrainVISA, Brain Voyager, CRkit, VisTrails and AFNI.

Proper citation: GIFTI (RRID:SCR_009579) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/dave1

Software application that has been designed to facilitate rapid and flexible visualization from neuroanatomically segmented results.

Proper citation: SVV (RRID:SCR_009613) Copy   

•   Source: SciCrunch Registry

http://erpinfo.org/erplab

A set of open source, freely available Matlab routines for analyzing Event Related Potential (ERP) data. It is tightly integrated with the EEGLAB Toolbox. ERPLAB routines can be accessed from the Matlab command window and from Matlab scripts in addition to being accessed from the EEGLAB GUI. Consequently, ERPLAB provides the ease of learning of a GUI-based system but also provides the power and flexibility of a scripted system.The development of ERPLAB Toolbox is being coordinated by Steve Luck and Javier Lopez-Calderon at the UC-Davis Center for Mind & Brain, with financial support from NIMH.

Proper citation: ERPLAB (RRID:SCR_009574) Copy   

•   Source: SciCrunch Registry

http://www.sourcesignal.com/

A technically supported modular platform for space-time-frequency analyses of EEG/MEG/ECoG integrated (optionally) with structural MRI and functional hemodynamic measures (fMRI and NIRS). The Locator module uses Polhemus devices to acquire 3D sensor coordinates. Data Editor provides pipelines of spatial and temporal filters, and easy-to-use event pipelines for conditional binning of time, frequency, and time-frequency data across participants, with group results. Coherence, phase synchronication, and quasi-causal information assess connectivity. Source Estimator enables modeling of discrete overdetermined and distributed underdetermined sources, and spatial filtering for 3D brain regions of interest. Statistical nonparametric mapping (SnPM) may be performed for all measures. MR Viewer and Image Processor comprise tools for BEM and FEM volume conductor models, using cortical source space models. See http://www.sourcesignal.com/Features_EMSE_550.pdf for details and a supported free trial.

Proper citation: EMSE Suite (RRID:SCR_009571) Copy   

•   Source: SciCrunch Registry

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

Software that uses a novel statistical-learning technique to segment brain regions of interest (ROIs) based on a training set of data and generates 3D MRI volumes. The software comes pre-trained on a provided data set but can be retrained to work with your desired regions of interest.

Proper citation: LONI Brain Parser (RRID:SCR_009572) Copy   

•   Source: SciCrunch Registry

http://www.slicer.org/slicerWiki/index.php/Documentation/Nightly/Extensions/DTIProcess

A DTI processing and analysis toolkit developed in UNC and University of Utah. Tools in this toolkit include dtiestim, dtiprocess, dtiaverage, fibertrack, fiberprocess, et al..

Proper citation: DTIProcess ToolKit (RRID:SCR_009561) Copy   

•   Source: SciCrunch Registry