Tools   Select Another Resource Report Type

http://trackvis.org/

TrackVis is software tool that can visualize and analyze fiber track data from diffusion MR imaging (DTI/DSI/HARDI/Q-Ball) tractography. It does NOT perform actual fiber tracking. Diffusion Toolkit is a set of tools that reconstruct diffusion imaging data and generate fiber track data for TrackVis to visualize. Because these two sets of tools were developed and maintained separately and each has distinguished funtionalities, they decided to distribute them as two separate programs for the ease of maintenance and upgrade. You do need both of them to perform complete diffusion data processing and analysis. Features of TrackVis include: * Cross-platform. Works on Windows, Mac OS X and Linux with native look and feel. * A variety of track filters (track selecting methods) allowing users to explore and locate specific bundles with ease. * Multiple rendering modes with customizable scalar-driven color codes. * Real-time parameter adjustment and 3D render. * Open format of the track data file allowing users to integrate customized scalar data into the track file and visualize and analyze it. Save and restore scenes in XML style scene file. * Statistical scalar analysis of tracks and ROIs. * Synchronized real-time multiple dataset analysis and display allowing time-point and/or subject comparison. Synchronized analysis and display on same dataset can also be performed in real-time remotely over the network. * Upfront in-line parameter adjustment in real-time. No tedious pop-up dialogs. TrackVis works with Track File created by Diffusion Toolkit. Diffusion Toolkit processes raw DICOM, Nifti format and ANALYZE images. TrackVis and Diffusion Toolkit are cross-platform software. They can run on Windows XP, Mac OS X as well as Linux.

Proper citation: TrackVis (RRID:SCR_004817) Copy   

•   Source: SciCrunch Registry

http://enigma.ini.usc.edu/

Network that brings together researchers in imaging genomics, to understand brain structure and function, based on MRI, DTI, fMRI and genomewide association scan (GWAS) data. The ENIGMA Network has several goals: * to create a network of like-minded individuals, interested in pushing forward the field of imaging genetics * to ensure promising findings are replicated via member collaborations, in order to satisfy the mandates of most journals * to share ideas, algorithms, data, and information on promising findings or methods * to facilitate training, including workshops and conferences on key methods and emerging directions in imaging genetics. Data sharing with other members of the ENIGMA Network is optional and by no means a requirement of joining the network. Genetics and Imaging Protocols are available.

Proper citation: ENIGMA: Enhancing Neuro Imaging Genetics Through Meta-Analysis (RRID:SCR_005515) Copy   

•   Source: SciCrunch Registry

http://www.neuron.yale.edu

NEURON is a simulation environment for modeling individual neurons and networks of neurons. It provides tools for conveniently building, managing, and using models in a way that is numerically sound and computationally efficient. It is particularly well-suited to problems that are closely linked to experimental data, especially those that involve cells with complex anatomical and biophysical properties. NEURON has benefited from judicious revision and selective enhancement, guided by feedback from the growing number of neuroscientists who have used it to incorporate empirically-based modeling into their research strategies. NEURON's computational engine employs special algorithms that achieve high efficiency by exploiting the structure of the equations that describe neuronal properties. It has functions that are tailored for conveniently controlling simulations, and presenting the results of real neurophysiological problems graphically in ways that are quickly and intuitively grasped. Instead of forcing users to reformulate their conceptual models to fit the requirements of a general purpose simulator, NEURON is designed to let them deal directly with familiar neuroscience concepts. Consequently, users can think in terms of the biophysical properties of membrane and cytoplasm, the branched architecture of neurons, and the effects of synaptic communication between cells. * helps users focus on important biological issues rather than purely computational concerns * has a convenient user interface * has a user-extendable library of biophysical mechanisms * has many enhancements for efficient network modeling * offers customizable initialization and simulation flow control * is widely used in neuroscience research by experimentalists and theoreticians * is well-documented and actively supported * is free, open source, and runs on (almost) everything

Proper citation: NEURON (RRID:SCR_005393) Copy   

•   Source: SciCrunch Registry

http://pubbrain.org/

A literature search and visualization tool that allows end users to enter any PubMed query and see that query rendered as a heatmap illustrating which regions of interest are most commonly mentioned within the search results. To use PubBrain, simply enter any valid PubMed search in the search box.

Proper citation: PubBrain (RRID:SCR_005387) Copy   

•   Source: SciCrunch Registry

http://www.neurobureau.org/

A neuroscience collaboratory that supports open neuroscience, which basically encompasses the unrestricted sharing of: analytic tools, computational resources, data, and knowledge. Its goal is to establish a spirit and forum for open neuroscience, and to facilitate the translation of that ethos into action by conducting successful large open interdisciplinary collaborative efforts such as releasing the preprocessed version of the ADHD-200 competition dataset. The Brain-Art Competition is likewise an effort to bring attention to the more aesthetically-oriented aspects of their field, and to publicize and encourage creative developments taking place at the nexus of art and neuroimaging.

Proper citation: Neuro Bureau (RRID:SCR_005357) Copy   

•   Source: SciCrunch Registry

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

OpenGL based medical image viewer that contains useful tools such as a DICOM anonymizer and format conversion utility. MIView can read DICOM, Analyze/Nifti, and raster images, and can write Analyze/Nifti and raster images.

Proper citation: MIView (RRID:SCR_000413) Copy   

•   Source: SciCrunch Registry

https://dipy.org/

Software Python package for analyzing diffusion data. Software library for analysis of diffusion MRI data.

Proper citation: Dipy (RRID:SCR_000029) Copy   

•   Source: SciCrunch Registry

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

Software for detecting artifacts and performing individual region-of-interest based statistical analysis of fMRI data and enables users of fMRI technology to produce more detailed, consistent and reliable results.

Proper citation: RapidArt (RRID:SCR_000422) Copy   

•   Source: SciCrunch Registry

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

A developer tool to provide batch processing capability for pipelines. Users input data into a input table and run analysis with it. It is used to power CamBA and Brainwaver User interfaces.

Proper citation: BrainFX (RRID:SCR_000302) Copy   

•   Source: SciCrunch Registry

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

A sequence of fully automated voxel-wise rigid registration that utilizes stable structures of reference for assessment of craniofacial changes overtime.The major strengths of this method are that registration does not depend on the precision of the 3D surface models and that a stable structure of reference can be used without the simple best fit of all surfaces.

Proper citation: CMFreg (RRID:SCR_000171) Copy   

•   Source: SciCrunch Registry

http://www.hitachi-medical.co.jp/english/

An instrumental supplier which provides researchers and clinicians with sophisticated All-in-One solutions in the field of neuroscience.

Proper citation: Hitachi Optical Topography System (RRID:SCR_000865) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/maps4mipav/

The exploratory development tree of Java Image Science Toolkit (JIST), an extension to the MIPAV (Medical Image Processing, Analysis, and Visualization) plug-in framework that allows the user to design and execute pipelines, which are multi-stage processing tasks.. New features and designs are tested here before general release into the JIST project. JIST was formerly known as the MedIC Automated Pipeline Scheduler (MAPS).

Proper citation: Maps4Mipav (Exploratory JIST) (RRID:SCR_000613) Copy   

•   Source: SciCrunch Registry

http://www.nirx.net

Commercial technology solutions for NIRS neuroscience imaging applications.

Proper citation: NIRx NIRS Neuroimaging (RRID:SCR_002491) Copy   

•   Source: SciCrunch Registry

http://biodev.ece.ucsb.edu/projects/bisquik/wiki

A scalable web-based system for biological image analysis, management and exploration. The Bisque system incorporates many features useful to imaging researchers from image capture to extensible image analysis and querying. At the core, bisque maintains a flexible database of images and experimental metadata. Image analyses can be incorporated into the system and deployed on clusters and desktops. Search and comparison of datasets by image data and content is supported. Novel semantic analyses are integrated into the system allowing high level semantic queries and comparison of image content. New features and testing of Bisque version: 0.5.1, among many others are: # Parallel execution of datasets # Rich interfaces for autogenerated module UI # Abstracted storage system for local, irods, etc.. They are using Mercurial for their source control system. This should be installed before proceeding. Browse source on-line, http://biodev.ece.ucsb.edu/projects/bisquik/browser Bisque Installation, http://biodev.ece.ucsb.edu/projects/bisquik/wiki/InstallationInstructions05 Bisque DOWNLOAD, http://biodev.ece.ucsb.edu/projects/bisquik/wiki/download, THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Bisque (RRID:SCR_005564) Copy   

•   Source: SciCrunch Registry

http://www.loni.usc.edu/Software/LOVE

A versatile 1D, 2D and 3D data viewer geared for cross-platform visualization of stereotactic brain data. It is a 3-D viewer that allows volumetric data display and manipulation of axial, sagittal and coronal views. It reads Analyze, Raw-binary and NetCDF volumetric data, as well as, Multi-Contour Files (MCF), LWO/LWS surfaces, atlas hierarchical brain-region labelings ( Brain Trees). It is a portable Java-based software, which only requires a Java interpreter and a 64 MB of RAM memory to run on any computer architecture. LONI_Viz allows the user to interactively overlay and browse through several data volumes, zoom in and out in the axial, sagittal and coronal views, and reports the intensities and the stereo-tactic voxel and world coordinates of the data. Expert users can use LONI_Viz to delineate structures of interest, e.g., sulcal curves, on the 3 cardinal projections of the data. These curves then may be use to reconstruct surfaces representing the topological boundaries of cortical and sub-cortical regions of interest. The 3D features of the package include a SurfaceViewer and a full real-time VolumeRenderer. These allow the user to view the relative positions of different anatomical or functional regions which are not co-planar in any of the axial, sagittal or coronal 2D projection planes. The interactive part of LONI_Viz features a region drawing module used for manual delineation of regions of interest. A series of 2D contours describing the boundary of a region in projection planes (axial, sagittal or coronal) could be used to reconstruct the surface-representation of the 3D outer shell of the region. The latter could then be resliced in directions complementary to the drawing-direction and these complementary contours could be loaded in all tree cardinal views. In addition the surface object could be displayed using the SurfaceViewer. A pre-loading data crop and sub-sampling module allows the user to load and view practically data of any size. This is especially important when viewing cryotome, histological or stained data-sets which may reach 1GB (109 bytes) in size. The user could overlay several pre-registered volumes, change intensity colors and ranges and the inter-volume opacities to visually inspect similarities and differences between the different subjects/modalities. Several image-processing aids provide histogram plotting, image-smoothing, etc. Specific Features: * Region description DataBase * Moleculo-genetic database * Brain anatomical data viewer * BrainMapper tool * Surface (LightWave objects/scenes) and Volume rendering tools * Interactive Contour Drawing tool Implementation Issues: * Applet vs. Application - the software is available as both an applet and a standalone application. The former could be used to browse data from within the LONI database, however, it imposes restrictions on file-size, Internet connection and network-bandwidth and client/server file access. The later requires a local install and configuration of the LONI_Viz software * Extendable object-oriented code (Java), computer architecture independent * Complete online software documentation is available at http://www.loni.ucla.edu/LONI_Viz and a Java-Class documentation is available at http://www.loni.ucla.edu/~dinov/LONI_Vis.dir/doc/LONI_Viz_Java_Docs.html

Proper citation: LONI Visualization Tool (RRID:SCR_000765) Copy   

•   Source: SciCrunch Registry

http://neuromorphometrics.org:8080/nvm/index.html

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 6, 2023. Software tool for quantitative neuroanatomical measurements in volumetric image data. Used to draw regions of interest for subsequent fMRI analysis.

Proper citation: NVM (RRID:SCR_000600) Copy   

•   Source: SciCrunch Registry

http://www.loni.usc.edu/Software/Pipeline

A free workflow application primarily aimed at neuroimaging researchers that allows users to easily describe their executables in a graphical user interface (ie. create a module) and connect them together to create complex analyses all without having to code a single line in a scripting language. The Pipeline Client runs on your PC/Mac/Linux computer upon which you can create sophisticated processing workflows using a variety of commonly available executable tools (e.g. FSL, AIR, FreeSurfer, AFNI, Diffusion Toolkit, etc). The Distributed Pipeline Server can be installed on your Linux cluster and you can submit processing jobs directly to your own compute systems. Once you����??ve created a module for use in the LONI Pipeline, you can save it into your personal library and reuse it in other workflows you create by simply dragging and dropping it in. Because the LONI Pipeline is written in Java, you can work in whatever operating system suits you best. If there are tools that you need that can only work on another operating system, you can install a Pipeline server on that computer and connect from your client to do processing and analysis remotely.

Proper citation: LONI Pipeline Processing Environment (RRID:SCR_001161) Copy   

•   Source: SciCrunch Registry

http://nrg.wustl.edu/software/dicom-browser/

A platform-independent desktop tool for inspecting DICOM header fields, editing DICOM header fields, viewing DICOM images, and transferring DICOM files to a DICOM receiver. DicomBrowser includes scriptable header editing to support various de-identification protocols. DicomBrowser is written in Java and uses ImageJ for image viewing and the dcm4che toolkit for much of its DICOM implementation.

Proper citation: DicomBrowser (RRID:SCR_000864) Copy   

•   Source: SciCrunch Registry

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

A collection of functions with batch functionality for SPM: * user entered expression (one set of volumes); * binarize non-zero voxels; * binarize/threshold each image; * binarize non-zero voxels, sum, rebinarize; * voxelwise calculations on pairs (add sub mult div ... etc.); * flip sign of all non-zero voxels; * x-flip image along y = 0; * mask images to a template; * T-to-Z transform; * Winsorize (cap) extreme values; * Z-score transform of image relative to its global mean and SD; * write single voxels to a .nii; * create a cluster image; * split cluster image into constituent images; * write hemisphere masks from template; * homotopic calculations; * replace zeros with __; * pad image with extra voxels;

Proper citation: imcalc: SPM batch image calculator (RRID:SCR_000868) Copy   

•   Source: SciCrunch Registry

http://neuralensemble.org/trac/OpenElectrophy

Software Python module for electrophysiology data analysis.

Proper citation: OpenElectrophy (RRID:SCR_000819) Copy   

•   Source: SciCrunch Registry