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http://www.vaa3d.org

A handy, fast, and versatile 3D/4D/5D Image Visualization & Analysis System for Bioimages & Surface Objects. Vaa3D is a cross-platform (Mac, Linux, and Windows) tool for visualizing large-scale (gigabytes, and 64-bit data) 3D/4D/5D image stacks and various surface data. It is also a container of powerful modules for 3D image analysis (cell segmentation, neuron tracing, brain registration, annotation, quantitative measurement and statistics, etc) and data management. Vaa3D is very easy to be extended via a powerful plugin interface. For example, many ITK tools are being converted to Vaa3D Plugins. Vaa3D-Neuron is built upon Vaa3D to make 3D neuron reconstruction much easier. In a recent Nature Biotechnology paper (2010, 28(4), pp.348-353) about Vaa3D and Vaa3D-Neuron, an order of magnitude of performance improvement (both reconstruction accuracy and speed) was achieved compared to other tools.

Proper citation: Vaa3D (RRID:SCR_002609) Copy   

•   Source: SciCrunch Registry

http://tipl.labsolver.org

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 14,2026. A lightweight C++ template library designed mainly for medical imaging processing. The design paradigm follows generic programming, and the purpose is to provide an easy-to-use and also ready-to-use library. The code is template-based, and only header files are needed to be included to the source code. This library provides the following functions: # DICOM (r), Analyze(r), Nifti (r/w), and MATLAB MAT V4 (r/w) # numerical: add, multiply, gradient. # interpolation: linear, gaussian radial basis # filters: mean, gaussian, laplacian, sobel, anisotropic diffusion # morphological processing: erosion, expansion, opening, closing # template-based Fourier transform # linear coregistration: rigid body, affine transform, least square fit, mutual information # nonlinear coregistration: The Large Deformation Diffeomorphic Metric Mapping (LDDMM)

Proper citation: Template Image Processing Library (RRID:SCR_002600) Copy   

•   Source: SciCrunch Registry

http://www.turtleseg.org

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 14,2026. An interactive segmentation tool originally designed for 3D medical images. Accurate and automatic 3D medical image segmentation remains an elusive goal and manual intervention is often unavoidable. TurtleSeg implements techniques that allow the user to provide intuitive yet minimal interaction for guiding the 3D segmentation process.

Proper citation: TurtleSeg (RRID:SCR_002605) Copy   

•   Source: SciCrunch Registry

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

Software algorithm that automatically estimates and removes physiological noise in BOLD fMRI data, including the effects of heartbeat and respiration. This algorithm (1) masks out high-variance CSF and vascular tracts that may otherwise confound analyses, and (2) regresses out noise timeseries in grey matter tissue, using an adaptive multivariate component decomposition (Canonical Autocorrelations Analysis). PHYCAA+ is an efficient, automated procedure that does NOT require external measures of physiology, nor does it require the user to manually identify noise components. Based on the peer-reviewed article: Churchill & Strother (2013). PHYCAA+: An Optimized, Adaptive Procedure for Measuring and Controlling Physiological Noise in BOLD fMRI. NeuroImage 82: 306-325

Proper citation: PHYCAA+: adaptive physiological noise correction for BOLD fMRI (RRID:SCR_002514) Copy   

•   Source: SciCrunch Registry

https://pdbp.ninds.nih.gov

Common data management resource and web portal to promote discovery of Parkinson's Disease diagnostic and progression biomarker candidates for early detection and measurement of disease progression. PDBP will serve as multi-faceted platform for integrating existing biomarker efforts, standardizing data collection and management across these efforts, accelerating discovery of new biomarkers, and fostering and expanding collaborative opportunities for all stakeholders.

Proper citation: Parkinson’s Disease Biomarkers Program Data Management Resource (PDBP DMR) (RRID:SCR_002517) Copy   

•   Source: SciCrunch Registry

http://idealab.ucdavis.edu/software/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 14,2026. A collection of software tools used for processing and organizing MRI data. The Dicom Importer allows you to to view, assemble, and organize dicom files. Subject Library is a filesystem-based search and reporting tool that can be configured to work with many different organization schemes. This package also contains a python library that can be used to write scripts for custom tasks.

Proper citation: Subject Library (RRID:SCR_002595) Copy   

•   Source: SciCrunch Registry

http://code.google.com/p/panda-tool/

Software matlab toolbox for pipeline processing of diffusion MRI images. For each subject, PANDA can provide outputs in 2 types: i) diffusion parameter data that is ready for statistical analysis; ii) brain anatomical networks constructed by using diffusion tractography. Particularly, there are 3 types of resultant diffusion parameter data: WM atlas-level, voxel-level and TBSS-level. The brain network generated by PANDA has various edge definitions, e.g. fiber number, length, or FA-weighted. The key advantages of PANDA are as follows: # fully-automatic processing from raw DICOM/NIFTI to final outputs; # Supporting both sequential and parallel computation. The parallel environment can be a single desktop with multiple-cores or a computing cluster with a SGE system; # A very friendly GUI (graphical user interface).

Proper citation: PANDA (RRID:SCR_002511) Copy   

•   Source: SciCrunch Registry

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

A set of command line tools allowing 2D and 3D image registration, mainly for medical imaging (although also relevant to other image registration problems).

Proper citation: TAPIR (RRID:SCR_002596) Copy   

•   Source: SciCrunch Registry

http://sve.bmap.ucla.edu/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 14,2026. An automated online framework for performing validation studies of skull-stripping methods. Registered users may download 40 T1 MRI volumes, skull-strip them with the algorithm of their choice, and upload their segmentation results to the SVE website. The server will then compare the 40 skull-stripped results against a set of manually generated brain masks. The server computes a series of measures for the uploaded data, including Jaccard and Dice measures. It also produces images for visualizing the spatial location of the segmentation errors relative to a common space. The results are archived on the server, and the measures are viewable by visitors to the site.

Proper citation: Segmentation Validation Engine (RRID:SCR_002591) Copy   

•   Source: SciCrunch Registry

http://www.cognitiveatlas.org/

Knowledge base (or ontology) that characterizes the state of current thought in cognitive science that captures knowledge from users with expertise in psychology, cognitive science, and neuroscience. There are two basic kinds of knowledge in the knowledge base. Terms provide definitions and properties for individual concepts and tasks. Assertions describe relations between terms in the same way that a sentence describes relations between parts of speech. The goal is to develop a knowledge base that will support annotation of data in databases, as well as supporting improved discourse in the community. It is open to all interested researchers. A fundamental feature of the knowledge base is the desire and ability to capture not just agreement but also disagreement regarding definitions and assertions. Thus, if you see a definition or assertion that you disagree with, then you can assert and describe your disagreement. The project is led by Russell Poldrack, Professor of Psychology and Neurobiology at the University of Texas at Austin in collaboration with the UCLA Center for Computational Biology (A. Toga, PI) and UCLA Consortium for Neuropsychiatric Phenomics (R. Bilder, PI). Most tasks used in cognitive psychology research are not identical across different laboratories or even within the same laboratory over time. A major advantage of anchoring cognitive ontologies to the measurement level is that the strategy for determining changes in task properties is easier than tracking changes in concept definitions and usage. The process is easier because task parameters are usually (if not always) operationalized objectively, offering a clear basis to judge divergence in methods. The process is also easier because most tasks are based on prior tasks, and thus can more readily be considered descendants in a phylogenetic sense.

Proper citation: Cognitive Atlas (RRID:SCR_002793) Copy   

•   Source: SciCrunch Registry

http://www.fmrib.ox.ac.uk/fsl/

Software library of image analysis and statistical tools for fMRI, MRI and DTI brain imaging data. Include registration, atlases, diffusion MRI tools for parameter reconstruction and probabilistic taractography, and viewer. Several brain atlases, integrated into FSLView and Featquery, allow viewing of structural and cytoarchitectonic standard space labels and probability maps for cortical and subcortical structures and white matter tracts. Includes Harvard-Oxford cortical and subcortical structural atlases, Julich histological atlas, JHU DTI-based white-matter atlases, Oxford thalamic connectivity atlas, Talairach atlas, MNI structural atlas, and Cerebellum atlas.

Proper citation: FSL (RRID:SCR_002823) Copy   

•   Source: SciCrunch Registry

http://briansimulator.org/

Software Python package for simulating spiking neural networks. Useful for neuroscientific modelling at systems level, and for teaching computational neuroscience. Intuitive and efficient neural simulator.

Proper citation: Brian Simulator (RRID:SCR_002998) Copy   

•   Source: SciCrunch Registry

http://sumsdb.wustl.edu/sums/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on May 11, 2016. Repository of brain-mapping data (surfaces and volumes; structural and functional data) derived from studies including fMRI and MRI from many laboratories, providing convenient access to a growing body of neuroimaging and related data. WebCaret is an online visualization tool for viewing SumsDB datasets. SumsDB includes: * data on cerebral cortex and cerebellar cortex * individual subject data and population data mapped to atlases * data from FreeSurfer and other brainmapping software besides Caret SumsDB provides multiple levels of data access and security: * Free (public) access (e.g., for data associated with published studies) * Data access restricted to collaborators in different laboratories * Owner-only access for work in progress Data can be downloaded from SumsDB as individual files or as bundles archived for offline visualization and analysis in Caret WebCaret provides online Caret-style visualization while circumventing software and data downloads. It is a server-side application running on a linux cluster at Washington University. WebCaret "scenes" facilitate rapid visualization of complex combinations of data Bi-directional links between online publications and WebCaret/SumsDB provide: * Links from figures in online journal article to corresponding scenes in WebCaret * Links from metadata in WebCaret directly to relevant online publications and figures

Proper citation: SumsDB (RRID:SCR_002759) Copy   

•   Source: SciCrunch Registry

http://brainmap.org/

A community database of published functional and structural neuroimaging experiments with both metadata descriptions of experimental design and activation locations in the form of stereotactic coordinates (x,y,z) in Talairach or MNI space. BrainMap provides not only data for meta-analyses and data mining, but also distributes software and concepts for quantitative integration of neuroimaging data. The goal of BrainMap is to develop software and tools to share neuroimaging results and enable meta-analysis of studies of human brain function and structure in healthy and diseased subjects. It is a tool to rapidly retrieve and understand studies in specific research domains, such as language, memory, attention, reasoning, emotion, and perception, and to perform meta-analyses of like studies. Brainmap contains the following software: # Sleuth: database searches and Talairach coordinate plotting (this application requires a username and password) # GingerALE: performs meta-analyses via the activation likelihood estimation (ALE) method; also converts coordinates between MNI and Talairach spaces using icbm2tal # Scribe: database entry of published functional neuroimaging papers with coordinate results

Proper citation: brainmap.org (RRID:SCR_003069) Copy   

•   Source: SciCrunch Registry

http://www.socr.ucla.edu/

A hierarchy of portable online interactive aids for motivating, modernizing probability and statistics applications. The tools and resources include a repository of interactive applets, computational and graphing tools, instructional and course materials. The core SOCR educational and computational components include the following suite of web-based Java applets: * Distributions (interactive graphs and calculators) * Experiments (virtual computer-generated games and processes) * Analyses (collection of common web-accessible tools for statistical data analysis) * Games (interfaces and simulations to real-life processes) * Modeler (tools for distribution, polynomial and spectral model-fitting and simulation) * Graphs, Plots and Charts (comprehensive web-based tools for exploratory data analysis), * Additional Tools (other statistical tools and resources) * SOCR Java-based Statistical Computing Libraries * SOCR Wiki (collaborative Wiki resource) * Educational Materials and Hands-on Activities (varieties of SOCR educational materials), * SOCR Statistical Consulting In addition, SOCR provides a suite of tools for volume-based statistical mapping (http://wiki.stat.ucla.edu/socr/index.php/SOCR_EduMaterials_AnalysesCommandLine) via command-line execution and via the LONI Pipeline workflows (http://www.nitrc.org/projects/pipeline). Course instructors and teachers will find the SOCR class notes and interactive tools useful for student motivation, concept demonstrations and for enhancing their technology based pedagogical approaches to any study of variation and uncertainty. Students and trainees may find the SOCR class notes, analyses, computational and graphing tools extremely useful in their learning/practicing pursuits. Model developers, software programmers and other engineering, biomedical and applied researchers may find the light-weight plug-in oriented SOCR computational libraries and infrastructure useful in their algorithm designs and research efforts. The three types of SOCR resources are: * Interactive Java applets: these include a number of different applets, simulations, demonstrations, virtual experiments, tools for data visualization and analysis, etc. All applets require a Java-enabled browser (if you see a blank screen, see the SOCR Feedback to find out how to configure your browser). * Instructional Resources: these include data, electronic textbooks, tutorials, etc. * Learning Activities: these include various interactive hands-on activities. * SOCR Video Tutorials (including general and tool-specific screencasts).

Proper citation: Statistics Online Computational Resource (RRID:SCR_003378) Copy   

•   Source: SciCrunch Registry

http://www.loni.usc.edu/BIRN/Projects/Mouse/

Animal model data primarily focused on mice including high resolution MRI, light and electron microscopic data from normal and genetically modified mice. It also has atlases, and the Mouse BIRN Atlasing Toolkit (MBAT) which provides a 3D visual interface to spatially registered distributed brain data acquired across scales. The goal of the Mouse BIRN is to help scientists utilize model organism databases for analyzing experimental data. Mouse BIRN has ended. The next phase of this project is the Mouse Connectome Project (https://www.nitrc.org/projects/mcp/). The Mouse BIRN testbeds initially focused on mouse models of neurodegenerative diseases. Mouse BIRN testbed partners provide multi-modal, multi-scale reference image data of the mouse brain as well as genetic and genomic information linking genotype and brain phenotype. Researchers across six groups are pooling and analyzing multi-scale structural and functional data and integrating it with genomic and gene expression data acquired from the mouse brain. These correlated multi-scale analyses of data are providing a comprehensive basis upon which to interpret signals from the whole brain relative to the tissue and cellular alterations characteristic of the modeled disorder. BIRN's infrastructure is providing the collaborative tools to enable researchers with unique expertise and knowledge of the mouse an opportunity to work together on research relevant to pre-clinical mouse models of neurological disease. The Mouse BIRN also maintains a collaborative Web Wiki, which contains announcements, an FAQ, and much more.

Proper citation: Mouse Biomedical Informatics Research Network (RRID:SCR_003392) Copy   

•   Source: SciCrunch Registry

https://fitbir.nih.gov/

Platform for Traumatic Brain Injury relevant data. System was developed to share data across entire TBI research field and to facilitate collaboration between laboratories and interconnectivity between informatics platforms. FITBIR implements interagency Common Data Elements for TBI research and provides tools and resources to extend data dictionary. Established submission strategy to ensure high quality and to provide maximum benefit to investigators. Qualified researchers can request access to data stored in FITBIR and/or data stored at federated repositories.

Proper citation: Federal Interagency Traumatic Brain Injury Research Informatics System (RRID:SCR_006856) Copy   

•   Source: SciCrunch Registry

http://scalablebrainatlas.incf.org/

A web-based, interactive brain atlas viewer, containing a growing number of atlas templates for various species, including mouse, macaque and human. Standard features include fast brain region lookup, point and click to select a region and view its full 3D extent, mark a stereotaxic coordinate and view all regions in a hierarchy. Built-in extensions are the CoCoMac plugin, which provides a spatial display of Macaque connectivity, and a service to transform stereotaxic coordinates to and from the INCF Waxholm space for the mouse. Three dimensional renderings of brain regions are available through a Matlab interface (local installation of Matlab required). The SBA is designed to be customizable. External users can create plugins, hosted on their own servers, to interactively attach images or data to spatial atlas locations. This fully web-based display engine for brain atlases and topologies allows client websites to show brain region related data in a 3D interactive context. Currently available atlases are: * Macaque: The Paxinos Rhesus Monkey atlas (2000) * Macaque: Various templates available through Caret, registered to F99 space: Felleman and Van Essen (1991), Lewis and Van Essen (2000), Regional Map from K��tter and Wanke (2005), Paxinos Rhesus Monkey (2000) * Macaque: The NeuroMaps Macaque atlas (2008) * Mouse: The INCF Waxholm Space for the mouse (2011). Previous versions available. * Mouse: The Allen Mouse Brain volumetric atlas (ABA07) * Human: The LPBA40 parcellation, registered to SRI24 space A variety of services are being developed around the templates contained in the Scalable Brain Atlas. For example, you can include thumbnails of brain regions in your own webpage. Other applications include: * Analyze atlas templates in Matlab * List all regions belonging to the given template * List of supported atlas templates * Find region by coordinate * Color-coded PNG (bitmap) or SVG (vector) image of a brain atlas slice * Region thumbnail in 2D (slice) or 3D (stack of slices) The Scalable Brain Atlas is created by Rembrandt Bakker and Gleb Bezgin, under supervision of Rolf K��tter in the NeuroPhysiology and -Informatics group of the Donders Institute, Radboud UMC Nijmegen.

Proper citation: Scalable Brain Atlas (RRID:SCR_006934) Copy   

•   Source: SciCrunch Registry

http://www.cns.atr.jp/dni/en/downloads/tools-for-brain-behavior-data-sharing/

This is MATLAB library to create Neuroshare data format. You can convert your own data into Neuroshare format file.

Proper citation: Matlab Neuroshare Library (RRID:SCR_006957) Copy   

•   Source: SciCrunch Registry

https://itunes.apple.com/gb/app/neuropub-visualizer/id405721542?mt=8

A NIfTI visualizer for statistical brain images (fMRI, VBM, etc) the iPad. The visualizer displays these images as overlay on the MNI standard brain. You can use it to store all your statistical images from your fMRI / VBM / TBSS studies and visualise them in 2D and 3D. Use NeuroPub as a library for your statistical images. It's the perfect app to bring to meetings, conferences, etc, and show your latest results.

Proper citation: NeuroPub Visualizer (RRID:SCR_006797) Copy   

•   Source: SciCrunch Registry