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

A tool that implements a graph-based connectivity assessment method. This method uses a multi-directional graph propagation method applied to sampled orientation distribution function (ODF), which can be computed directly from the original diffusion imaging data.

Proper citation: COST (RRID:SCR_014098) Copy   

•   Source: SciCrunch Registry

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

A software package written in OpenCL (Open Computing Language) that can be used for parallel analysis of fMRI data on a large variety of hardware configurations. If BROCCOLI is running on a GPU, it can perform non-linear spatial normalization to a 1 mm brain template in 4-6 s and run a second level permutation test with 10,000 permutations.

Proper citation: BROCCOLI (RRID:SCR_014093) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/afni_3dsvm/

A command-line program and plugin for AFNI built around SVM-Light. It performs support vector machine (SVM) analysis on fMRI data and runs on Unix+X11+Motif systems, including SGI, Solaris, Linux, and Mac OS X.

Proper citation: 3dsvm (RRID:SCR_014083) Copy   

•   Source: SciCrunch Registry

http://www.softpedia.com/get/Science-CAD/BrainCSI.shtml

A tool for analysis of Magnetic Resonance Spectroscopy (MRS) data by registering it to anatomical images. BrainCSI imports LCModel results to calculate absolute metabolite concentrations using tissue water. Corrections to LCModel metabolite concentrations for partial volume of tissues are accomplished by tissue classification of the anatomical images.

Proper citation: BrainCSI (RRID:SCR_013244) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/ntu-dsi-122/

A diffusion spectrum imaging (DSI) template constructed in the standard ICBM-152 space from 122 healthy adults. The template was built through incorporating the macroscopic anatomical information using high-resolution T1-weighted images and the microscopic structural information obtained from DSI datasets, rendering it to achieve a high anatomical matching to the ICBM-152 space. This template can serve as a representative DSI dataset for a healthy adult population. It is released in its original DWI format.

Proper citation: NTU-DSI-122: a DSI template in ICBM-152 space (RRID:SCR_014155) Copy   

•   Source: SciCrunch Registry

http://www.cis.hut.fi/projects/ica/fastica/

General-purpose unsupervised data-analysis tool, most often used for brain imaging data.

Proper citation: FastICA (RRID:SCR_013110) Copy   

•   Source: SciCrunch Registry

https://github.com/NIRALUser/DTIAtlasBuilder

This tool creates an Atlas image as an average of several DTI images that will be registered. The registration will be done in two steps : - Affine Registration with BRAINSFit - Non Linear Registration with GreedyAtlas A final step will apply the transformations to the original DTI images so that the final average can be computed. The main function writes a python script that will be executed to compute the Atlas. By running DTIAtlasBuilder, you will need to fill in informations in a Graphical User Interface, and then compute the Atlas. You can also run the tool in command line without using the GUI. Using the GUI, you will be able to save or load a dataset file or a parameter file. The tool needs these other tools to work, so be sure to have these installed on your computer: - ImageMath - ResampleDTIlogEuclidean - CropDTI - dtiprocess - BRAINSFit - GreedyAtlas - dtiaverage - DTI-Reg - unu - MriWatcher If you download the package, be sure to have the glut library installed.

Proper citation: DTI Atlas Builder (RRID:SCR_013112) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/r2r_prf/

Software tool as a framework for fitting and describing connectivity patterns between regions that is a simple extension from the current population receptive field models in the visual neuroscience literature. The connectivity from each voxel in a designated seed region to a mapping region is modeled as a 3-dimensional Gaussian, providing location parameters and spread parameters. This allows the direct description of the relative mapping from one region to another.

Proper citation: Region to Region (RRID:SCR_016995) Copy   

•   Source: SciCrunch Registry

https://github.com/nipy/heudiconv

Software tool as flexible DICOM converter for organizing brain imaging data into structured directory layouts.

Proper citation: HeuDiConv: a heuristic-centric DICOM converter (RRID:SCR_017427) 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.nitrc.org/projects/meetings/

Project to assist the community in the support of information about upcoming Conferences, Workshops and Meetings. Such support may be documents, news, files, etc. To see a listing of upcoming Events, please use the NITRC Community Events Page at http://www.nitrc.org/incf/event_list.php (and tab at right). To announce an Event, please use the Submit an Event at the NITRC Community Events Page, http://www.incf.org/Events/events/createObject?type_name=Event (and tab at right). Note, INCF account is currently required. All users are encouraged to check this site for upcoming meetings, and promote future meetings here.

Proper citation: NITRC Community Conferences Workshops and Meetings (RRID:SCR_002323) Copy   

•   Source: SciCrunch Registry

https://med.inria.fr/

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   

•   Source: SciCrunch Registry

http://nilearn.github.io

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   

•   Source: SciCrunch Registry

http://www.med.unc.edu/bric/ideagroup/free-softwares/abeat-a-toolbox-for-consistent-analysis-of-longitudinal-adult-brain-mri

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

https://imagej.net/

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   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   

•   Source: SciCrunch Registry