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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/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/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

http://www.nitrc.org/projects/gpu-areg/

This tool can be used as a command line module with 3D Slicer (version 3 and above) for the affine registration of image volumes. The registration toolbox has 2 options: 1) a Mutual Information based registration, 2) a Sum-of-Square differences registration method. The final output is in the same space as the fixed image. You do require to have CUDA v2.2 or greater installed on your system with atleast 256MB Nvidia GPU memmory card. All operating systems are supported, but take a look at the CMakeLists.txt file for how to compile for you system.

Proper citation: GPU based affine registration (RRID:SCR_009486) Copy   

•   Source: SciCrunch Registry

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

This module implements the Finsler tractography method with HARDI data described by J. Melonakos et al. From a set of seeding and target points, the paths are estimated as the shortest path taking into account a local, directional dependent cost. The output provided is the connectivity map from each voxel in the volume to the seeding points, plus a vector volume with the directions tangent to the fiber bundles at each point. If the Backtracing module within is built, these directions can be traced back to actually compute the fiber bundles (VTK required). The software can be built as either a stand-alone or a CLI plugin for 3D Slicer.

Proper citation: Finsler tractography module for Slicer (RRID:SCR_009477) Copy   

•   Source: SciCrunch Registry

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

An end-to-end application allowing Group-wise Automatic Mesh-Based analysis of cortIcal Thickness as well as other surface area measurements. This cross-platform tool can be run within 3D Slicer as an external module, or directly as a command line.

Proper citation: GAMBIT (RRID:SCR_009483) Copy   

•   Source: SciCrunch Registry

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

Slicer3 module to provide a capability for performing white matter lesion classification and summary.

Proper citation: 3DSlicerLupusLesionModule (RRID:SCR_000853) 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://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/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

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