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http://slicer.org/

A free, open source software package for visualization and image analysis including registration, segmentation, and quantification of medical image data. Slicer provides a graphical user interface to a powerful set of tools so they can be used by end-user clinicians and researchers alike. 3D Slicer is natively designed to be available on multiple platforms, including Windows, Linux and Mac Os X. Slicer is based on VTK (http://public.kitware.com/vtk) and has a modular architecture for easy addition of new functionality. It uses an XML-based file format called MRML - Medical Reality Markup Language which can be used as an interchange format among medical imaging applications. Slicer is primarily written in C++ and Tcl.

Proper citation: 3D Slicer (RRID:SCR_005619) Copy   

•   Source: SciCrunch Registry

http://www.slicer.org/slicerWiki/index.php/Slicer3:Module:Rician_Noise_Removal

Two Slicer3 modules removing rician noise in diffusion tensor MRI

Proper citation: Slicer3 Module Rician noise filter (RRID:SCR_009614) Copy   

•   Source: SciCrunch Registry

http://www.slicer.org/slicerWiki/index.php/Slicer3:Module:Level-Set_Segmentation_Framework-Documentation

The modules in the framework support different tasks in the segmentation realization in 3DSlicer. A module called Level-set label map evolver was developed, which takes an initial label image and a feature image as input and performs a Geodesic Active Contours evolution on the label image according to the feature image and to a different terms in the level-set equation. The evolution takes place for a customizable number of iterations. The output is a label image that can be used to produce a model. Other modules were developed to accompany the main module as can be seen in http://www.slicer.org/slicerWiki/index.php/Slicer3:Module:Level-Set_Segmentation_Framework-Documentation

Proper citation: Level-set Segmentation for Slicer3 (RRID:SCR_009558) Copy   

•   Source: SciCrunch Registry

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

This module reduces Rician noise on nhdr/nrrd DWIs. Filters image in mean squared error sense using Rician noise model. All estimations are performed as sample estimates in a "shaped neighborhood" defined by the weights extracted from structural similarity of voxels following same idea as in Non-Local Means filter.

Proper citation: Joint Anisotropic LMMSE Filter for Stationary Rician noise removal in DWI (RRID:SCR_009502) Copy   

•   Source: SciCrunch Registry

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

A Diffusion Tensor fiber tracking software suite that includes streamline tracking tools. The fiber tracking includes a guided tracking tool that integrates apriori information into a streamlines algorithm. This suite of programs is built using the NA-MIC toolkit and uses the Slicer3 execution model framework to define the command line arguments. These tools can be fully integrated with Slicer3 using the module discovery capabilities of Slicer3. NOTE: All new development is being managed in a github repository. Please visit, https://github.com/BRAINSia/BRAINSTools

Proper citation: GTRACT (RRID:SCR_009651) Copy   

•   Source: SciCrunch Registry

http://www.unc.edu/~grwu/Software.html

A software plugin for 3D Slicer that matches morphological signatures of medical images automatically. HAMMER is an acronym for Hierarchical Attribute Matching Mechanism for Elastic Registration (Dinggang Shen, Christos Davatzikos, HAMMER: Hierarchical Attribute Matching Mechanism for Elastic Registration, IEEE Trans. on Medical Imaging, 21(11):1421-1439, Nov 2002) - an elastic registration algorithm for medical images, matching morphological signatures of images in a hierarchical multi-scale regime. White matter lesion (WML) segmentation is a novel multi-spectral WML segmentation protocol via incorporating information from T1-w, T2-w, PD-w and FLAIR MR brain images. (Zhiqiang Lao, Dinggang Shen, Dengfeng Liu, Abbas F Jawad, Elias R Melhem, Lenore J Launer, Nick R Bryan, Christos Davatzikos, Computer-Assisted Segmentation of White Matter Lesions in 3D MR images, Using Pattern Recognition, Academic Radiology, 15(3):300-313, March 2008).

Proper citation: Hammer And WML Modules for 3D Slicer (RRID:SCR_005980) Copy   

•   Source: SciCrunch Registry

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

A comprehensive processing pipeline developed and used at University of North Carolina and University of Utah for brain MRIs. The processing pipeline includes image registration, filtering, segmentation and inhomogeneity correction. The tool is cross-platform and can be run within 3D Slicer or as a stand-alone program. The image segmentation algorithm is based on the EMS software developed by Koen van Leemput.

Proper citation: ABC (Atlas Based Classification) (RRID:SCR_005981) Copy   

•   Source: SciCrunch Registry

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

Software that allows users to dynamically interact with multiple surfaces simultaneously. It is very useful for visualisation and comparison of 3D surfaces by also displaying their scalars or vectors attributes stored in the points, and allowing the user to simply modify the colormap. ShapePopulationViewer is available as an extension of 3D Slicer.

Proper citation: ShapePopulationViewer (RRID:SCR_014167) Copy   

•   Source: SciCrunch Registry

http://www.ncbcs.org/biositemaps/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on April 27,2023. Biositemaps represent a mechanism for computational biologists and bio-informaticians to openly broadcast and retrieve meta-data about biomedical data, tools and services (i.e., biomedical resources) over the Internet. All Institutions with an interest in biomedical research can publish a biositemap.rdf file on their Internet site. The technology, developed by the Biositemaps Working Group of the NIH Roadmap National Centers of Biomedical Computing (NCBC), addresses (i) locating, (ii) querying, (iii) composing or combining, and (iv) mining biomedical resources. Each site which intends to contribute to the inventory instantiates a file on its Internet site biositemap.rdf which conforms to a defined RDF schema and uses concepts from the Biomedical Resource Ontology to describe the resources. Each biositemap.rdf file is simply a list of controlled metadata about resources (software tools, databases, material resources) that your organization uses or believes are important to biomedical research. The key enabling technologies are the Information Model (IM) which is the list of metadata fields about each resource (resource_name, description, contact_person, resource_type,...) and the Biomedical Resource Ontology (BRO) which is a controlled terminology for the resource_typeand which is used to improve the sensitivity and specificity of web searches. Biositemaps blend the features of Sitemaps (enabling efficient web-content exploration) and RSS Feeds (a mechanism for wide and effective news dissemination). As a hybrid between Sitemaps and RSS feeds, the Biositemap infrastructure facilitates a decentralized, portable, extensible and computationally tractable generation and consumption of meta-data about existent, revised and new resources for biomedical computation. Web browsers, crawlers and robots can discover, accumulate, process, integrate and deliver Biositemaps content to (human or machine) users in a variety of graphical, tabular, computational formats. Biositemaps content allows such web browsers to pool resource-associated metadata from disparate and diverse sites and present it to the user in an integrated fashion. The Biositemaps protocol provides clues, information and directives for all Biositemap web harvesters that point to the existence and content of such biomedical resources at different sites.

Proper citation: Biositemaps (RRID:SCR_001976) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/slicer3examples/

Example Slicer3 plugins that can be built against a Slicer3 build or a Slicer3 installation. Note: these are for 3D Slicer version 3. There is now a version 4 of 3D Slicer available. Information about extensions for version 4 can be found at the following links: http://www.slicer.org/slicerWiki/index.php/Documentation/Nightly/SlicerApplication/ExtensionsManager http://www.slicer.org/slicerWiki/index.php/Documentation/Nightly/Developers/Tutorials/BuildTestPackageDistributeExtensions

Proper citation: Slicer3 Example Modules (RRID:SCR_002559) Copy   

•   Source: SciCrunch Registry

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

Software framework which uses an unscented Kalman filter for performing tractography. At each point on the fiber the most consistent direction is found as a mixture of previous estimates and of the local model. It is very easy to expand the framework and to implement new fiber representations for it. Currently it is possible to tract fibers using two different 1-, 2-, or 3-tensor methods. Both methods use a mixture of Gaussian tensors. One limits the diffusion ellipsoids to a cylindrical shape (the second and third eigenvalue are assumed to be identical) and the other one uses a full tensor representation. The project is written in C++. It could be used both as a Slicer3 module and as a standalone commandline application.

Proper citation: Diffusion Tractography with Kalman Filter (RRID:SCR_002585) Copy   

•   Source: SciCrunch Registry

http://www.lead-dbs.org/

MATLAB toolbox for deep-brain-stimulation (DBS) electrode reconstructions and visualizations based on postoperative MRI and computed tomography (CT) imaging. The toolbox also facilitates visualization of localization results in 2D/3D, analysis of DBS-electrode placement's effects on clinical results, simulation of DBS stimulations, diffusion tensor imaging (DTI) based connectivity estimates, and fiber-tracking from the VAT to other brain regions (connectomic surgery).

Proper citation: LEAD-DBS (RRID:SCR_002915) Copy   

•   Source: SciCrunch Registry

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

Probabilistic atlas of human white matter tracts/regions underlying several well-known resting state brain networks. The atlas includes group probability maps for each network, as well as each individual tract that are aligned to both the SPM and MRIStudio ICBM templates.

Proper citation: UManitoba - JHU Functionally Defined Human White Matter Atlas (RRID:SCR_015525) Copy   

•   Source: SciCrunch Registry

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

A 3D stereoscopic (anaglyph method) full brain functional connectivity atlas created using a parcellation atlas published by Craddock et al. (2012). Using 3D Slicer 3.6.3 and the two hundred Region of Interest (ROI) version of the Craddock atlas, 200 grayscale surface models were created using a z-stat threshold > 2.3, and each surface model was processed with a surface decimation algorithm, smoothed with the Taubin algorithm and without surface normals. For improved visualization of the functional connectivity networks and their relative anatomical position, the surface model of five subcortical anatomical structures (corpus callosum, bilateral caudate, pallidum, putamen, thalamus, amygdala and hippocampus) were included in SAIBN. These surfaces were created with 3D Slicer using the segmentation computed with Freesurfer v. 5.1. The viewer should use red-cyan glasses to see the 3D stereoscopic effect using 3D Slicer (version 3.6.3, http://www.slicer.org/pages/Special:SlicerDownloads).

Proper citation: Stereoscopic Atlas of Intrinsic Brain Networks (RRID:SCR_002568) Copy   

•   Source: SciCrunch Registry

https://github.com/SlicerMorph/SlicerMorph

Open and extensible platform to retrieve, visualize and analyse 3D morphology.Extension to import microCT data and conduct 3D morphometrics in Slicer. Used for data import, visualization, measurement, annotation, and geometric morphometric analysis on 3D data, including volumetric scans (CTs and MRs) and 3D surface scans, all within the 3D Slicer application.

Proper citation: SlicerMorph (RRID:SCR_024674) Copy   

•   Source: SciCrunch Registry

http://wiki.na-mic.org/Wiki/index.php/2010_Winter_Project_Week_Spine_Segmentation_Module_in_Slicer3

3D Slicer module for automated segmentation of the spine. This is an implementation of a novel model-based segmentation algorithm. This work was presented at the NA-MIC Week in Salt Lake City, Jan 2010.

Proper citation: SpineSegmentation module for 3DSlicer (RRID:SCR_002593) Copy   

•   Source: SciCrunch Registry

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

An end-to-end application allowing individual regional analysis of cortical thickness. This cross-platform tool can be run within Slicer3 as an external module, or directly as a command line. * Operating System: MacOS, Linux * Programming Language: C++ * Supported Data Format: ANALYZE, Nrrd, Other Format * build requires: Insight Toolkit

Proper citation: ARCTIC (RRID:SCR_005989) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/

Software repository for comparing structural (MRI) and functional neuroimaging (fMRI, PET, EEG, MEG) software tools and resources. NITRC collects and points to standardized information about structural or functional neuroimaging tool or resource.

Proper citation: NeuroImaging Tools and Resources Collaboratory (NITRC) (RRID:SCR_003430) Copy   

•   Source: SciCrunch Registry

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

A fast and robust software implementation of the popular Nonlocal Means for MRI-Rician denoising. It works by computing the non-local weights based on distances in a features space comprising the local mean value and gradients of the image. It can reach an acceleration factor of 20x over the original implementation, with an improved performance for medium-low SNR images. They use a bias correction step for Rician noise based on the well-known Conventional Approach. This software can be compiled either as a Slicer module or a stand-alone: http://www.nitrc.org/snapshots.php?group_id=518

Proper citation: Fast Nonlocal Means for MRI denoising (RRID:SCR_002586) Copy   

•   Source: SciCrunch Registry

https://bioimagesuiteweb.github.io/webapp/index.html

Web applications for analysis of multimodal/multispecies neuroimaging data. Image analysis software package. Has facilities for DTI and fMRI processing. Capabilities for both neuro/cardiac and abdominal image analysis and visualization. Many packages are extensible, and provide functionality for image visualization and registration, surface editing, cardiac 4D multi-slice editing, diffusion tensor image processing, mouse segmentation and registration, and much more. Can be intergrated with other biomedical image processing software, such as FSL, AFNI, and SPM.

Proper citation: BioImage Suite (RRID:SCR_002986) Copy   

•   Source: SciCrunch Registry