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

Construct and analyse brain network is a brain network visualization tool, which can help researchers to visualize construct and analyse resting state functional brain networks from different levels in a quick, easy and flexible way. Entrance parameter of construct and analyse brain network is export parameters of dparsf software.It would be greatly appreciated if you have any suggestions about the package or manual.

Proper citation: BrainNetworkConstructionAnalysisPlatform (RRID:SCR_000854) Copy   

•   Source: SciCrunch Registry

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

Communnity project to help support the efforts of investigators using Philips Healthcare systems. This clearingsite helps users find forums, mailinglists, etc. that support this community. If you have suggestions for inclusion, let the project admin know!

Proper citation: Philips Users Community (RRID:SCR_001438) Copy   

•   Source: SciCrunch Registry

http://incf.org/programs/atlasing/projects/waxholm-space

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 1st, 2023. Coordinate based reference space for the mapping and registration of neuroanatomical data. Users can download image volumes representing the canonical Waxholm Space (WHS) adult C57BL/6J mouse brain, which include T1-, T2*-, and T2-Weighted MR volumes (generated at the Duke Center for In-Vivo Microscopy), Nissl-stained optical histology (acquired at Drexel University), and a volume of labels. All volumes are represented at 21.5μ isotropic resolution. Datasets are provided as gzipped NIFTI files.

Proper citation: Waxholm Space (RRID:SCR_001592) Copy   

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https://www.mristudio.org/

An image processing program running under Windows suitable for such tasks as tensor calculation, color mapping, fiber tracking, and 3D visualization. Most of operations can be done with only a few clicks. This tool evolved from DTI Studio. Tools in the program can be grouped in the following way: * Image Viewer * Diffusion Tensor Calculations * Fiber Tracking and Editing * 3D Visualization * Image File Management * Region of Interesting (ROI) Drawing and Statistics * Image Registration

Proper citation: MRI Studio (RRID:SCR_001398) Copy   

•   Source: SciCrunch Registry

http://surfer.nmr.mgh.harvard.edu/

Open source software suite for processing and analyzing human brain MRI images. Used for reconstruction of brain cortical surface from structural MRI data, and overlay of functional MRI data onto reconstructed surface. Contains automatic structural imaging stream for processing cross sectional and longitudinal data. Provides anatomical analysis tools, including: representation of cortical surface between white and gray matter, representation of the pial surface, segmentation of white matter from rest of brain, skull stripping, B1 bias field correction, nonlinear registration of cortical surface of individual with stereotaxic atlas, labeling of regions of cortical surface, statistical analysis of group morphometry differences, and labeling of subcortical brain structures.Operating System: Linux, macOS.

Proper citation: FreeSurfer (RRID:SCR_001847) Copy   

•   Source: SciCrunch Registry

http://www.nesys.uio.no/Atlas3D/

A multi-platform visualization tool which allows import and visualization of 3-D atlas structures in combination with tomographic and histological image data. The tool allows visualization and analysis of the reconstructed atlas framework, surface modeling and rotation of selected structures, user-defined slicing at any chosen angle, and import of data produced by the user for merging with the atlas framework. Tomographic image data in NIfTI (Neuroimaging Informatics Technology Initiative) file format, VRML and PNG files can be imported and visualized within the atlas framework. XYZ coordinate lists are also supported. Atlases that are available with the tool include mouse brain structures (3-D reconstructed from The Mouse Brain in Stereotaxic Coordinates by Paxinos and Franklin (2001)) and rat brain structures (3-D reconstructed from The Rat Brain in Stereotaxic Coordinates by Paxinos and Watson (2005)). Experimental data can be imported in Atlas3D and warped to atlas space, using manual linear registration, with the possibility to scale, rotate, and position the imported data. This facilitates assignment of location and comparative analysis of signal location in tomographic images.

Proper citation: Atlas3D (RRID:SCR_001808) Copy   

•   Source: SciCrunch Registry

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

Open source whole genome association analysis toolset, designed to perform range of basic, large scale analyses in computationally efficient manner. Used for analysis of genotype/phenotype data. Through integration with gPLINK and Haploview, there is some support for subsequent visualization, annotation and storage of results. PLINK 1.9 is improved and second generation of the software.

Proper citation: PLINK (RRID:SCR_001757) Copy   

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

An international working group dedicated to improving access to neuroimaging results in a free and open-access manner. It seeks to establish a universal coordinate database, including both past papers and future studies. Their current project involves the creation of a comprehensive database of neuroimaging results searchable based on standardized coordinates. Once complete, this will allow anyone to find all of the articles that report a coordinate, or set of coordinates, easily and without cost. Eventually, they hope to expand this database to include not only coordinates, but statistical parametric maps as well. Formation of such a database will increase the likelihood of relevant papers being found and cited, and also be a very useful tool for those interested in meta-analysis, and hopefully clarify structure-function relationships. They are interested in hearing from people who might be willing to contribute to their projects, particularly those with programming experience. The number of published neuroimaging studies is increasing rapidly and it is not feasible to read them all. If a computer database could store key information from published fMRI papers and make that information easier to search or share, this would have substantial benefits for the neuroimaging community. Projects like AMAT, Brainmap, Brede and SumsDB have started to tackle this problem. NIDAG wants to formalize and improve these databases so that they meet the needs of the neuroimaging community. Formal meta-analysis of published data is a valuable way to assess the consistency and reliability of experimental results. A database of neuroimaging results would facilitate meta-analyses, in conjunction with tools like GingerALE and Multi-level Kernel Density Analysis.

Proper citation: NIDAG: Neuroimaging Data Access Group (RRID:SCR_001674) Copy   

•   Source: SciCrunch Registry

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

Software package for brain image manipulation and analysis, focusing on fMRI and lesion analysis. VoxBo can be used independently or in conjunction with other packages. It provides GLM-based statistical tools, an architecture for interoperability with other tools (they encourage users to incorporate SPM and FSL into their processing pipelines), an automation system, a system for parallel distributed computing, numerous stand-alone tools, decent wiki-based documentation, and lots more.

Proper citation: VoxBo (RRID:SCR_002166) Copy   

•   Source: SciCrunch Registry

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

Software package that is a powerful graphical interface that displays, segments, aligns, manipulates, and blends image (pixel) and geometry (real-world coordinates) data simultaneously. Several applications are directly built into MIVA. Registration modes include interactive affine transformations. Fiducial registration tools facilitate rapid alignments for inter-modality volumes. Interactive Region of Interst (ROI) and Volume-of-Interest (VOI) tools exist to segment medical images. Virtually unique to MIVA are its 3D geometry tools and their compatibility with pixel based medical images. A full 3D interactive rat brain atlas is in an fMRI module which walks one through the necessary steps of fMRI. A multiple material surface routine takes segmented medical slices and creates 3D triangulated surfaces that align along all region boarders without overlap or gaps. These surfaces are the direct input into the MIVA tetrahedral mesh generator.

Proper citation: Medical Image Visualization and Analysis (RRID:SCR_002315) Copy   

•   Source: SciCrunch Registry

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

This simple visualization tool allows to load several images at the same time. The cursor across all windows are coupled and you can move/zoom on all the images at the same time. Very useful for quality control, image comparison.

Proper citation: MriWatcher (RRID:SCR_002318) Copy   

•   Source: SciCrunch Registry

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

An efficient level set framework for multi-object segmentation. Its representation inherently prevents overlaps and gaps and it readily preserves object topology and object relationships. MGDM is efficient, storing only a fixed number of functions for any number of objects, and therefore scales well to segmentation problems with many classes and large images. It's representation also avoids some instabilities in other multi-class level set methods. MGDM is cross-platform; MATLAB wrappers, Java source and API are provided, with MIPAV plugins forthcoming.

Proper citation: MGDM: Multi Geometric Deformable Model (RRID:SCR_002311) 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://www.nitrc.org/projects/msseg

Training material for the MS lesion segmentation challenge 2008 to compare different algorithms to segment the MS lesions from brain MRI scans. Data used for the workshop is composed of 54 brain MRI images and represents a range of patients and pathology which was acquired from Children's Hospital Boston and University of North Carolian. Data has initially been randomized into three groups: 20 training MRI images, 24 testing images for the qualifying and 8 for the onsite contest at the 2008 workshop. The downloadable online database consists now of the training images (including reference segmentations) and all the 32 combined testing images (without segmentations). The naming has not been changed in comparison to the workshop compeition in order to allow easy comparison between the workshop papers and the online database papers. One dataset has been removed (UNC_test1_Case02) due to considerable motion present only in its T2 image (without motion artifacts in T1 and FLAIR). Such a dataset unfairly penalizes methods that use T2 images versus methods that don't use the T2 image. Currently all cases have been segmented by expert raters at each institution. They have significant intersite variablility in segmentation. MS lesion MRI image data for this competition was acquired seperately by Children's Hospital Boston and University of North Carolina. UNC cases were acquired on Siemens 3T Allegra MRI scanner with slice thickness of 1mm and in-plane resolution of 0.5mm. To ease the segmentation process all data has been rigidly registered to a common reference frame and resliced to isotrophic voxel spacing using b-spline based interpolation. Pre-processed data is stored in NRRD format containing an ASCII readable header and a separate uncompressed raw image data file. This format is ITK compatible. If you want to join the competition, you can download data set from links here, and submit your segmentation results at http://www.ia.unc.edu/MSseg after registering your team. They require team name, password, and email address for future contact. Once experiment is completed, you can submit the segmentation data in a zip file format. Please refer submission page for uploading data format.

Proper citation: MS lesion segmentation challenge 2008 (RRID:SCR_002425) Copy   

•   Source: SciCrunch Registry

https://github.com/BRAINSia/BRAINSTools/tree/master/BRAINSFit

A program for registering images with with mutual information based metric. Several registration options are given for 3,6, 9,12,16 parameter (i.e. translate, rigid, scale, scale/skew, full affine) based constraints for the registration. The program 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: BRAINSFit (RRID:SCR_002340) Copy   

•   Source: SciCrunch Registry

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

Software to fit s-reps to segmented anatomic objects, to compute probability distributions on these s-reps, to train and to apply classifiers between two classes of anatomic objects, and to apply hypothesis testing to determine which geometric or physiological features vary significantly between two classes. Software for object segmentation from medical images may also be included. S-reps are skeletal models for anatomic objects especially suited for computing probability distributions from populations of these objects and for providing object-related coordinates for the interior of these objects. They allow classification and hypothesis testing using their geometric features and physiological features derived from medical images. They also allow the definition of shape spaces, probability-based geometric typicality functions, and appearance models used for segmentation or registration. A variety of successful applications to objects in neuroimages have already been performed.

Proper citation: S-rep Fitting Statistics and Segmentation (RRID:SCR_002540) Copy   

•   Source: SciCrunch Registry

http://scralyze.sourceforge.net

A powerful software for model-based analysis of peripheral psychophysiology (e.g. skin conductance, heart rate, pupil size etc.). General linear modelling and dynamic causal modelling of these signals provide for inference on neural states/processes. SCRalyze includes flexible data import and display, statistical inference and results display and export. Easy programming of add-ons for new data formats, signal channels, and models.

Proper citation: SCRalyze (RRID:SCR_002542) Copy   

•   Source: SciCrunch Registry

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

Project to discuss, debate, develop and deploy ontological practices for the fMRI community.

Proper citation: Resource Ontology Discussion Group (RRID:SCR_002536) Copy   

•   Source: SciCrunch Registry

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