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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

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

A FSL package for the comprehensive management of large-scale multi-site fMRI projects, including data storage, retrieval, calibration, analysis, multi-modal integration, and quality control.

Proper citation: FBIRN Image Processing Scripts (RRID:SCR_009471) 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/jalmmse_dwi/

This module reduces Rician noise on nhdr/nrrd DWIs. Filters image in mean squared error sense using Rician noise model. All estimations are performed as sample estimates in a "shaped neighborhood" defined by the weights extracted from structural similarity of voxels following same idea as in Non-Local Means filter.

Proper citation: Joint Anisotropic LMMSE Filter for Stationary Rician noise removal in DWI (RRID:SCR_009502) Copy   

•   Source: SciCrunch Registry

http://www.nmr.mgh.harvard.edu/~jbm/jip/

Software toolkit for analysis of rodent and non-human primate fMRI data. The toolkit consists of binary executables, highly portable open-source c code, and image resources that enable 1) Automated registration based upon mutual information (affine, non-linear warps), with flexible control and visualization of each step; 2) visualization of 4-dimensional data using either mosaic or tri-planar display of the z/slice dimension, and integration of a general linear model for graphical display of time series analysis; 3) A simple and flexible 1st-order GLM for fMRI time series analysis, a 1st-order GLM analysis for PET data within the SRTM framework, plus a 2nd-order GLM analysis following the Worsley 2002 scheme, and 4) MRI templates to place your rodent and non-human primate data into standardized spaces.

Proper citation: JIP Analysis Toolkit (RRID:SCR_009588) Copy   

•   Source: SciCrunch Registry

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

This code registers linearly and non-linearly Diffusion Weighted Magnetic Resonance Images (DW-MRIs) by extending FLIRT (linear registration of 3D scalar volumes) and FNIRT (non-linear registration of 3D scalar volumes) in the FMRIB Software Library (FSL) to work with 4D volumes. The basis for registering DW-MRIs is the concept of Angular Interpolation (Tao, X., Miller, J. V., 2006. A method forregistering diffusion weighted magnetic resonance images. In: MICCAI. Vol. 9. pp. 594?602), which is implemented and extended to non-linear registration, based on the FLIRT and FNIRT models in FSL. See http://www.frontiersin.org/Brain_Imaging_Methods/10.3389/fnins.2013.00041/abstract. The code does not overwrite FLIRT, FNIRT or any of the FSL C++ code. It is added as FLIRT4D, FNIRT4D and supporting cost functions. The makefiles will however be overwritten to compile the new code, without affecting any version of FSL.

Proper citation: DW-MRI registration in FSL (RRID:SCR_009461) Copy   

•   Source: SciCrunch Registry

http://www.hammersuite.com/

The tool is a GUI for a complete processing pipeline of brain MR images. It provides functions on skull-stripping, cerebellum removal, tissue segmentation, and HAMMER registration.

Proper citation: HAMMER Suite (RRID:SCR_009583) Copy   

•   Source: SciCrunch Registry

http://econnectome.umn.edu/

An open-source MATLAB software package for imaging brain functional connectivity from electrophysiological signals. It provides interactive graphical interfaces for EEG/ECoG/MEG preprocessing, source estimation, connectivity analysis and visualization. Connectivity from EEG/ECoG/MEG can be mapped over sensor and source domains. This package is designed for use by researchers in neuroscience, psychology, cognitive science, clinical neurophysiology, neurology and other disciplines. The graphical interface-based platform requires little programming knowledge or experience with MATLAB. eConnectome is developed by the Biomedical Functional Imaging and Neuroengineering Laboratory at the University of Minnesota, directed by Dr. Bin He. The visualization module is jointly developed with Drs. Fabio Babiloni and Laura Astolfi at the University of Rome La Sapienza.

Proper citation: eConnectome (RRID:SCR_009618) Copy   

•   Source: SciCrunch Registry

http://www.imagilys.com/brainmagix-spm-viewer/

A free, professional viewer for SPM fMRI results. SPM (Statistical Parametric Mapping, UCL, London) is a powerful fMRI analysis software but its visualization capabilities are sometimes a limitation for the researchers. That's why Imagilys has decided to offer the neuroimaging community a free version of its commercial "BrainMagix" neuroimaging software, called "BrainMagix SPM viewer". BrainMagix SPM Viewer's Features - Professional viewer for your SPM-based fMRI activations - JAVA-programmed, cross-platform (Windows, MAC, Linux), without Matlab license, making it possible to share your results with colleagues who do not have SPM installed - Reads SPM.mat files and NIfTI images in an user-friendly way - Overlay the blobs with an atlas or any anatomical image - On the fly adjustment of threshold and cluster size - Localize your activations in an atlas - BOLD signal curves in ROIs (future feature) - Export your results as PNG images

Proper citation: BrainMagix SPM Viewer (RRID:SCR_009537) Copy   

•   Source: SciCrunch Registry

http://web1.sph.emory.edu/bios/CBIS/download_page.php

A statistical and graphical visualization MATLAB toolbox for the analysis of fMRI data, called the Bayesian Spatial Model for activation and connectivity (BSMac). BSMac simultaneously performs whole-brain activation analyses at the voxel and region of interest levels as well as task-related functional connectivity (FC) analyses using a flexible Bayesian modeling framework (Bowman et al., 2008). BSMac allows for inputting data in either Analyze or Nifti file formats. The user provides information pertaining to subgroup memberships, scanning sessions, and experimental tasks (stimuli), from which the design matrix is constructed. BSMac then performs parameter estimation based on MCMC methods and generates plots for activation and FC, such as interactive 2D maps of voxel and region-level task-related changes in neural activity and animated 3D graphics of the FC results.

Proper citation: BSMac (RRID:SCR_009531) Copy   

•   Source: SciCrunch Registry

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

Program to develop generic standards and tools to facilitate the recording, sharing, and reporting of neuroimaging metadata. It is expected that these efforts will greatly improve upon current practices for archiving and sharing neuroscience data. Neuroscience data, particularly those in neuroinformatics related areas such as neuroimaging and electrophysiology, are associated with a rich set of descriptive information often called metadata. For data archive, storage, sharing and re-use, metadata are of equal importance to primary data, as they define the methods and conditions of data acquisition (such as device characteristics, study/experiment protocol and parameters, behavioral paradigms, and subject/patient information), and statistical procedures. A further challenge for datasharing is the rapidly evolving nature of investigative methods and scientific applications.

Proper citation: INCF Neuroimaging Data Sharing (RRID:SCR_009497) Copy   

•   Source: SciCrunch Registry

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

Suite of tools for brain image analysis. Image manipulation, 2D visualization, linear alignment, BBSI, template-based bias correction, skullstrip. GUI Image analysis tools. Now modified to read/write single file nifti (.nii) format. Other packages to be added.

Proper citation: IDeA Lab brain image processing suite (RRID:SCR_009495) Copy   

•   Source: SciCrunch Registry

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

A method for group-wise image registration by pairwisely registering similar images identified using graph theoretic techniques. Particularly, they use sparse coding to estimate image similarity measures among images to be registered, yielding asymmetric, group-wise image similarity measures for each image to others in the group.

Proper citation: Groupwise Image Registration Toolbox (RRID:SCR_009492) Copy   

•   Source: SciCrunch Registry

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

An international effort to establish resources necessary to study the application of neuroimaging measures as (surrogate) biomarkers in Huntington''s Disease (HD). The primary aims are to develop and apply software tools, imaging protocols, quality control procedures, data archiving, data distribution, and participation guidelines that will accelerate existing and prospective imaging studies.

Proper citation: HD Neuro-Informatics (RRID:SCR_009493) Copy   

•   Source: SciCrunch Registry

https://github.com/BRAINSia/BRAINSTools/tree/master/BRAINSMush

Tool to generate brain volume mask from input of T1 and T2-weighted images alongside a region of interest brain mask. This volume mask omits dura, skull, eyes, etc. The program is built upon ITK and uses the Slicer3 execution model framework to define the command line arguments and can be fully integrated with Slicer3 using the module discovery capabilities of Slicer3.

Proper citation: BRAINSMush (RRID:SCR_009485) Copy   

•   Source: SciCrunch Registry

http://cocomac.org/WWW/paxinos3D/index.html

An interactive interface of macaque stereotaxic atlas with a connectivity database, allowing integrated data analysis and mapping between 3D structures with database vocabularies. These Java-based tools are capable of reading stacks of polygons described in svg vector format and arrange them in 3D space so that the corresponding structures can be viewed and manipulated individually. An additional excel (currently v. 1997-2003) file maintains the structure abbreviations and their mapping to the terminology of databases that provide supplementary information. Here in particular we have manually drawn the cortical, striatal, thalamic and amygdaloid structures of the 151 frontal sections from the Rhesus Monkey Brain in Stereotactic Coordinates authored by Paxinos and colleagues in 1999. After loading the excel file and a set of the svg files, the view can be rotated, zoomed and individual brain structures be selected for identification and simple geometric measures. A stereotaxic grid is a display option. The abbreviations of the brain structures are mapped to entities recorded in the CoCoMac database of primate brain connectivity. Thereby one can retrieve mapping and connectivity information for the selected structure as text or connecting arrows.

Proper citation: CoCoMac-Paxinos3D viewer (RRID:SCR_009548) Copy   

•   Source: SciCrunch Registry

http://invizian.loni.usc.edu

A visualization environment that enables you, via your computer, to display and interact with hundreds of neuroimaging data sets at once ?bringing together brain image data from some of the world?s best neuroscience research teams. INVIZIAN empowers both researchers and students of neuroscience to explore and understand the human brain using a simple yet powerful user interface for neuroimaging data exploration and discovery. See a beautiful example of a cloud of individual brains tumbling around in the INVIZIAN interface in Vimeo (http://vimeo.com/67984681). Visit often to see how we are making continuing progress to make Invizian even more amazing.

Proper citation: INVIZIAN (RRID:SCR_009549) 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.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