Tools   Select Another Resource Report Type

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://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://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://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://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://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://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://itools.loni.usc.edu/

An infrastructure for managing of diverse computational biology resources - data, software tools and web-services. The iTools design, implementation and meta-data content reflect the broad NCBC needs and expertise (www.NCBCs.org).

Proper citation: iTools (RRID:SCR_009626) Copy   

•   Source: SciCrunch Registry

http://www.cise.ufl.edu/~abarmpou/lab/fanDTasia/

A Java applet tool for DT-MRI processing. It opens Diffusion-Weighted MRI datasets from user's computer and performs very efficient tensor field estimation using parallel threaded processing on user's browser. No installation is required. It runs on any operating system that supports Java (Windows, Mac, Linux,...). The estimated tensor field is guaranteed to be positive definite second order or higher order and is saved in user's local disc. MATLAB functions are also provided to open the tensor fields for your convenience in case you need to perform further processing. The fanDTasia Java applet provides also vector field visualization for 2nd and 4th-order tensors, as well as calculation of various anisotropic maps. Another useful feature is 3D fiber tracking (DTI-based) which is also shown using 3d graphics on the user's browser.

Proper citation: fanDTasia Java Applet: DT-MRI Processing (RRID:SCR_009624) 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