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http://nrg.wustl.edu/projects/fiv

A tool for visualizing functional and anatomic MRI data.

Proper citation: FIV (RRID:SCR_009575) Copy   

•   Source: SciCrunch Registry

http://www.ncigt.org/pages/Research_Projects/ImagingCoreToolbox/Imaging_Toolkit

This software provides algorithms for the reconstruction of raw MR data. In particular, it supports the reconstruction of accelerated data acquisitions where k-space is subsampled and the Fourier domain encoding is complemented by temporal encoding, spatial encoding, or and/or a constrained reconstruction. This library of functions provides a number of reconstruction algorithms that accurately employ advanced MR imaging methods including: UNFOLD; parallel imaging methods such as SENSE and GRAPPA; Homodyne processing of partial-Fourier data, and gradient field inhomogeneity correction (gradwarp); EPI Nyquist Ghost correction and ramp-sampling gridding. The target audience is research groups who may be interested in exploring or employing advanced MR reconstruction techniques, but don't have the necessary expertise in-house. Inquires may be directed to: ncigt-imaging-toolkit -at- bwh.harvard.edu

Proper citation: NCIGT Fast Imaging Library (RRID:SCR_009609) Copy   

•   Source: SciCrunch Registry

http://www.mazesuite.com/

A complete set of tools that enables researchers to perform spatial and navigational behavior experiments within interactive, easy to create, and extendable (e.g., multiple rooms) 3D virtual environments. MazeSuite can be used to design/edit adapted 3D environments where subjects? behavioral performance can be tracked. Maze Suite consists of three main applications; an editing program to create and alter maps (MazeMaker), a visualization/rendering module (MazeWalker), and finally an analysis/mapping tool (MazeAnalyzer). Additionally, MazeSuite has the capabilities of sending signal pulses to physiological recording devices using standard computer ports. MazeSuite, with all 3 applications, is a unique and complete toolset for researchers who want to easily and rapidly deploy interactive 3D environments. Requirements Maze Suite is designed for Windows 7, Windows Vista and Windows XP. 3D rendering quality depends on available graphics card hardware; OpenGL 2.1 or above compliant is recommended. For Windows XP systems, .NET Framework Version 2.0 or above is required and can be downloaded from Microsoft's website.

Proper citation: MazeSuite (RRID:SCR_009606) Copy   

•   Source: SciCrunch Registry

http://ric.uthscsa.edu/mango/

A viewer for medical research images that provides analysis tools and a user interface to navigate image volumes. There are three versions of Mango, each geared for a different platform: * Mango ? Desktop ? Mac OS X, Windows, and Linux * webMango ? Browser ? Safari, Firefox, Chrome, and Internet Explorer * iMango ? Mobile ? Apple iPad Key Features: * Built-in support for DICOM, NIFTI, Analyze, and NEMA-DES formats * Customizable: Create plugins, custom filters, color tables, file formats, and atlases * ROI Editing: Threshold and component-based tools for painting and tracing ROIs * Surface Rendering: Interactive surface models supporting cut planes and overlays * Image Registration: Semi-automatic image coregistration and manual transform editing * Image Stacking: Threshold and transparency-based image overlay stacking * Analysis: Histogram, cross-section, time-series analysis, image and ROI statistics * Processing: Kernel and rank filtering, arithmetic/logic image and ROI calculators

Proper citation: Mango (RRID:SCR_009603) Copy   

•   Source: SciCrunch Registry

http://visual.cs.utsa.edu/eegvis

A MATLAB toolbox for exploration of multi-channel EEG and other large array-based data sets using multi-scale drill-down techniques. The toolbox can be used directly in MATLAB at any stage in a user's processing pipeline, as a plug in for EEGLAB, or as a standalone precompiled application without MATLAB running. EEGVIS and its supporting packages are freely available under the GNU general public license. The toolbox also supplies a number of extensible base classes for users who wish to develop their own visualizations.

Proper citation: EEGVIS (RRID:SCR_009569) Copy   

•   Source: SciCrunch Registry

http://omicslab.genetics.ac.cn/ISRNA/

An online toolkit for analyzing high-throughput small RNA sequencing data., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: ISRNA (RRID:SCR_009565) Copy   

•   Source: SciCrunch Registry

https://github.com/clementsan/DTI-Reg

An open-source C++ application that performs pair-wise DTI registration, using scalar FA map to drive the registration. Individual steps of the pair-wise registration pipeline are performed via external applications - some of them being 3D Slicer modules. Starting with two input DTI images, scalar FA maps are generated via dtiprocess. Registration is then performed between these FA maps, via BRAINSFit/BRAINSDemonWarp or ANTS -Advanced Normalization Tools-, which provide different registration schemes: rigid, affine, BSpline, diffeomorphic, logDemons. The final deformation is then applied to the source DTI image via ResampleDTI.

Proper citation: DTI-Reg (RRID:SCR_009560) Copy   

•   Source: SciCrunch Registry

http://users-mb.au.dk/pmgrp/downloads.php

A pipeline for small RNA-seq data analysis.

Proper citation: shortran (RRID:SCR_009636) Copy   

•   Source: SciCrunch Registry

http://code.google.com/p/psom/

A lightweight software library to manage complex multi-stage data processing. A pipeline is a collection of jobs, i.e. Matlab or Octave codes with a well identified set of options that are using files for inputs and outputs. To use PSOM, the only requirement is to generate a description of a pipeline in the form of a simple Matlab / Octave structure. PSOM then automatically offers the following services: * Run jobs in parallel using multiple CPUs or within a distributed computing environment. * Generate log files and keep track of the pipeline execution. These logs are detailed enough to fully reproduce the analysis. * Handle job failures : successful completion of jobs is checked and failed jobs can be restarted. * Handle updates of the pipeline : change options or add jobs and let PSOM figure out what to reprocess !

Proper citation: Pipeline System for Octave and Matlab (RRID:SCR_009637) Copy   

•   Source: SciCrunch Registry

http://www.nordicneurolab.com

From state of the art post-processing and visualization software for BOLD, Diffusion / DTI, and Perfusion / DCE imaging to fMRI hardware for audio and visual stimulation, eye tracking, and patient response collection, they provide products and solutions that define the field of functional MR imaging. They are dedicated to bringing the most advanced neuro-imaging tools to market while making functional MRI programs easy to implement. Through collaboration with research and clinical teams from both academic and medical centers, MR system manufacturers, and third party vendors they develop and manufacture hardware and software solutions that meet the needs of very experienced centers while developing training programs to make fMRI easy to adopt for more novice users. Their products are used around the world by researchers and clinicians alike.

Proper citation: NordicNeuroLab (RRID:SCR_009632) Copy   

•   Source: SciCrunch Registry

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

This package contains a software implementation for joint label fusion and corrective learning, which were applied in MICCAI 2012 Grand Challenge on Multi-Atlas Labeling and finished in the first place. Joint label fusion is for combining candidate segmentations produced by registering and warping multiple atlases for a target image. Corrective learning can be applied to further reduce systematic errors produced by joint label fusion. In general, corrective learning can be applied to correct systematic errors produced by other segmentation methods as well.

Proper citation: PICSL Multi-Atlas Segmentation Tool (RRID:SCR_009633) Copy   

•   Source: SciCrunch Registry

http://bisp.kaist.ac.kr/NIRS-SPM

A SPM and MATLAB-based software package for statistical analysis of near-infrared spectroscopy (NIRS) signals. Based on the general linear model (GLM), and Sun's tube formula / Lipschitz-Killing curvature (LKC) based expected Euler characteristics, NIRS-SPM not only provides activation maps of oxy-, deoxy-, and total-hemoglobin, but also allows for super-resolution activation localization. Additional features, including a wavelet-minimum description length detrending algorithm and cerebral metabolic rate of oxygen (CMRO2) estimation without hypercapnia, were implemented in the NIRS-SPM software package., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: NIRS-SPM (RRID:SCR_009630) Copy   

•   Source: SciCrunch Registry

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

NITRC-wide community facilities: Forums, Wiki, Tracker, and News.

Proper citation: NITRC Community (RRID:SCR_009631) Copy   

•   Source: SciCrunch Registry

http://www.cbs.mpg.de/institute/software/lipsia/

Software tool for processing functional magnetic resonance imaging (fMRI) data.Software system for evaluation of functional magnetic resonance images of human brain.

Proper citation: Lipsia (RRID:SCR_009595) Copy   

•   Source: SciCrunch Registry

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

A reliable patient response system designed specifically for use in an fMRI. Lumina was developed to satisfy the requirements of both the clinical and research fields.

Proper citation: Lumina LP- 400 Response System (RRID:SCR_009596) Copy   

•   Source: SciCrunch Registry

http://gforge.dcn.ed.ac.uk/gf/project/limo_eeg/

A matlab toolbox (EEGlab compatible) allowing the processing of MEEG data using single trials and hierarchical linear models. Almost all statistical designs can be analyzed with the tool. Across subject analyses are performed using bootstrap offering robust inferences.

Proper citation: LIMO EEG (RRID:SCR_009592) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/diffusion-mri/

This program contains Python modules for modeling and reconstruction of diffusion weighted MRI data. It is a subset of the code internally used in the CVGMI lab at the University of Florida. Three different reconstruction methods are currently included in this program, namely, Mixture of Wisharts (MOW), Diffusion Orientation Transform (DOT) and Q-ball Imaging (QBI). This program is mainly developed and maintained by Bing Jian, as part of his Ph.D. research, supervised by Prof. Baba Vemuri. Please note that the source code of this program is hosted at Google Code, see the Source Code link on the left.

Proper citation: Multi-fiber Reconstruction from DW-MRI (RRID:SCR_009509) Copy   

•   Source: SciCrunch Registry

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

This repository stores and provides opportunities for collaboration through Matlab code, libraries, and configuration information for projects in early stage development. The MASI research laboratory concentrates on analyzing large-scale cross-sectional and longitudinal neuroimaging data. Specifically, they are interested in population characterization with magnetic resonance imaging (MRI), multi-parametric studies (DTI, sMRI, qMRI), and shape modeling.

Proper citation: MASIMatlab (RRID:SCR_009506) Copy   

•   Source: SciCrunch Registry

http://www.smivision.com/en/gaze-and-eye-tracking-systems/products/iview-x-mri-meg.html

A non-invasive, long-range eye tracking system for use in the fMRI environment. Some features of the system include: * Elaborate faraday shielding and fiber optics to avoid noise in high-field magnets. * Includes stimulus presentation software ?Experiment Center? and is compatible with 3rd party products such as ?Presentation? by NeuroBS. * Utilizes mirror box customized for large field of view. * Includes powerful analysis software ?BeGaze2? for graphical and statistical analysis of eye movements. * Includes fixation, saccade and blink detection, and area-of-interest based statistics * Real-time data available via digital or analog output

Proper citation: iView X MRI-LR - Eye Tracking for fMRI (RRID:SCR_009627) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/masi-fusion/

Tool that provides a unified framework for testing and applying statistical and voting label fusion techniques. The project will include implementations of several different voting techniques including majority vote, weighted voting, and regionally weighted voting. Additionally, multiple statistical fusion methods will be included, notably, STAPLE, Spatial STAPLE, STAPLER and COLLATE. In addition to the fusion algorithms, code for running specialized simulations and various tools and utilities to test the efficacy of the algorithms will be provided.

Proper citation: MASI Label Fusion (RRID:SCR_009505) Copy   

•   Source: SciCrunch Registry