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http://www.nitrc.org/projects/gpu-areg/

This tool can be used as a command line module with 3D Slicer (version 3 and above) for the affine registration of image volumes. The registration toolbox has 2 options: 1) a Mutual Information based registration, 2) a Sum-of-Square differences registration method. The final output is in the same space as the fixed image. You do require to have CUDA v2.2 or greater installed on your system with atleast 256MB Nvidia GPU memmory card. All operating systems are supported, but take a look at the CMakeLists.txt file for how to compile for you system.

Proper citation: GPU based affine registration (RRID:SCR_009486) 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.nitrc.org/projects/fmriclassify/

They demonstrate and provide R code that can classify between groups of fMRI scans based on functional network connectivity differences, requiring only 4 lines of code to be altered. In addition, they include a detailed article explaining the methods behind and motivations of this tool. This code can also be altered to perform connectivity analysis and classification using ROI based methods by reading in distance arrays previously created. They run Independent component analysis (ICA) on fMRI data to establish functional networks, measure the functional connectivity between these networks using the temporal cross-correlations between independent component to create a distance matrix and indicating the networking. Connectivity properties are used as a feature matrix for an SVM classifier. Collectively, this project provides and explains both methods and code to perform functional network connectivity and fMRI SVM classi?cation.

Proper citation: fMRI Classification in R (RRID:SCR_009519) Copy   

•   Source: SciCrunch Registry

http://www.slicer.org/slicerWiki/index.php/Slicer3:Module:Level-Set_Segmentation_Framework-Documentation

The modules in the framework support different tasks in the segmentation realization in 3DSlicer. A module called Level-set label map evolver was developed, which takes an initial label image and a feature image as input and performs a Geodesic Active Contours evolution on the label image according to the feature image and to a different terms in the level-set equation. The evolution takes place for a customizable number of iterations. The output is a label image that can be used to produce a model. Other modules were developed to accompany the main module as can be seen in http://www.slicer.org/slicerWiki/index.php/Slicer3:Module:Level-Set_Segmentation_Framework-Documentation

Proper citation: Level-set Segmentation for Slicer3 (RRID:SCR_009558) Copy   

•   Source: SciCrunch Registry

http://www.rad.upenn.edu/sbia/software/dramms/

A software designed for deformable 2D-to-2D and 3D-to-3D image registration. Some typical applications of DRAMMS include, ** Cross-subject registration of the same organ (can be brain, breast, cardiac, etc); ** Mono- and Multi-modality registration (MRI, CT, histology); Longitudinal registration (pediatric brain growth, cancer development, etc); ** Registration under partial missing correspondences (small lesions, tumors, histological cuts). DRAMMS is implemented as a Unix command-line tool. It is fully automatic and easy to use ? users input two images, and DRAMMS will output the registered image and deformation. No need for pre-segmentation of any structures, no need for any prior knowledge, and no need for human initialization or intervention.

Proper citation: DRAMMS (RRID:SCR_009555) Copy   

•   Source: SciCrunch Registry

http://www.connectomeviewer.org/viewer/

A free, open source, cross-platform Python-based software application for visualization and analysis in connectome research. Features of the software include: Connectome File Format including metadata, networks, surfaces, volumes, track files; complex network analysis toolboxes; modular plugin architecture for extensibility; Mayavi2 for 3D Scientific Visualization and Plotting; interactive data manipulation and scripting capabilities; and Neuroimaging and Diffusion in Python libraries.

Proper citation: Connectome Viewer (RRID:SCR_009552) Copy   

•   Source: SciCrunch Registry

https://www.conn-toolbox.org

Matlab based cross platform software package for computation, display, and analysis of functional connectivity in fMRI (fcMRI). Used for resting state data (rsfMRI) as well as task related designs. Covers pipeline from raw fMRI data to hypothesis testing.

Proper citation: CONN (RRID:SCR_009550) Copy   

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http://cbfbirn.ucsd.edu/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented August 23, 2017.

A web based central repository for individual and group analysis of Arterial Spin Labeling (ASL) data sets and ASL pulse sequences developed at CMFRI UCSD for MRI researchers. This resource currently hosts more 1300 ASL data sets from 22 projects and consists of mainly two main tools 1) The Cerebral Blood Flow Database and Analysis Pipeline (CBFDAP) is a web enabled data and workflow management system extended from the HID codebase on NITRC specialized for Arterial Spin Labeling data management and analysis (including group analysis) in a centralized manner. 2) Pulse Sequence Distribution System (PSDS) for managing dissamination of ASL pulse sequences developed at the UCSD CFMRI. This resource also includes web and video tutorials for end users.

Proper citation: CBFBIRN (RRID:SCR_009543) 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.easyneuroimaging.com/

Blog presenting some scripts that can be used to facilitate and automate processing and analysis of brain data. In addition, it could be helpful explaining non clear stages and steps of brain data processing using some software such as; Freesurfer, FSL, Brainvoyager QX... At the moment, there are more than 10 applescripts in the main website http://www.easyneuroimaging.com that control different tools and commands (aparcstats2table, asegstats2table, BET, dcm2nii, FIRST, fslsplit, fslswapdim, fslview, mri_convert, Qdec, Recon-all, SIENAX, tkmedit, tksurfer)

Proper citation: Neuroimaging Made Easy Blog (RRID:SCR_009611) 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

http://libeep.sourceforge.net/

Software library that deals with reading and writing RIFF-format CNT/AVR-files. This file format is also called EEProbe data format, and is used in the software packages EEProbe, ASA, ASA-Lab, Cognitrace, eemagine EEG, Visor, by ANT Neuro B.V., The Netherlands. The file format provides for storage of EEG/ERP/MEG data as 32-bit values, and includes a very efficient compression algorithm. Encoding/decoding from the compressed data is performed automatically through the LIBEEP interface functions.

Proper citation: LIBEEP (RRID:SCR_009591) Copy   

•   Source: SciCrunch Registry

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

Software toolbox containing many kinds of kits that you may be interested in during fMRI data analysis. This toolbox is a homebrew kits built during practical ASL(arterial spin labeling) based Cerebral Blood Flow (CBF) data analysis. Meanwhile, this toolbox is also compatible with BOLD data analysis. Everyone would find something useful for their own data analysis! This toolbox is run and tested on SPM8 with MATLAB 7.6.0(R2008a) under the Linux OS. Theoretically, most of the functions (except the menu1&2 which are specially designed for the Batch Editor of SPM8) of this toolbox should be compatible with SPM5 and should also work smoothly under the Windows OS. Feel free to give feedback to authors if you encounter any bugs or problems. Senhua Zhu Center for functional Neuroimaging, University of Pennsylvania 3 W.Gates Bldg, 3400, Philadelphia, PA (19104), United States Email: [email protected] ; [email protected] QQ group number (QQ?): 60524357 Google group: https://groups.google.com/d/forum/fmri-grocer

Proper citation: fMRI Grocer (RRID:SCR_009622) Copy   

•   Source: SciCrunch Registry

http://elastix.isi.uu.nl/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on February 23,2023. Software toolbox for rigid and nonrigid registration of images. elastix is open source software, based on the well-known Insight Segmentation and Registration Toolkit (ITK). The software consists of a collection of algorithms that are commonly used to solve (medical) image registration problems. The modular design of elastix allows the user to quickly configure, test, and compare different registration methods for a specific application. A command-line interface enables automated processing of large numbers of data sets, by means of scripting. A paper describing elastix contains more details: S. Klein, M. Staring, K. Murphy, M.A. Viergever, J.P.W. Pluim, elastix: a toolbox for intensity based medical image registration,; IEEE Transactions on Medical Imaging, vol. 29, no. 1, pp. 196 - 205, January 2010., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: elastix (RRID:SCR_009619) Copy   

•   Source: SciCrunch Registry

https://www.nitrc.org/projects/w2mhs/

An open source MATLAB toolbox designed for detecting and quantifying White Matter Hyperintensities(WMH) in Alzheimer?s and aging related neurological disorders.Our toolbox provides a self-sufficient set of tools for segmenting these WMHs reliably and further quantifying their burden for down-processing studies. WMHs arise as bright regions on T2-weighted FLAIR images. They reflect comorbid neural injury or cerebral vascular disease burden. Their precise detection is of interest in Alzheimer?s disease (AD) with regard to its prognosis.

Proper citation: Wisconsin White Matter Hyperintensities Segmentation Toolbox (RRID:SCR_009652) Copy   

•   Source: SciCrunch Registry