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https://github.com/mjacquem/RodentThickness

An automatic cortical thickness measurement tool for rat brains. The pipeline consists of four steps: preprocessing to create binary mask and label map, thickness measurement which produces laplacian field and thickness map in order, run particle correspondence followed by statistical analysis resulting in mean thickness color map and t-test result. By running RodentThickness, you will need to fill in informations in a Graphical User Interface, and then compute. You can also run the tool in command line without using the GUI. Using the GUI, you will be able to save or load a dataset file or a configuration file. The tool needs these other tools to work, so be sure to have these installed on your computer: * ImageMath * measureThicknessFilter * GenParaMeshCLP * ParaToSPHARMMeshCLP * ShapeWorksRun * ShapeWorksGroom * SegPostProcessCLP * BinaryToDistanceMap * MeshPointsIntensitysampling

Proper citation: Rodent Cortical Thickness Analysis (RRID:SCR_002539) Copy   

•   Source: SciCrunch Registry

http://www.kcl.ac.uk/iop/depts/neuroimaging/research/imaginganalysis/Software/rBET.aspx

A modified version of the Brain Extraction Tool (BET) that can process rodent brains.

Proper citation: Rodent Brain Extraction Tool (RRID:SCR_002538) Copy   

•   Source: SciCrunch Registry

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

Non-rigid registration / distortion correction tools for enhanced functional localization through the registration of EPI fMRI to high-resolution anatomical MRI.

Proper citation: NPTK (RRID:SCR_002496) Copy   

•   Source: SciCrunch Registry

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

Support and community integration for the enhanced NITRC services of the Image Repository (IR) and the Computational Environment (CE). The NITRC Computational Environment, an on-demand, cloud based computational virtual machine pre-installed with popular NITRC neuroimaging tools built using NeuroDebian. NITRC Image Repository is built upon XNAT and supports both NIfTI and DICOM images. The NITRC-IR offers 3,733 Subjects, and 3,743 Imaging Sessions searchable across seven projects to promote re-use and integration of valuable NIH-funded data.

Proper citation: NITRC Enhanced Services (RRID:SCR_002494) Copy   

•   Source: SciCrunch Registry

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

Open-source utilities that are C++ based command line applications that allow image analysis and processing using ITK or VTK libraries. Specifically the following utilities are contained thus far: * ImageMath - the swiss army knife image modification * ImageStat - compute stats on images * IntensityRescaler - rescale/normalize intensities using a prior brain tissue segmentation * convertITKformats - convert 3D images in all ITK formats (NRRD, NIFTI, GIPL, Meta etc) * DWI_NiftiNrrdConversion - convert DWI and DTI from/to NRRD and NIFTI, works with UNC DTI tools and FSL * CropTools - crops 3D and 4D images * PolydataMerge - Merges VTK polydata files * PolydataTransform - Transforms polydata files * TransformDeformationField - concatenates or average deformation fields (H-fields or displacement fields) * DTIAtlasBuilder - Creates a DTI average from multiple DTI images

Proper citation: NIRAL Utilities (RRID:SCR_002490) Copy   

•   Source: SciCrunch Registry

http://pysurfer.github.com

Software Python tool for visualization and interaction with cortical surface representations of neuroimaging data from Freesurfer. It extends Mayavi powerful visualization engine with interface for working with MRI and MEG data. PySurfer offers command-line interface designed to broadly replicate Freesurfer program as well as Python library for writing scripts to explore complex datasets., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: PySurfer (RRID:SCR_002524) Copy   

•   Source: SciCrunch Registry

http://mgui.wikidot.com

An open source Java-based project intended to provide a graphic user interface (GUI) for interactions between scientists (or enthusiasts) and their data. In its current (beta) form, mgui offers the following functionality: * Cross-platform functionality (with a Java Runtime installation, runs on Linux, Windows, Mac, or Solaris) * 2D rendering of data based upon Java2D, and 3D rendering based upon Java3D * The ability to organize complex datasets into intuitive mgui projects * A processing pipeline interface which allows users to process their datasets with any available Java or native software tools * An extensible I/O framework accommodating a variety of standard and non-standard file formats * Database connectivity using JDBC * Graph visualization based upon the JUNG library * An intuitive Swing-based GUI for managing, querying, and visualizing data * Various CAD-type tools for editing and creating geometry * A computational modelling framework

Proper citation: ModelGUI (RRID:SCR_002441) Copy   

•   Source: SciCrunch Registry

http://air.bmap.ucla.edu/MultiTracer2/MultiTracer.html

A Java application that allows images to be displayed in three dimensions. The tool allows anatomic structures to be traced and the tracings to be saved in a format that facilitates review and revision. It supports NIfTI-1.1 format float, double and signed and unsigned byte, short, and integer formats and provides legacy support for Analyze 7.5 8 and 16 bit images. It provides image display, editing, delineation of structure boundaries, export of traced contours and generation of masked volumes. Images are displayed in 3 orthogonal views. Time series can be displayed as averaged or contrast images and time courses can be visualized graphically. Version 2 provides enhancements to the original MultiTracer feature set.

Proper citation: MultiTracer (RRID:SCR_002445) Copy   

•   Source: SciCrunch Registry

http://slicedrop.com

A viewer for medical imaging data that supports a variety of scientific file formats out-of-the-box (see https://github.com/xtk/X/wiki/X:Fileformats for a complete list). We think that the best way to render your files is without any necessary conversions. Just drop'em on a website and they are ready to render. Just drag'n'drop some medical imaging files on this website or try one of the four examples in the right corner. Then, play with the panels on the left and click, drag and rotate the 3d content. Slice:Drop uses WebGL and HTML5 Canvas to render the data in 2D and 3D. We use our own open-source toolkit to perform the rendering, called XTK ( http://goxtk.com ).

Proper citation: Slice:Drop (RRID:SCR_002557) Copy   

•   Source: SciCrunch Registry

http://brainmap.org/sleuth/

Software application that searches the BrainMap Database for papers of interest, reads their corresponding meta-data, and plots their results as coordinates on a standard glass brain in Talairach space.

Proper citation: Sleuth (RRID:SCR_002555) Copy   

•   Source: SciCrunch Registry

http://www.med.unc.edu/bric/ideagroup/free-softwares/hammer

Software for both groupwise registration and longitudinal registration, which are the necessary steps for many brain-related applications. Specifically, groupwise registration is important for unbiased analysis of a large set of MR brain images. Therefore, in this software package, they have included two of their recently-developed groupwise registration algorithms: 1) Improved unbiased groupwise registration guided with the sharp group-mean image, and 2) Hierarchical feature-based groupwise registration with implicit template (Groupwise-HAMMER for short). On the other hand, they also included their recently-developed groupwise longitudinal registration algorithm that aligns not only the longitudinal image sequence for each subject, but also align all longitudinal image sequences of all subjects to the common space simultaneously.

Proper citation: GLIRT (RRID:SCR_002390) Copy   

•   Source: SciCrunch Registry

http://fmri.wfubmc.edu/software/Bpm

Software toolbox that performs SPM analysis with voxel-wise imaging covariates. The BPM toolbox incorporates information obtained from other modalities as regressors in a voxel-wise analysis, thereby permitting investigation of more sophisticated hypotheses. The BPM toolbox has been developed in Matlab with a user-friendly interface for performing analyses, including voxel-wise multimodal correlation, ANCOVA, and multiple regression. It has a high degree of integration with the SPM (statistical parametric mapping) software relying on it for visualization and statistical inference. Furthermore, statistical inference for a correlation field, rather than a widely used T-field, has been implemented in the correlation analysis for more accurate results. Requirements: * SPM2 or SPM5 * MATLAB version 6.5 or higher

Proper citation: WFU Biological Parametric Mapping Toolbox (RRID:SCR_002613) Copy   

•   Source: SciCrunch Registry

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

Software toolbox for statistical image clustering, peak detection and data extraction developed to allow the user to have flexibility of clustering their data. Based on your threshold, it will cluster your data and find the peaks within each cluster. Additionally, it has been combined with a data extraction tool that allows one to extract the data from all the scans of the analysis from all the clusters, along with several other extraction options, with a single command.

Proper citation: peak nii (RRID:SCR_002572) Copy   

•   Source: SciCrunch Registry

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

An advanced viewer for electrophysiological and behavioral data: it can display local field potentials (EEG), neuronal spikes, behavioral events, as well as the position of the animal in the environment. It also features limited editing capabilities.

Proper citation: NeuroScope (RRID:SCR_002455) Copy   

•   Source: SciCrunch Registry

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://www.tractor-mri.org.uk/

Software application that includes R packages for reading, writing and visualising magnetic resonance images stored in Analyze, NIfTI and DICOM file formats (DICOM support is read only). It also contains functions specifically designed for working with diffusion MRI and tractography, including a standard implementation of the neighbourhood tractography approach to white matter tract segmentation. A shell script is also provided to run experiments with TractoR without interacting with R.

Proper citation: TractoR: Tractography with R (RRID:SCR_002602) 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.bic.mni.mcgill.ca/software/N3/

The perl script nu_correct implements a novel approach to correcting for intensity non-uniformity in MR data that achieves high performance without requiring supervision. By making relatively few assumptions about the data, the method can be applied at an early stage in an automated data analysis, before a tissue intensity or geometric model is available. Described as Non-parametric Non-uniform intensity Normalization (N3), the method is independent of pulse sequence and insensitive to pathological data that might otherwise violate model assumptions. To eliminate the dependence of the field estimate on anatomy, an iterative approach is employed to estimate both the multiplicative bias field and the distribution of the true tissue intensities. Preprocessing of MR data using N3 has been shown to substantially improve the accuracy of anatomical analysis techniques such as tissue classification and cortical surface extraction.

Proper citation: MNI N3 (RRID:SCR_002484) Copy   

•   Source: SciCrunch Registry

https://github.com/gbook/nidb

Neuroimaging database designed to allow simple importing, searching, and sharing of imaging data. NIDB also provides automated pipelining with importing of results back into NIDB which can be searched along with imaging meta data.

Proper citation: NIDB - Neuroinformatics Database (RRID:SCR_002488) Copy   

•   Source: SciCrunch Registry