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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.rogue-research.com

Neuronavigation system for use in human cognitive neuroscience (TMS, EEG, NIRS) and for non-human neurosurgical applications.

Proper citation: Brainsight (RRID:SCR_009539) 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/iaclmedic/

This project is used for students enrolled in courses using the JIST framework. Content in this CVS is freely available, but it is not intended for any specific purpose.

Proper citation: JHU Proj. in Applied Medical Imaging (RRID:SCR_009499) 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/vmagnotta/

A Diffusion Tensor fiber tracking software suite that includes streamline tracking tools. The fiber tracking includes a guided tracking tool that integrates apriori information into a streamlines algorithm. This suite of programs is built using the NA-MIC toolkit and uses the Slicer3 execution model framework to define the command line arguments. These tools can be fully integrated with Slicer3 using the module discovery capabilities of Slicer3. NOTE: All new development is being managed in a github repository. Please visit, https://github.com/BRAINSia/BRAINSTools

Proper citation: GTRACT (RRID:SCR_009651) 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

http://www.vpixx.com/products/visual-stimulators/datapixx.html

Supplies a complete multi-function data and video processing USB peripheral for vision research. In addition to a dual-display video processor, the DATAPixx includes an array of peripherals which often need to be synchronized to video during an experiment, including a stereo audio stimulator, a button box port for precise reaction-time measurement, triggers for electrophysiology equipment, and even a complete analog I/O subsystem. Because we implemented the video controller and peripheral control on the same circuit board, you can now successfully synchronize all of your subject I/O to video refresh with microsecond precision.

Proper citation: DATAPixx (RRID:SCR_009648) Copy   

•   Source: SciCrunch Registry

http://www.restfmri.net

A user-friendly convenient toolkit to calculate Functional Connectivity (FC), Regional Homogeneity (ReHo), Amplitude of Low-Frequency Fluctuation (ALFF), Fractional ALFF (fALFF), Gragner causality and perform statistical analysis. You also can use REST to view your data, perform Monte Carlo simulation similar to AlphaSim in AFNI, calculate your images, regress out covariates, extract Region of Interest (ROI) time courses, reslice images, and sort DICOM files.

Proper citation: REST: a toolkit for resting-state fMRI (RRID:SCR_009641) Copy   

•   Source: SciCrunch Registry

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

To enable widespread application of the Biological parametric mapping (BPM) approach, they introduce robust regression and non-parametric regression in the neuroimaging context of application of the general linear model. Biological parametric mapping (BPM) has extended the widely popular statistical parametric approach to enable application of the general linear model to multiple image modalities (both for regressors and regressands) along with scalar valued observations. This approach offers great promise for direct, voxelwise assessment of structural and functional relationships with multiple imaging modalities. However, as presented, the biological parametric mapping approach is not robust to outliers and may lead to invalid inferences (e.g., artifactual low p-values) due to slight mis-registration or variation in anatomy between subjects.

Proper citation: Robust Biological Parametric Mapping (RRID:SCR_009642) Copy   

•   Source: SciCrunch Registry

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

Quadratically constrained quadratic programing (QCQP) technique in medical image analysis. QCQP based tools are provided for classification, segmentation, and bias field correction.

Proper citation: QCQP (RRID:SCR_009640) Copy   

•   Source: SciCrunch Registry

http://www.columbia.edu/~dx2103/brainimagescope.html

Software package for processing diffusion tensor imaging data. The following functions are included: 1. Converting imaging data in DICOME format to ANALYZE format 2. Extracting binary brain mask for quick scalp-removing 3. Correcting eddy-current induced distortion 4. Optimized tensor estimation based on noisy diffusion-weighted imaging (DWI) data 5. Scalp removal using a brain mask image 6. Corregistering imaging data and generating deformation field for mapping images from individual spaces to a template or target space 7. Spatial Normalization and Warping DTI 8. Fiber tracking 9. Clustering fiber tracts 10. Identifying brain ventricles and generating binary masks for the baseline and DW imaging data 11. Deriving diffusion anisotropy indices (DAIs) and principal directions (PD) and the corresponding color-coded PD-map.

Proper citation: DTI BrainImageScope (RRID:SCR_009559) Copy   

•   Source: SciCrunch Registry

http://www.connectomics.org/cfflib/

A container format for multi-modal neuroimaging data. It comprises connectome objects of type: CMetadata, CNetwork, CVolume, CSurface, CTrack, CScript, CData, CTimeseries, CImagestack. The Python library cfflib provides read/write functionality.

Proper citation: Connectome File Format (RRID:SCR_009551) 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://www.cise.ufl.edu/~tichen/cdfHC.zip

A Matlab demo for group wise point set registration using a novel CDF-based Havrda-Charvat Divergence, which is based on the paper: Ting Chen, Baba C. Vemuri, Anand Rangarajan and Stephan J. Eisenschenk, Group-wise Point-set registration using a novel CDF-based Havrda-Charvat Divergence. In IJCV : International Journal of Computer Vision, 86(1):111-124, January, 2010.

Proper citation: CDF-HC PointSetReg (RRID:SCR_009544) Copy   

•   Source: SciCrunch Registry