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http://free-d.versailles.inra.fr/html/freed.html

Free-D allows the reconstruction of 3D models from image stacks (segmentation, registration, surface reconstruction, 3D rendering). It is designed in the goal of non-linear spatial normalization and averaging of collections of individual 3D models (this module is currently in alpha version only and not included in the distributed version)., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Free-D (RRID:SCR_009578) Copy   

•   Source: SciCrunch Registry

http://musc.edu/cbi/dki

A software tool for post-processing diffusional kurtosis imaging (DKI) datasets. DKE consists of a suite of command-line programs along with a graphical user interface (GUI). DKE is currently supported on 32- and 64-bit Windows platforms. Given a set of diffusion-weighted images acquired following a valid DKI protocol, DKE generates a set of kurtosis (axial, mean, radial) parametric maps. DKE also generates diffusivity (axial, mean, radial) and fractional anisotropy maps using both DKI and diffusion tensor imaging signal models. DKE features include: DICOM and NIfTI format support, interactive (GUI) as well as batch mode (command-line) processing, and rigid-body motion correction. DKE implements the methods described in the following paper: Tabesh A, Jensen JH, Ardekani BA, and Helpern JA. Estimation of tensors and tensor-derived measures in diffusional kurtosis imaging. Mag Reson Med. 2011 Mar;65(3):823-36. http://www.ncbi.nlm.nih.gov/pubmed/21337412

Proper citation: Diffusional Kurtosis Estimator (RRID:SCR_009563) Copy   

•   Source: SciCrunch Registry

http://neurospaces.sourceforge.net/

The GEneral NEural SImulation System (GENESIS) started as a very advanced software package in the late eighties, for biologically accurate neuronal modeling. Besides being used as a neuronal simulator, it was also applied to various domains outside computational neuroscience. The Neurospaces project is a departure from the monolithic software system design of the original GENESIS system. It is a development center for software components of computational neuroscience simulators. There are many advantages of developing independent software components: - Interfacing to an individual component is obviously more simple than interfacing to a do-all monolithic system. The compartmental solver developed for the Neurospaces project can be connected to Matlab fi. - It simplifies the individual components and encourages other developers to get involved. - It allows for separate testing of the components. More than 1000 use case tests been defined for these software components, including integration tests. - Integrating different component, gives different flavours of the same simulator, and enhances the user experienced consistency when doing multilevel simulations. - A component based software system avoids vendor-lockin. Its life-cycle is more smooth than that of a monolithic system, because software components can be upgraded one at a time. The Neurospaces project embodies many software components that all have been developed in full isolation. The core of the most important components is finished. The current development focus has shifted from component integration to the support of specific use case with an emphasis on single neuron modeling. This is a list of software components that have been developed or are under construction. Together, these tools give the core for the upcoming GENESIS 3 GUI. - GShell: a simple replacement for the Genesis 2 SLI. - Heccer: a fast compartmental solver, a backend. - Dash: a second compartmental solver faster than Heccer, for simpler models. - Neurospaces Model Container: provides a solver independent internal and external storage format for models. - Discrete event system: consists of a discrete event distributor and queuer. This is used for abstract modeling of an action potential traveling inside an axon as a ''discrete event''. - SSP: a flexible scheduler written in perl, to run simulations with the Neurospaces model container and Heccer. - The Neurospaces Studio: some tools for graphical browsing and command line usage. - The Genesis Script Language Interface: a scripting component that reads Genesis 2 scripts and feeds them to the Neurospaces model container. - The Geometry Library is a general purpose geometry library, with some essential geometrical operators, not commonly found in other geometrical libraries. - Using the Geometry Library, a Reconstruct Interface has been written. This interface supports the conversion of contours exported by the Reconstruct software to the Neurospaces declarative NDF format. - The Neurospaces project browser for browsing projects and inspecting simulation results. - The Installer package contains the Neurospaces installer and developer tools that have emerged from developing Neurospaces software components. - The Configurator package contains configuration utilities for the other tools. It is not needed for the other tools to work properly. Rather, it allows to set up model database and simulation servers in a convenient way. - There is also a Neurospaces blog and a wiki at googlecode for the Neurospaces project, with information for developers.

Proper citation: GEneral NEural SImulation System: The Neurospaces Project (RRID:SCR_008035) Copy   

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

A diffusion MRI service that handles the processing of diffusion data from raw data to structural connectivity. They provide high angular resolution (HARDI) reconstruction from DTI data with at least 20 gradient directions acquisitions.

Proper citation: Imeka Tractography Service (RRID:SCR_014124) Copy   

•   Source: SciCrunch Registry

https://github.com/BRAINSia/BRAINSTools

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 23,2023. A suite of tools to generate the cortical surface of the brain. The surface is generated in the middle of grey matter and can be used to measure surface features including cortical depth and curvature.

Proper citation: BRAINSCortex (RRID:SCR_001082) Copy   

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http://www.montefiore.ulg.ac.be/~phillips/FASST.html

An EEG toolbox developed to help users with 3 specific types of data and problems: simulatenous EEG-fMRI recording, continuous EEG scoring (e.g. sleep) and handling (visualisation, cutting, power spectrum, etc.) multi-channel recording of spontaneous EEG. The toolbox is written in Matlab and is specifically compatible with the BrainAmp family of EEG recorders (from BrainProducts GmbH) Three other data formats are now also supported: the edf "European Data Format", exported raw-EGI data (from Electrical Geodesics, Inc.) and the BCI2000 format.The results are directly compatible with SPM8 and are saved with SPM8 EEG data format.

Proper citation: fMRI Artefact rejection and Sleep Scoring Toolbox (RRID:SCR_009620) Copy   

•   Source: SciCrunch Registry

http://www.pymvpa.org

A Python package intended to ease statistical learning analyses of large datasets. It offers an extensible framework with a high-level interface to a broad range of algorithms for classification, regression, feature selection, data import and export. While it is not limited to the neuroimaging domain, it is eminently suited for such datasets. PyMVPA is truly free software (in every respect) and additionally requires nothing but free-software to run. Decoding patterns of neural activity onto cognitive states is one of the central goals of functional brain imaging. Standard univariate fMRI analysis methods, which correlate cognitive and perceptual function with the blood oxygenation-level dependent (BOLD) signal, have proven successful in identifying anatomical regions based on signal increases during cognitive and perceptual tasks. Recently, researchers have begun to explore new multivariate techniques that have proven to be more flexible, more reliable, and more sensitive than standard univariate analysis. Drawing on the field of statistical learning theory, these new classifier-based analysis techniques possess explanatory power that could provide new insights into the functional properties of the brain. However, unlike the wealth of software packages for univariate analyses, there are few packages that facilitate multivariate pattern classification analyses of fMRI data. This Python-based, cross-platform, open-source software toolbox software toolbox for the application of classifier-based analysis techniques to fMRI datasets makes use of Python's ability to access libraries written in a large variety of programming languages and computing environments to interface with the wealth of existing machine learning packages.

Proper citation: PyMVPA (RRID:SCR_006099) Copy   

•   Source: SciCrunch Registry

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

A Matlab-based tool for computational neuroscience-based analysis and data visualization. Its features include: surface mesh visualization in PLY, PIAL, NV, STL,VTK, and GIFTI formats; conversion of NIfTI voxel images to surface meshes and saving as PLY or VTK; track (TRK files) visualization; connectome data (BrainNet Viewer .node and .edge files) visualization; intuitive GUI; that availability of all functions available in the GUI through scripting (automated scripts can be created); and exporting of rendered image as bitmap.

Proper citation: MRIcroS (RRID:SCR_014142) Copy   

•   Source: SciCrunch Registry

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

A statistical analysis tool for manifold-valued data. The SPD manifold for diffusion tensor images (DTI) and the Hilbert unit sphere for square root representation of orientation distribution functions (ODF) can be used.

Proper citation: Multivariate General Linear Models (MGLM) on Riemannian Manifolds (RRID:SCR_014143) Copy   

•   Source: SciCrunch Registry

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

Software Matlab toolbox for directed functional connectivity analysis of fMRI BOLD signal from predefined regions of interest. It recovers true structure of connections and estimates weights attributed to each connection. Obtains patterns at group and individual levels.

Proper citation: GIMME (RRID:SCR_014115) Copy   

•   Source: SciCrunch Registry

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

A set of many useful automation scripts to facilitate the neuroimaging data analysis process. It contains BASH scripts for MRI data management, FSL automation and web application.

Proper citation: XFSL: An FSL toolbox (RRID:SCR_014181) Copy   

•   Source: SciCrunch Registry

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

The Longitudinal MS Lesion Imaging Archive provides Training data consisting of longitudinal images from five patients and Testing data consisting of 15 patients. Each longitudinal dataset includes T1-weighted, T2-weighted, PD-weighted, and T2-weighted FLAIR MRI with 3-5 time points acquired on a 3T MR scanner. T1-weighted images have approximately a 1mm cubic voxel resolution, while the other scans are 1mm in plane with 3mm sections. Accounting for the multiple time points, this constitutes approximately 80 individual data sets. The Training data contains manual segmentations of the MS lesions from two different raters for each of the time points provided.

Proper citation: Longitudinal MS Lesion Imaging Archive (RRID:SCR_014136) Copy   

•   Source: SciCrunch Registry

http://www.hitachi-medical.co.jp/english/

An instrumental supplier which provides researchers and clinicians with sophisticated All-in-One solutions in the field of neuroscience.

Proper citation: Hitachi Optical Topography System (RRID:SCR_000865) Copy   

•   Source: SciCrunch Registry

http://www.nmr.mgh.harvard.edu/CFNT/index

Biomedical technology research center that develops and applies innovative neuroimaging technologies and techniques to enable closer examination of the human brain, and thereby contribute to better understanding of the brain in health and disease. They develop new techniques and advance existing technologies for acquisition and analysis of functionally specific images of the working brain, with unprecedented physiological precision and spatiotemporal resolution. The research and development aims to improve and extend existing methods for non-invasive magnetic resonance image analysis and acquisition, electromagnetic source imaging, optical neuroimaging, and most recently, combined MR-PET neuroimaging. The Resource provides an essential interactive environment, within which an interdisciplinary team of highly skilled scientists, engineers, and clinicians with diverse expertise in multiple modalities and disciplines. The resource supports service use of the Center's facilities by neuroscientists throughout the country, provide extensive training opportunities for students, fellows, and staff scientists, and seek to advance the field of brain mapping through active dissemination of new knowledge and technology.

Proper citation: Center for Functional Neuroimaging Technologies (RRID:SCR_001423) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/maps4mipav/

The exploratory development tree of Java Image Science Toolkit (JIST), an extension to the MIPAV (Medical Image Processing, Analysis, and Visualization) plug-in framework that allows the user to design and execute pipelines, which are multi-stage processing tasks.. New features and designs are tested here before general release into the JIST project. JIST was formerly known as the MedIC Automated Pipeline Scheduler (MAPS).

Proper citation: Maps4Mipav (Exploratory JIST) (RRID:SCR_000613) Copy   

•   Source: SciCrunch Registry

http://www.nirx.net

Commercial technology solutions for NIRS neuroscience imaging applications.

Proper citation: NIRx NIRS Neuroimaging (RRID:SCR_002491) 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/fp_cit_atlas

The FP-CIT SPECT brain template has been created using a fully automatic procedure involving posterization of the source image to three levels: background, brain and striatum. We performed a spatial affine registration of these 40 posterized source images to a posterized reference image in the MNI space. The intensity values of the transformed images is normalized linearly, assuming that the histogram of the intensity values follows an alpha-stable distribution. Lastly, we built the [123I]FP-CIT SPECT template by the mean of the transformed and normalized images. More info: 1) Salas-Gonzalez et al. Building a FP-CIT SPECT brain template using a posterization approach. Accepted in Neuroinformatics. 2) Salas-Gonzalez et al. Linear intensity normalization of FP-CIT SPECT brain images using the alpha-stable distribution. NeuroImage, Volume 65, 2013, pp. 449-455. http://dx.doi.org/10.1016/j.neuroimage.2...

Proper citation: FP-CIT SPECT brain template in MNI space (RRID:SCR_013668) Copy   

•   Source: SciCrunch Registry

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

A filter which allows the Laplace-Beltrami operator to determine surface harmonics in terms of PointData at each vertex. It determines the requested N most significant harmonics of a surface.

Proper citation: Laplace Beltrami Filter on QuadEdge Meshes (RRID:SCR_014133) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/mrml-paraview/

ITK-based processing and 3D Slicer scene management in ParaView. It is meant to broaden the use of ParaView for high performance computing and visualization in the medical imaging research community. The effort is focused on developing ParaView plug-ins for managing VTK structures from 3D Slicer MRML scenes and encapsulating ITK filters for deployment in ParaView.

Proper citation: KWScene: MRML-based Atlas and Scene Builder/Reader/Writer (RRID:SCR_014131) Copy   

•   Source: SciCrunch Registry