Are you sure you want to leave this community? Leaving the community will revoke any permissions you have been granted in this community.
SciCrunch Registry is a curated repository of scientific resources, with a focus on biomedical resources, including tools, databases, and core facilities - visit SciCrunch to register your resource.
https://github.com/bheAI/MonkeyCBP_CLI
Software toolbox for connectivity based parcellation of monkey brain. Integrated pipeline realizing tractography based brain parcellation with automatic processing and massive parallel computing. Highly automated process and high throughput performance supported by GPU option makes toolbox ready to be used by research community.
Proper citation: MonkeyCBP (RRID:SCR_017640) Copy
http://www.nitrc.org/projects/reproman/
Software tool to simplify creation and management of computing environments in Neuroimaging.
Proper citation: ReproMan (RRID:SCR_018468) Copy
http://www.sci.utah.edu/cibc-software/scirun.html
A Problem Solving Environment (PSE) for modeling, simulation and visualization of scientific problems. SCIRun now includes the biomedical components formally released as BioPSE, as well as BioMesh3D. BioMesh3D is a free, easy to use program for generating quality meshes for the use in biological simulations. The most recent stable release is version 4.6.
Proper citation: SCIRun (RRID:SCR_002541) Copy
http://www.nitrc.org/projects/rfmri/
The package fmri provides fMRI analysis with R using structural adaptive smoothing methods. They allow smoothing especially at low SNR avoiding the apparent blurring of non-adapative smoothing and thus without reducing the effective spatial resolution.
Proper citation: R-package for adaptive fMRI analysis (RRID:SCR_002530) Copy
Software tool as multi platform medical image processing and visualization software. Functionalities include 2D/3D/4D image visualization, image registration, diffusion MR processing and tractography, filtering.
Proper citation: medInria (RRID:SCR_001462) Copy
http://surfer.nmr.mgh.harvard.edu/fswiki/mri_deface
Tool to remove facial features from an MRI structural image for the purpose of de-identification.
Proper citation: MRI Defacer (RRID:SCR_002424) Copy
A software package to facilitate the use of statistical learning on NeuroImaging data. Namely NiLearn leverages the scikit-learn Python toolbox for multivariate statistics with applications such as predictive modelling, classification, decoding, or connectivity analysis.
Proper citation: NiLearn (RRID:SCR_001362) Copy
http://www.loni.usc.edu/Software/ShapeTools
Software library that is a collection of Java classes that enable Java programmers to model, manipulate and visualize geometric shapes and associated data values. It simplifies the creation of application programs by providing a ready-made set of support routines. * File format readers that implement ShapeIO interface (modeled after Java ImageIO) are automatically used when appropriate. * Storage of additional metadata of arbitrary type (other than shape vertices and interconnections) is enabled by the use of data attributes. * Shapes may contain a set of child shapes allowing for the construction and manipulation of complex hierarchies of shapes. * The various components of a shape are specified as interfaces with specific implementations, making it easy to create specialized implementations of a shape component when different performance characteristics are required.
Proper citation: LONI ShapeTools (RRID:SCR_002697) Copy
A 4D adult brain extraction and analysis toolbox with graphical user interfaces to consistently analyze 4D adult brain MR images. Single-time-point images can also be analyzed. Main functions of the software include image preprocessing, 4D brain extraction, 4D tissue segmentation, 4D brain labeling, ROI analysis. Linux operating system (64 bit) is required. A computer with 8G memory (or more) is recommended for processing many images simultaneously. The graphical user interfaces and overall framework of the software are implemented in MATLAB. The image processing functions are implemented with the combination of C/C++, MATLAB, Perl and Shell languages. Parallelization technologies are used in the software to speed up image processing.
Proper citation: aBEAT (RRID:SCR_002238) Copy
Open source Java based image processing software program designed for scientific multidimensional images. ImageJ has been transformed to ImageJ2 application to improve data engine to be sufficient to analyze modern datasets.
Proper citation: ImageJ (RRID:SCR_003070) Copy
http://cibsr.stanford.edu/tools/human-brain-project/artrepair-software.html
A toolbox for SPM to improve fMRI analysis of high motion pediatric and clinical subjects. The toolbox includes special algorithms for motion adjustment, data repair, and noise filtering, and methods to find outlier subjects in group studies. Visualization tools are included for quality checking the data, including a movie format for viewing all data and all contrast estimates on every voxel of every subject. Methods are included to quantify results into percent signal change. * Operating System: OS Independent * Programming Language: MATLAB * Supported Data Format: ANALYZE, NIfTI-1 * execution requires: SPM
Proper citation: ArtRepair for robust fMRI (RRID:SCR_005990) Copy
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
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
http://www.nitrc.org/projects/dwmri_in_matlab/
An on-line tutorial on how to use MATLAB for Diffusion-Weighted MRI processing. The following subjects are covered in this tutorial: Generation of Synthetic Diffusion-Weighted MRI datasets, Diffusion Tensor (DTI) Estimation from DW-MRI, DTI Visualization as a field of ellipsoids, Higher-order Diffusion Tensor Estimation from DW-MRI, Computing of Tensor Orientation Distribution Functions (Tensor ODF), Computing of Fiber Orientations, Higher-order Diffusion Tensor Image Visualization as fields of spherical functions, Multi-fiber reconstruction etc. The tutorial contains numerous illustrations, figures and Matlab scripts embedded in the text. The reader/user can automatically generate Matlab script for a self-designed DW-MRI experiment by selecting which steps needs to be followed. The code that corresponds to the selected steps is then appropriately merged in the Matlab Script Generator, and the user can easily copy and paste the produced code directly to the Matlab command prompt.
Proper citation: MATLAB Tutorial on Diffusion Tensor MRI (RRID:SCR_009507) Copy
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
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
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
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
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
http://www.nitrc.org/projects/challenges/
Portal for platforms available to conduct and compete in challenges aiming to improve scientific progress. Challenges allow researchers to share their research and problems with other subject matter experts for collaborative progress.
Proper citation: Challenge Competitions Collection (RRID:SCR_015650) Copy
Can't find your Tool?
We recommend that you click next to the search bar to check some helpful tips on searches and refine your search firstly. Alternatively, please register your tool with the SciCrunch Registry by adding a little information to a web form, logging in will enable users to create a provisional RRID, but it not required to submit.
Welcome to the dkNET Resources search. From here you can search through a compilation of resources used by dkNET and see how data is organized within our community.
You are currently on the Community Resources tab looking through categories and sources that dkNET has compiled. You can navigate through those categories from here or change to a different tab to execute your search through. Each tab gives a different perspective on data.
If you have an account on dkNET then you can log in from here to get additional features in dkNET such as Collections, Saved Searches, and managing Resources.
Here is the search term that is being executed, you can type in anything you want to search for. Some tips to help searching:
You can save any searches you perform for quick access to later from here.
We recognized your search term and included synonyms and inferred terms along side your term to help get the data you are looking for.
If you are logged into dkNET you can add data records to your collections to create custom spreadsheets across multiple sources of data.
Here are the sources that were queried against in your search that you can investigate further.
Here are the categories present within dkNET that you can filter your data on
Here are the subcategories present within this category that you can filter your data on
If you have any further questions please check out our FAQs Page to ask questions and see our tutorials. Click this button to view this tutorial again.