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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
http://www.nitrc.org/projects/fsl_extensions/
A reference for modifications, extensions, and utilities for the FMRIB Software Library (FSL).
Proper citation: FSL extensions (RRID:SCR_009472) Copy
http://www.loni.usc.edu/Software/DiD
Software application for removing patient-identifying information from medical image files. Removing this information is often necessary for enabling investigators to share image files in a HIPAA compliant manner.
Proper citation: LONI De-identification Debablet (RRID:SCR_009593) Copy
http://www.montefiore.ulg.ac.be/~phillips/FASST.html
An EEG toolbox developed to help users with 3 specific types of data and problems: simulatenous EEG-fMRI recording, continuous EEG scoring (e.g. sleep) and handling (visualisation, cutting, power spectrum, etc.) multi-channel recording of spontaneous EEG. The toolbox is written in Matlab and is specifically compatible with the BrainAmp family of EEG recorders (from BrainProducts GmbH) Three other data formats are now also supported: the edf "European Data Format", exported raw-EGI data (from Electrical Geodesics, Inc.) and the BCI2000 format.The results are directly compatible with SPM8 and are saved with SPM8 EEG data format.
Proper citation: fMRI Artefact rejection and Sleep Scoring Toolbox (RRID:SCR_009620) Copy
http://www.sci.utah.edu/cibc/software/231-biomesh3d.html
A free, easy to use program for generating quality meshes for use in biological simulations. It is currently integrated with SCIRun and uses the SCIRun system to visualize the intermediate results. The BioMesh3D program uses a particle system to distribute nodes on the separating surfaces that separate the different materials and then uses the TetGen software package to generate a full tetrahedral mesh.
Proper citation: BioMesh3D (RRID:SCR_009534) Copy
Software for source analysis and dipole localization in EEG and MEG research. BESA Research has been developed on the basis of 20 years experience in human brain research by Michael Scherg, University of Heidelberg, and Patrick Berg, University of Konstanz. BESA Research is a highly versatile and user-friendly Windows program with optimized tools and scripts to preprocess raw or averaged data for source analysis. All important aspects of source analysis are displayed in one window for immediate selection of a wide range of tools. BESA Research provides a variety of source analysis algorithms, a standardized realistic head model (FEM), and allows for fast and easy hypothesis testing and integration with MRI and fMRI.
Proper citation: BESA (RRID:SCR_009530) Copy
http://www.nitrc.org/projects/hitachi2nirs/
A Matlab script to convert the raw .csv Hitachi ETG4000 output file into a .nirs file for use with Homer2. The script also requires a .pos file. This is the output of the polhemus 3D digitiser that they use to record where the optodes are located spatially. I realize that not everyone uses a 3D digitiser so I have included three example .pos files - one for each of the possible optode arrangements of the Hitachi system (either two 3x3 arrays, one 3x5 array or one 4x4 array). If you use a different arrangement or have more probes than them, feel free to get in touch and they may be able to advise on how to create a model .pos file. There are two versions of the conversion script: 1. single - this will read in ONE .csv file and ONE .pos file and create ONE .nirs file 2. multi - this will read in a user-specified number of .csv files and ONE .pos file. It will then create one .nirs file for each .csv file that was read in and deposit it in the same directory as that .csv file.
Proper citation: Hitachi2nirs (RRID:SCR_009494) Copy
http://www.nitrc.org/projects/gig-ica/
Software toolbox for group-information guided Independent Component Analysis (ICA). In GIG-ICA, group information captured by standard Independent Component Analysis (ICA) on the group level is used as guidance to compute individual subject specific Independent Components (ICs) using a multi-objective optimization strategy. For computing subject specific ICs, GIG-ICA is applicable to subjects that are involved or not involved in the computation of the group information. Besides the group ICs, group information captured from other imaging modalities and meta analysis could be used as the guidance in GIG-ICA too.
Proper citation: Group Information Guided ICA (RRID:SCR_009491) Copy
http://sites.google.com/site/mrilateralventricle/
A fully automated algorithm which works within SPM8 to segment the lateral ventricles from structural MRI images. The algorithm has been validated in infants, adults and patients with Alzheimer's disease (ICC>0.95). ALVIN is insensitive to different scanner sequences (ICC>0.99, 8 different sequences 1.5T and 3T) and sensitive to changes in ventricular volume. Processing time is approx 10mins per subject.
Proper citation: ALVIN (RRID:SCR_009527) Copy
http://www.nitrc.org/projects/fmricpca/
Constrained Principal Component Analysis (CPCA) combines regression analysis and principal component analysis into a unified framework. This method derives images of functional neural networks from singular-value decomposition of BOLD signal time series, and allows derivation of images when the analyzed BOLD signal is constrained to the scans occurring in peristimulus time, using all other scans as baseline. CPCA provides allows (1) determination of multiple functional networks involved in a task, (2) estimation of the pattern of BOLD changes associated with each functional network over peristimulus time points, (3) quantification of the degree of interaction between these multiple functional networks, and (4) a statistical test of the degree to which experimental manipulations affect each functional network. fMRI CPCA provides all results in matlab.mat file format, as well as writing images in analyze format for all components, rotated and unrotated.
Proper citation: fMRI-CPCA (RRID:SCR_009520) Copy
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
http://caid.cs.uga.edu/?name=software
A software toolbox to predict 358 DICCCOL landmarks (Dense Individualized and Common Connectivity-based Cortical landmarks (http://dicccol.cs.uga.edu) ) on a new brain given b0, brain surface data and DTI derived fiber data (vtk format). Each DICCCOL landmark is defined by group-wise consistent white-matter fiber connection patterns derived from diffusion tensor imaging (DTI) data. DICCCOL aims to provide large-scale cortical landmarks with finer granularity, better functional homogeneity, more accurate functional localization, and automatically-established cross-subjects correspondence.
Proper citation: DICCCOL predictor (RRID:SCR_009554) Copy
An open-source toolkit for cross-sectional and longitudinal atlas building. The CalaTK project develops innovative methods and tools for longitudinal atlases with a focus on neurodevelopment. The computational toolbox is developed with the objective to analyze the neural developmental patterns observed in human and non-human primate structural and diffusion tensor magnetic resonance (MR) images.
Proper citation: CalaTK (RRID:SCR_009547) Copy
A workflow-oriented environment focused on biomedical image computing and simulation. The open source framework is extensible through plug-ins and is focused on building research and clinical software prototypes. Gimias has been used to develop clinical prototypes in the fields of cardiac imaging and simulation, angiography imaging and simulation, and neurology.
Proper citation: GIMIAS (RRID:SCR_009545) Copy
http://www.nitrc.org/projects/brat/
An fMRI toolkit which contains a large selection of complex network measures in Matlab GUI. These measures are increasingly used to characterize structural and functional brain connectivity datasets.
Proper citation: Brainnetome fMRI toolkit (RRID:SCR_014092) Copy
http://www.nitrc.org/projects/glmdenoise
A MATLAB toolbox for denoising task-based fMRI data. It derives noise regressors from voxels unrelated to the experimental paradigm and uses these regressors in a general linear model (GLM) analysis of the data. The technique only requires a design matrix indicating the experimental design and an fMRI dataset.
Proper citation: GLMdenoise: a fast, automated technique for denoising task-based fMRI data (RRID:SCR_014116) Copy
http://www.nitrc.org/projects/basco/
A software tool (with GUI) for investigating inter-regional functional connectivity in event-related fMRI data and allows the user to assess the modulation of functional connectivity by an experimental condition.
Proper citation: BetA-Series COrrelation (RRID:SCR_014086) Copy
http://www.nitrc.org/projects/dicomconvert/
A DICOM image converter based on the ITK IO mechanism for reading and writing images. The formats currently supported by the converter are DICOM to: Analyze (*.hdr); MetaImage (*.mhd); Nrrd (*.nhdr, *.nrrd).
Proper citation: DICOMConvert (RRID:SCR_014100) Copy
http://www.nitrc.org/projects/notion/
Standalone software designed to be used by radiology researchers for storage and anonymization of research images.
Proper citation: Notion ResearchPACS (RRID:SCR_014154) Copy
http://sourceforge.net/projects/cudasphere/
A CUDA C based toolkit which provides a GPU based implementation of the spherical model forward solution for the 306 channel Elekta Neuromag MEG system and the EEG. The 1-Sphere forward solution for the MEG and the 4-Sphere forward solution for the EEG is implemented in CUDA C and an accelerated solution is obtained using the NVIDIA GPU when the solution is calculated for a large number of dipoles (on the order of 15000 and above) and sensor location. Speedup by a factor of 22 and 32 is obtained for the EEG and MEG solution respectively when compared to the fastest CPU implementation available in the public domain. The complete source code and pre-compiled binaries are also made available via an open source license (GPL Version 3). A CUDA enabled NVIDIA graphics card is required to use the software.
Proper citation: CUDA-SPHERE-FWD-MEEG (RRID:SCR_013225) Copy
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