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

A variety of MEG- and fMRI-compatible hardware for research use including typical response collection devices such as joysticks, response pads, mice, as well as stimulation devices such as vibrotactile stimulators, olfactometers, and pressure/force generators. The company also offers custom design and production services for many different applications.

Proper citation: Mag Design and Engineering (RRID:SCR_009600) Copy   

•   Source: SciCrunch Registry

http://www.distributome.org/

An open-source, open content-development project for exploring, discovering, navigating, learning, and computational utilization of diverse probability distributions.

Proper citation: Distributome (RRID:SCR_009564) 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://www.nitrc.org/projects/probbiascor/

A multichannel capable tool for probabilistic inhomogeneity correction implemented as both a standalone command line tool and a Slicer3 module.

Proper citation: ProbabilisticBiasCorrection (RRID:SCR_009638) Copy   

•   Source: SciCrunch Registry

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

Computer program that provides a graphical user interface for fMRI researchers to easily and efficiently design their blocked experiments. The computer program POBE calculates the optimal number of subjects and the optimal scanning time for user specified experimental factors and model parameters so that the statistical efficiency is maximised for a given study budget. POBE can also be used to determine the minimum budget for a given power. Furthermore, a maximin design can be determined as efficient design for a possible range of values for the unknown model parameters.

Proper citation: Program for optimal design of blocked fMRI experiments (RRID:SCR_009639) Copy   

•   Source: SciCrunch Registry

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

Script which points browser to Nathan Kline Institute (NKI) Rockland Sample.

Proper citation: Rockland Download Link Script (RRID:SCR_009513) Copy   

•   Source: SciCrunch Registry

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

While the traditional temporally concatenated Group ICA (TC-GICA) adopting three steps of PCA reduction, it could result in inconsistent and variable components when different subject orders were used, both for the group- and individual-level results. Such instability can further cause instable and thus unreliable statistical results. Subject Order-Independent Group ICA (SOI-GICA) aims to fix this problem by producing stable and reliable GICA results. For details please see the paper Subject Order-Independent Group ICA (SOI-GICA) for Functional MRI Data Analysis (Zhang et al., 2010, NeuroImage)(http://dx.doi.org/10.1016/j.neuroimage.2010.03.039). MICA is the toolbox inplemented SOI-GICA for convenience of usage.

Proper citation: Subject Order-Independent Group ICA (RRID:SCR_009514) Copy   

•   Source: SciCrunch Registry

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

A self-contained virtual machine that can be executed on a common laptop or desktop, enabling the Pipeline to run virtually anywhere. Neophytes to the Pipeline can have their own private server running in minutes, software engineers and workflow designers can use the PNVE as a sandbox, and those without access to grid computing facilities can now take full advantage of the Pipeline processing environment.

Proper citation: Pipeline Neuroimaging VirtualEnvironment (RRID:SCR_009635) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/brainnet_2013/

Tool that associates localized white matter (WM) lesions with disruptions in gray matter connectivity as a step toward understanding the lesions? functional implications. A Tractogram Reference Set (TRS), i.e. collections of white matter fibers, is constructed from 73 normal healthy individuals and coregistered to a common space (MNI). The NeMo Tool uses the TRS to assess structural network disruption due to a particular WM lesion mask on a region and network-wise level. This tool is an easy way for researchers and clinicians to investigate changes in the structural brain network without having to perform tractography on their own normal data or on diseased/injured brains where the results may not represent the underlying physiology.

Proper citation: Network Modification Tool Lite (RRID:SCR_009511) Copy   

•   Source: SciCrunch Registry

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

An open source implementation of a non-rigid groupwise registration method. This project is implemented by Serdar K Balci (serdar at csail.mit.edu) and supervised by Polina Golland and William M. Wells All metrics are implementing in a multi-threaded fashion. The algorithm will run faster on computers with multiple CPU''s.

Proper citation: Non-rigid groupwise registration method (RRID:SCR_009512) Copy   

•   Source: SciCrunch Registry

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

Bibliography of books related to neuroscience addressing the topic of functional and structural neuroimaging.

Proper citation: NITRC Books (RRID:SCR_009510) 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.sci.utah.edu/cibc/software/map3d.html

A scientific visualization application written to display and edit complex, three-dimensional geometric models and scalar, time-based data associated with those models such as high resolution EEG, MEG, and ECG.

Proper citation: map3d (RRID:SCR_009628) Copy   

•   Source: SciCrunch Registry

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

Software using a novel local label learning strategy to estimate the target image?s segmentation label using statistical machine learning techniques. They used a support vector machine (SVM) with a K nearest neighbor (KNN) based training sample selection strategy to learn a classifier for each of the target image voxel based on a training dataset consisting of its neighboring voxels in the atlases. Validation experiments on hippocampus segmentation of 117 MR images demonstrated that the method can produce segmentation results consistently better than state-of-the-art label fusion methods.

Proper citation: Local Label Learning Segmentation (RRID:SCR_009504) Copy   

•   Source: SciCrunch Registry

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

Project to provide long-term hosting and release for small tools related to medical image analysis. Source repository contains highly experimental code intended for collaborative development. However, any interested parties are welcome to browse/reuse code. Stable/evolved projects will be moved to independent projects.

Proper citation: Landman NeuroImaging Tools (RRID:SCR_009503) Copy   

•   Source: SciCrunch Registry

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

This repository stores plugins, tutorial code, and examples demonstrating MRI manipulation within the MIPAV plugin environment. This project is separate from JIST so that we can provide WRITE access to any interested party without overly exposing the infrastructure to unplanned modification. Please contact the administrators if you would like to join this project - open use is encouraged.

Proper citation: JIST Resources for Algorithm Development (RRID:SCR_009500) 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

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

Segmentation of the brain from three-dimensional MR images is a crucial pre-processing step in morphological and volumetric brain studies. BrainMask implements a fully automatic brain segmentation algorithm that uses advanced thresholding with morphology and 3D edge detection algorithms. BrainMask demonstrates high segmentation accuracy. For a representative 26 datasets, the segmentation error averaged 3.4% ������ 1.3% (Mikheev A et al. J Magn Reson Imag 27(6):1235-41;2008). BrainMask includes NNN - a tool based on the algorithm developed by John Sled for correcting the intensity non-uniformity in MR data (Sled JG et al. IEEE Trans Med Imag 17(1):87-97;1998). BrainMask also includes a versatile DICOM wiewer and allows to selectively load and organize DICOM images into 3D and 4D datasets.

Proper citation: BrainMask Volume Processing Tool (RRID:SCR_009538) Copy   

•   Source: SciCrunch Registry

http://brainbrowser.cbrain.mcgill.ca

A web-enabled brain surface viewer that allows the user to explore in real time a 3D brain map expressed on a base surface. BrainBrowser has two modes of operation, exploring either a pre-calculated database of structural correlation maps or working with user-defined data. In this mode, the user may choose to explore the correlation structure for cortical thickness, cortical area or cortical volume, or any other pre-calculated metric. In the second mode, the user is prompted for the local filenames of the statistical map and the base surface. BrainBrowser can also be used to manipulate 3D fibre pathways derived from DTI, using the same simple file format (.obj) as for surface data. BrainBrowser on Youtube: http://www.youtube.com/watch?v=HlRTUYUf1Ew NOTE: BrainBrowser requires a WebGL-enabled browser such as Google Chrome to support its 3D graphics capability.

Proper citation: BrainBrowser (RRID:SCR_009535) Copy   

•   Source: SciCrunch Registry