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SciCrunch Registry is a curated repository of scientific resources, with a focus on biomedical resources, including tools, databases, and core facilities - visit SciCrunch to register your resource.
http://www.nitrc.org/projects/nihlungseg/
A segmentation tool for the segmentation of a lung from CT images. The sofware can be run in two modes: fully automatic and semi-automatic with manual seeding by the user. The software also allows the user to perform basic filtering operations and manual correction to the segmentation. The VTK-based rendering implementation, along with option to view in axial, coronal, and sagittal, provides the user with better visualization of the segmented lung.
Proper citation: NIH-CIDI Lung Segmentation Tool (RRID:SCR_014150) Copy
http://www.nitrc.org/projects/nutil/
Software toolbox to simplify and streamline mechanism of pre and post processing 2D brain image data. Neuroscience image processing and analysis utilities. Stand alone application that runs on all operating systems.
Proper citation: Nutil - Neuroimaging utilities (RRID:SCR_017183) Copy
Software tool as a cross-platform NIfTI format image viewer. Used for viewing and exporting of brain images. MRIcroGL is a variant of MRIcron.
Proper citation: MRIcron (RRID:SCR_002403) Copy
http://www.dian-info.org/default.htm
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 23,2022. An international research partnership of leading scientists determined to understand a rare form of Alzheimers disease that is caused by a gene mutation and to establish a research database and tissue repository to support research on Alzheimers disease by other investigators around the world. One goal of DIAN is to study possible brain changes that occur before Alzheimers disease is expressed in people who carry an Alzheimers disease mutation. Other family members without a mutation will serve as a comparison group. People in families in which a mutation has been identified will be tracked in order to detect physical or mental changes that might distinguish people who inherited the mutation from those who did not. DIAN currently involves eleven outstanding research institutions in the United States, United Kingdom, and Australia. John C. Morris, M.D., Friedman Distinguished Professor of Neurology at Washington University School of Medicine in St. Louis, is the principal investigator of the project., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.
Proper citation: DIAN - Dominantly Inherited Alzheimer Network (RRID:SCR_000812) Copy
http://www.nitrc.org/projects/cluster_roi/
A set of tools for deriving region of interest (ROI) atlases by whole brain clustering of task or resting state data. This resource also contains several atlases derived by parcellating publicly available resting state fMRI datasets. The initial release will include python scripts and ROI atlases developed to perform the analyses described in Craddock et. al., A whole brain fMRI atlas generated via spatially constrained spectral clustering, which is currently in revision in Human Brain Mapping. The scripts provide all of the tools necessary to derive an ROI atlases using spatially constrained Ncut spectral clustering. The scripts require python, numpy and scipy to run. Source code and parcellations now available! Go to http://ccraddock.github.io/cluster_roi/ for more information.
Proper citation: Spatially Constrained Parcellation (RRID:SCR_002198) Copy
http://www.nitrc.org/projects/mica/
Software toolbox based on FSL command line tools that performs masked independent component analysis and related analyses in an integrated way within a spatially restricted subregion of the brain. Used for investigating functional connectivity in functional magnetic resonance imaging data in the field of neuroimaging.
Proper citation: masked ICA (mICA) Toolbox (RRID:SCR_016349) Copy
http://www.nitrc.org/projects/uf2c/
Software tool to standardize and facilitate connectivity studies through a graphical user interface and validated preset parameters.
Proper citation: User Friendly Functional Connectivity - UF²C (RRID:SCR_016550) Copy
http://www.nitrc.org/projects/vmas_2020/
Software tool to generate whole connected 3D brain ventricular shape model and encode ventricular surface deformation information that is inaccessible by ventricle volume measure. Contains automated segmentation approach and surface based multivariate morphometry statistics.
Proper citation: Ventricular Morphometry Analysis System (RRID:SCR_019007) Copy
http://www.nitrc.org/projects/abcdrepronim/
Course provides training for reproducible analyses of Adolescent Brain Cognitive Development Study data. Designed to provide comprehensive background to ABCD study while delivering hands on instruction on reproducible ReproNim workflows and outcomes.
Proper citation: ABCD-ReproNim Course (RRID:SCR_018911) Copy
https://github.com/cwatson/braingraph/
Software R package for performing graph theory analyses of brain MRI data.
Proper citation: brainGraph (RRID:SCR_017260) Copy
http://www.nitrc.org/projects/reprocontainers/
Software containerized environments for reproducible neuroimaging. Part of ReproNim - Center for Reproducible Neuroimaging Computation. DataLad dataset with collection of popular computational tools provided within ready to use containerized environments.
Proper citation: ReproNim/containers (RRID:SCR_018467) Copy
An information extracting and processing package for biological literature that can be used online or installed locally via a downloadable software package, http://www.textpresso.org/downloads.html Textpresso's two major elements are (1) access to full text, so that entire articles can be searched, and (2) introduction of categories of biological concepts and classes that relate two objects (e.g., association, regulation, etc.) or describe one (e.g., methods, etc). A search engine enables the user to search for one or a combination of these categories and/or keywords within an entire literature. The Textpresso project serves the biological and biomedical research community by providing: * Full text literature searches of model organism research and subject-specific articles at individual sites. Major elements of these search engines are (1) access to full text, so that the entire content of articles can be searched, and (2) search capabilities using categories of biological concepts and classes that relate two objects (e.g., association, regulation, etc.) or identify one (e.g., cell, gene, allele, etc). The search engines are flexible, enabling users to query the entire literature using keywords, one or more categories or a combination of keywords and categories. * Text classification and mining of biomedical literature for database curation. They help database curators to identify and extract biological entities and facts from the full text of research articles. Examples of entity identification and extraction include new allele and gene names and human disease gene orthologs; examples of fact identification and extraction include sentence retrieval for curating gene-gene regulation, Gene Ontology (GO) cellular components and GO molecular function annotations. In addition they classify papers according to curation needs. They employ a variety of methods such as hidden Markov models, support vector machines, conditional random fields and pattern matches. Our collaborators include WormBase, FlyBase, SGD, TAIR, dictyBase and the Neuroscience Information Framework. They are looking forward to collaborating with more model organism databases and projects. * Linking biological entities in PDF and online journal articles to online databases. They have established a journal article mark-up pipeline that links select content of Genetics journal articles to model organism databases such as WormBase and SGD. The entity markup pipeline links over nine classes of objects including genes, proteins, alleles, phenotypes, and anatomical terms to the appropriate page at each database. The first article published with online and PDF-embedded hyperlinks to WormBase appeared in the September 2009 issue of Genetics. As of January 2011, we have processed around 70 articles, to be continued indefinitely. Extension of this pipeline to other journals and model organism databases is planned. Textpresso is useful as a search engine for researchers as well as a curation tool. It was developed as a part of WormBase and is used extensively by C. elegans curators. Textpresso has currently been implemented for 24 different literatures, among them Neuroscience, and can readily be extended to other corpora of text.
Proper citation: Textpresso (RRID:SCR_008737) Copy
http://www.nitrc.org/projects/brainsolution/
A collection of tools for MRI T1 brain image segmentation in the Windows environment. It helps construct a complete pipeline with necessary preprocessing and postprocessing procedures besides brainparser, the core program of our fast brain segmentation. The execution of the whole pipeline can be completed in 2 hours with good segmentation results. Execution requires: FSL
Proper citation: BrainSolution (RRID:SCR_009447) Copy
http://www.nitrc.org/projects/dfbidb/
A suite of tools for efficient management of neuroimaging project data. Specifically, DFBIdb was designed to allow users to quickly perform routine management tasks of sorting, archiving, exploring, exporting and organising raw data. DFBIdb was implemented as a collection of Python scripts that maintain a project-based, centralised database that is based on the XCEDE 2 data model. Project data is imported from a filesystem hierarchy of raw files, which is an often-used convention of imaging devices, using a single script that catalogues meta-data into a modified XCEDE 2 data model. During the import process data are reversibly anonymised, archived and compressed. The import script was designed to support multiple file formats and features an extensible framework that can be adapted to novel file formats. Graphical user interfaces are provided for data exploration. DFBIdb includes facilities to export, convert and organise customisable subsets of project data according to user-specified criteria.
Proper citation: DFBIdb (RRID:SCR_009456) Copy
http://nrg.wustl.edu/projects/fiv
A tool for visualizing functional and anatomic MRI data.
Proper citation: FIV (RRID:SCR_009575) Copy
http://www.nitrc.org/projects/ccseg/
An open-source C++-based application that allows automatic as well as user-interactive segmentation of the Corpus Callosum. Via a Qt-based graphical user interface, CCSeg also performs semi-automatic segmentation.
Proper citation: CCSeg - Corpus Callosum Segmentation (RRID:SCR_009453) Copy
http://www.ncigt.org/pages/Research_Projects/ImagingCoreToolbox/Imaging_Toolkit
This software provides algorithms for the reconstruction of raw MR data. In particular, it supports the reconstruction of accelerated data acquisitions where k-space is subsampled and the Fourier domain encoding is complemented by temporal encoding, spatial encoding, or and/or a constrained reconstruction. This library of functions provides a number of reconstruction algorithms that accurately employ advanced MR imaging methods including: UNFOLD; parallel imaging methods such as SENSE and GRAPPA; Homodyne processing of partial-Fourier data, and gradient field inhomogeneity correction (gradwarp); EPI Nyquist Ghost correction and ramp-sampling gridding. The target audience is research groups who may be interested in exploring or employing advanced MR reconstruction techniques, but don't have the necessary expertise in-house. Inquires may be directed to: ncigt-imaging-toolkit -at- bwh.harvard.edu
Proper citation: NCIGT Fast Imaging Library (RRID:SCR_009609) Copy
A complete set of tools that enables researchers to perform spatial and navigational behavior experiments within interactive, easy to create, and extendable (e.g., multiple rooms) 3D virtual environments. MazeSuite can be used to design/edit adapted 3D environments where subjects? behavioral performance can be tracked. Maze Suite consists of three main applications; an editing program to create and alter maps (MazeMaker), a visualization/rendering module (MazeWalker), and finally an analysis/mapping tool (MazeAnalyzer). Additionally, MazeSuite has the capabilities of sending signal pulses to physiological recording devices using standard computer ports. MazeSuite, with all 3 applications, is a unique and complete toolset for researchers who want to easily and rapidly deploy interactive 3D environments. Requirements Maze Suite is designed for Windows 7, Windows Vista and Windows XP. 3D rendering quality depends on available graphics card hardware; OpenGL 2.1 or above compliant is recommended. For Windows XP systems, .NET Framework Version 2.0 or above is required and can be downloaded from Microsoft's website.
Proper citation: MazeSuite (RRID:SCR_009606) Copy
A viewer for medical research images that provides analysis tools and a user interface to navigate image volumes. There are three versions of Mango, each geared for a different platform: * Mango ? Desktop ? Mac OS X, Windows, and Linux * webMango ? Browser ? Safari, Firefox, Chrome, and Internet Explorer * iMango ? Mobile ? Apple iPad Key Features: * Built-in support for DICOM, NIFTI, Analyze, and NEMA-DES formats * Customizable: Create plugins, custom filters, color tables, file formats, and atlases * ROI Editing: Threshold and component-based tools for painting and tracing ROIs * Surface Rendering: Interactive surface models supporting cut planes and overlays * Image Registration: Semi-automatic image coregistration and manual transform editing * Image Stacking: Threshold and transparency-based image overlay stacking * Analysis: Histogram, cross-section, time-series analysis, image and ROI statistics * Processing: Kernel and rank filtering, arithmetic/logic image and ROI calculators
Proper citation: Mango (RRID:SCR_009603) Copy
http://visual.cs.utsa.edu/eegvis
A MATLAB toolbox for exploration of multi-channel EEG and other large array-based data sets using multi-scale drill-down techniques. The toolbox can be used directly in MATLAB at any stage in a user's processing pipeline, as a plug in for EEGLAB, or as a standalone precompiled application without MATLAB running. EEGVIS and its supporting packages are freely available under the GNU general public license. The toolbox also supplies a number of extensible base classes for users who wish to develop their own visualizations.
Proper citation: EEGVIS (RRID:SCR_009569) Copy
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