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

The packaged tools perform Local Binary Pattern on Three Orthogonal Planes (LBP-TOP) analysis on MR brain images. One can use them to extract LBP texture features for machine learning applications or other advance analysis. Bash scripts performing simple preprocessing with FSL and AFNI as well as LBP mapping programs written by Java are both including in this package. The output is the histogram describing the brain morphology.

Proper citation: Local Binary Pattern Analysis Tools for MR Brain Images (RRID:SCR_000412) Copy   

•   Source: SciCrunch Registry

http://micro-manager.org

Software package for control of automated microscopes. Cross-platform desktop application, to control motorized microscopes, scientific cameras, stages, illuminators, and other microscope accessories.

Proper citation: uManager (RRID:SCR_000415) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/meshmetric3d/

Software visualization tool based on the VTK library. Its main feature is to measure and display surface-to-surface distance between two triangle meshes using user-specified uniform sampling. Offers all the basic tools to visualize meshes such as color, opacity, smoothing, down sampling or type of representation.

Proper citation: 3DMeshMetric (RRID:SCR_000043) Copy   

•   Source: SciCrunch Registry

http://cbrain.mcgill.ca/loris

A modular and extensible web-based data management system that integrates all aspects of a multi-center study, from heterogeneous data acquisition to storage, processing and ultimately dissemination, within a streamlined platform. Through a standard web browser, users are able to perform a wide variety of tasks, such as data entry, 3D image visualization and data querying. LORIS also stores data independently from any image processing pipeline, such that data can be processed by external image analysis software tools. LORIS provides a secure web-based and database-driven infrastructure to automate the flow of clinical data for complex multi-site neuroimaging trials and studies providing researchers with the ability to easily store, link, and access significant quantities of both scalar (clinical, psychological, genomic) and multi-dimensional (imaging) data. LORIS can collect behavioral, neurological, and imaging data, including anatomical and functional 3D/4D MRI models, atlases and maps. LORIS also functions as a project monitoring and auditing platform to oversee data acquisition across multiple study sites. Confidentiality during multi-site data sharing is provided by the Subject Profile Management System, which can perform automatic removal of confidential personal information and multiple real-time quality control checks. Additionally, web interactions with the LORIS portal take place over an encrypted channel via SSL, ensuring data security. Additional features such as Double Data Entry and Statistics and Data Query GUI are included.

Proper citation: LORIS - Longitudinal Online Research and Imaging System (RRID:SCR_000590) Copy   

•   Source: SciCrunch Registry

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

Autism research program that makes available post-mortem brain tissue to qualified scientists all over the world. Working directly with tissue banks, organ procurement agencies, medical examiners and the general public, this is the largest program dedicated to increasing and enhancing the availability of post-mortem brain tissue for basic research in autism. To date, the ATP has collected and stored more than 170 brains in their repositories at Harvard (US) and Oxford (UK). These brains are processed by formalin fixation and/or snap frozen to properly provide high quality tissue of all brain regions, in support of biological research in autism. The ATP is unique in that they diligently pursue all available clinical data (pre and post mortem) on tissue donors in order to create the most biologically relevant brain repository for autism research. These data, together with tissue resources from both banks and associated repositories, are presented to all interested researchers through their extensive web-based data portal (login required). The ATP is not a brain bank, but works directly with the Harvard Brain Tissue Resource Center in Boston (HBTRC), Massachusetts to serve as its tissue repository. This program augments brain bank functions by: * Creating the most biologically relevant brain tissue repository possible * Fully covering all costs associated with brain extraction and transfer to the repositories at Harvard (US and Canada) and Oxford (UK). * Providing scientific oversight of tissue distributions * Overseeing and managing all tissue grants * Clinically phenotyping and acquiring extensive medical data on all of their donors * Providing continuing family support and communication to all of their donors * Directly supporting researchers to facilitate autism research * Maintaining a robust web based data management and secure on-line global interface system * Developing and supporting ATP established scientific initiatives * Actively providing public outreach and education The ATP is not a clinical organ procurement agency, but rather they facilitate the wishes of donors and families to donate their tissue to autism research. Through the ATP's established international infrastructure, they work with any accredited tissue bank, organ procurement agency, or medical examiner that receives a family's request to donate their loved one's tissue to the program. Once contacted, the ATP will insure that the family's request to donate their loved one's tissue is faithfully met, covering all costs to the family and partnering agency as well as ensuring the tissues' proper and rapid transport to the ATP's repository at the Harvard Brain Tissue Resource Center (HBTRC) in Boston, Massachusetts.

Proper citation: Autism Tissue Program (RRID:SCR_000651) Copy   

•   Source: SciCrunch Registry

http://www.talairach.org/

Software automated coordinate based system to retrieve brain labels from the 1988 Talairach Atlas. Talairach Daemon database contains anatomical names for brain areas using x-y-z coordinates defined by the 1988 Talairach Atlas.

Proper citation: Talairach Daemon (RRID:SCR_000448) Copy   

•   Source: SciCrunch Registry

http://fcp-indi.github.io

A configurable, open-source, Nipype-based, automated processing pipeline for resting state functional MRI (R-fMRI) data, for use by both novice and expert users. C-PAC was designed to bring the power, flexibility and elegance of the Nipype platform to users in a plug and play fashion?without requiring the ability to program. Using an easy to read, text-editable configuration file, C-PAC can rapidly orchestrate automated R-fMRI processing procedures, including: - quality assurance measurements - image preprocessing based upon user specified preferences - generation of functional connectivity maps (e.g., correlation analyses) - customizable extraction of time-series data - generation of local R-fMRI metrics (e.g., regional homogeneity, voxel-matched homotopic connectivity, fALFF/ALFF) C-PAC makes it possible to use a single configuration file to launch a factorial number of pipelines differing with respect to specific processing steps.

Proper citation: C-PAC (RRID:SCR_000862) Copy   

•   Source: SciCrunch Registry

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

An I/O library for Matlab/Octave Matlab and Octave library for reading and writing Nifti-1 files. cbiNifti is intended to be a small, self-contained library that makes minimal assumptions about what Nifti files should look like and allow users easy access to the raw data. cbiNifti handles compressed file formats for reading and writing, using Unix pipes for compression and decompression. More information and code examples at: http://www.pc.rhul.ac.uk/staff/J.Larsson/software.html

Proper citation: cbiNifti: Matlab/Octave Nifti library (RRID:SCR_000860) Copy   

•   Source: SciCrunch Registry

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://rfmri.org/DPARSF

A MATLAB toolbox forpipeline data analysis of resting-state fMRI that is based on Statistical Parametric Mapping (SPM) and a plug-in software within DPABI. After the user arranges the Digital Imaging and Communications in Medicine (DICOM) files and click a few buttons to set parameters, DPARSF will then give all the preprocessed (slice timing, realign, normalize, smooth) data and results for functional connectivity, regional homogeneity, amplitude of low-frequency fluctuation (ALFF), fractional ALFF, degree centrality, voxel-mirrored homotopic connectivity (VMHC) results. DPARSF can also create a report for excluding subjects with excessive head motion and generate a set of pictures for easily checking the effect of normalization. In addition, users can also use DPARSF to extract time courses from regions of interest. DPARSF basic edition is very easy to use while DPARSF advanced edition (alias: DPARSFA) is much more flexible and powerful. DPARSFA can parallel the computation for each subject, and can be used to reorient images interactively or define regions of interest interactively. Users can skip or combine the processing steps in DPARSF advanced edition freely.

Proper citation: DPARSF (RRID:SCR_002372) Copy   

•   Source: SciCrunch Registry

http://niftyrec.scienceontheweb.net/

Software toolbox that includes reconstruction tools for emission and transmission imaging modalities, including Single Photon Emission Computed Tomography (SPECT), Positron Emission Tomography (PET), cone-beam X-Ray CT and parallel-beam X-Ray CT. At the core of NiftyRec are efficient, GPU accelerated, projection, back-projection and iterative reconstruction algorithms. The easy to use Matlab and Python interfaces of NiftyRec enable fast prototyping and development of reconstruction algorithms. NiftyRec includes standard iterative reconstruction algorithms such as Maximum Likelihood Expectation Maximisation (MLEM), Ordered Subsets Expectation Maximisation (OSEM) and One Step Late Maximum A Posteriori Expectation Maximisation (OSL-MAPEM), for multiple imaging modalities.

Proper citation: NiftyRec (RRID:SCR_002499) Copy   

•   Source: SciCrunch Registry

http://www.warwick.ac.uk/snpm

A toolbox for Statistical Parametric Mapping (SPM) that provides an extensible framework for voxel level non-parametric permutation/randomization tests of functional Neuroimaging experiments with independent observations. SnPM uses the General Linear Model to construct pseudo t-statistic images, which are then assessed for significance using a standard non-parametric multiple comparisons procedure based on randomization/permutation testing. It is most suitable for single subject PET/SPECT analyses, or designs with low degrees of freedom available for variance estimation. In these situations the freedom to use weighted locally pooled variance estimates, or variance smoothing, makes the non-parametric approach considerably more powerful than conventional parametric approaches, as are implemented in SPM. Further, the non-parametric approach is always valid, given only minimal assumptions. The SnPM toolbox provides an alternative to the Statistics section of SPM.

Proper citation: Statistical non-Parametric Mapping (RRID:SCR_002092) Copy   

•   Source: SciCrunch Registry

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

Matlab toolbox that implements the wavelet-based image fusion technique for orthogonal images, introduced in (Aganj et al, MRM 2012).

Proper citation: Wavelet-based Image Fusion (RRID:SCR_002007) Copy   

•   Source: SciCrunch Registry

http://mindboggle.info

Mindboggle (http://mindboggle.info) is open source software for analyzing the shapes of brain structures from human MRI data. The following publication in PLoS Computational Biology documents and evaluates the software: Klein A, Ghosh SS, Bao FS, Giard J, Hame Y, Stavsky E, Lee N, Rossa B, Reuter M, Neto EC, Keshavan A. (2017) Mindboggling morphometry of human brains. PLoS Computational Biology 13(3): e1005350. doi:10.1371/journal.pcbi.1005350

Proper citation: Mindboggle (RRID:SCR_002438) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/iowa3/

Software for real-time parametric statistical analysis of functional MRI (fMRI) data. The system that combines a general architecture for sampling and time-stamping relevant information channels in fMRI (image acquisition, stimulation, subject responses, cardiac and respiratory monitors, etc.) and an efficient approach to manipulating these data, featuring incremental subsecond multiple linear regression. The advantages of the system are the simplification of event timing and efficient and unified data formatting. Substantial parametric analysis can be performed and displayed in real-time. Immediate (replay) and delayed off-line analysis can also be performed with the same interface. The system provides a time-accounting infrastructure that readily supports standard and innovative approaches to fMRI.

Proper citation: I/OWA (RRID:SCR_000858) Copy   

•   Source: SciCrunch Registry

http://www.imagescience.org/meijering/software/neuronj/

NeuronJ is an ImageJ plugin to facilitate the tracing and quantification of elongated structures in two-dimensional (2D) images (8-bit gray-scale and indexed color), in particular neurites in fluorescence microscopy images. Sponsors: The development of NeuronJ started while the primary developer ( Dr. Erik Meijering, PhD) was with the Biomedical Imaging Group (collaborating with people from the Laboratory of Cellular Neurobiology) of the Swiss Federal Institute of Technology in Lausanne (EPFL), Switzerland, and was finished while Dr. Meijering was with the Biomedical Imaging Group Rotterdam in the Netherlands.

Proper citation: NeuronJ: An ImageJ Plugin for Neurite Tracing and Quantification (RRID:SCR_002074) Copy   

•   Source: SciCrunch Registry

https://neuinfo.org/mynif/search.php?list=cover&q=*

Service that partners with the community to expose and simultaneously drill down into individual databases and data sets and return relevant content. This type of content, part of the so called hidden Web, is typically not indexed by existing web search engines. Every record links back to the originating site. In order for NIF to directly query these independently maintained databases and datasets, database providers must register their database or dataset with the NIF Data Federation and specify permissions. Databases are concept mapped for ease of sharing and to allow better understanding of the results. Learn more about registering your resource, http://neuinfo.org/nif_components/disco/interoperation.shtm Search results are displayed under the Data Federation tab and are categorized by data type and nervous system level. In this way, users can easily step through the content of multiple resources, all from the same interface. Each federated resource individually displays their query results with links back to the relevant datasets within the host resource. This allows users to take advantage of additional views on the data and tools that are available through the host database. The NIF site provides tutorials for each resource, indicated by the Professor Icon professor icon showing users how to navigate the results page once directed there through the NIF. Additionally, query results may be exported as an Excel document. Note: NIF is not responsible for the availability or content of these external sites, nor does NIF endorse, warrant or guarantee the products, services or information described or offered at these external sites. Integrated Databases: Theses virtual databases created by NIF and other partners combine related data indexed from multiple databases and combine them into one view for easier browsing. * Integrated Animal View * Integrated Brain Gene Expression View * Integrated Disease View * Integrated Nervous System Connectivity View * Integrated Podcasts View * Integrated Software View * Integrated Video View * Integrated Jobs * Integrated Blogs For a listing of the Federated Databases see, http://neuinfo.org/mynif/databaseList.php or refer to the Resources Listed by NIF Data Federation table below.

Proper citation: NIF Data Federation (RRID:SCR_004834) Copy   

•   Source: SciCrunch Registry

http://brainsia.github.io/BRAINSTools/

Medical image processing software suite for brain analysis.

Proper citation: BRAINSTools (RRID:SCR_006618) Copy   

•   Source: SciCrunch Registry

http://icatb.sourceforge.net/fusion/fusion_startup.php

A MATLAB toolbox which implements the joint Independent Component Analysis (ICA), parallel ICA and CCA with joint ICA methods. It is used to to extract the shared information across modalities like fMRI, EEG, sMRI and SNP data. * Environment: Win32 (MS Windows), Gnome, KDE * Operating System: MacOS, Windows, Linux * Programming Language: MATLAB * Supported Data Format: ANALYZE, NIfTI-1

Proper citation: Fusion ICA Toolbox (RRID:SCR_003494) Copy   

•   Source: SciCrunch Registry