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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.
From state of the art post-processing and visualization software for BOLD, Diffusion / DTI, and Perfusion / DCE imaging to fMRI hardware for audio and visual stimulation, eye tracking, and patient response collection, they provide products and solutions that define the field of functional MR imaging. They are dedicated to bringing the most advanced neuro-imaging tools to market while making functional MRI programs easy to implement. Through collaboration with research and clinical teams from both academic and medical centers, MR system manufacturers, and third party vendors they develop and manufacture hardware and software solutions that meet the needs of very experienced centers while developing training programs to make fMRI easy to adopt for more novice users. Their products are used around the world by researchers and clinicians alike.
Proper citation: NordicNeuroLab (RRID:SCR_009632) Copy
https://www.nitrc.org/projects/lumina/
A reliable patient response system designed specifically for use in an fMRI. Lumina was developed to satisfy the requirements of both the clinical and research fields.
Proper citation: Lumina LP- 400 Response System (RRID:SCR_009596) Copy
http://www.nitrc.org/projects/diffusion-mri/
This program contains Python modules for modeling and reconstruction of diffusion weighted MRI data. It is a subset of the code internally used in the CVGMI lab at the University of Florida. Three different reconstruction methods are currently included in this program, namely, Mixture of Wisharts (MOW), Diffusion Orientation Transform (DOT) and Q-ball Imaging (QBI). This program is mainly developed and maintained by Bing Jian, as part of his Ph.D. research, supervised by Prof. Baba Vemuri. Please note that the source code of this program is hosted at Google Code, see the Source Code link on the left.
Proper citation: Multi-fiber Reconstruction from DW-MRI (RRID:SCR_009509) Copy
http://www.nitrc.org/projects/masimatlab/
This repository stores and provides opportunities for collaboration through Matlab code, libraries, and configuration information for projects in early stage development. The MASI research laboratory concentrates on analyzing large-scale cross-sectional and longitudinal neuroimaging data. Specifically, they are interested in population characterization with magnetic resonance imaging (MRI), multi-parametric studies (DTI, sMRI, qMRI), and shape modeling.
Proper citation: MASIMatlab (RRID:SCR_009506) Copy
http://www.smivision.com/en/gaze-and-eye-tracking-systems/products/iview-x-mri-meg.html
A non-invasive, long-range eye tracking system for use in the fMRI environment. Some features of the system include: * Elaborate faraday shielding and fiber optics to avoid noise in high-field magnets. * Includes stimulus presentation software ?Experiment Center? and is compatible with 3rd party products such as ?Presentation? by NeuroBS. * Utilizes mirror box customized for large field of view. * Includes powerful analysis software ?BeGaze2? for graphical and statistical analysis of eye movements. * Includes fixation, saccade and blink detection, and area-of-interest based statistics * Real-time data available via digital or analog output
Proper citation: iView X MRI-LR - Eye Tracking for fMRI (RRID:SCR_009627) Copy
http://www.nitrc.org/projects/masi-fusion/
Tool that provides a unified framework for testing and applying statistical and voting label fusion techniques. The project will include implementations of several different voting techniques including majority vote, weighted voting, and regionally weighted voting. Additionally, multiple statistical fusion methods will be included, notably, STAPLE, Spatial STAPLE, STAPLER and COLLATE. In addition to the fusion algorithms, code for running specialized simulations and various tools and utilities to test the efficacy of the algorithms will be provided.
Proper citation: MASI Label Fusion (RRID:SCR_009505) Copy
https://github.com/BRAINSia/BRAINSTools/tree/master/BRAINSROIAuto
Automatically creates a mask based on the "foreground" of an anatomical scan volume.
Proper citation: BRAINSROIAuto (RRID:SCR_009501) Copy
http://www.nitrc.org/projects/iaclmedic/
This project is used for students enrolled in courses using the JIST framework. Content in this CVS is freely available, but it is not intended for any specific purpose.
Proper citation: JHU Proj. in Applied Medical Imaging (RRID:SCR_009499) Copy
http://www.vpixx.com/products/visual-stimulators/datapixx.html
Supplies a complete multi-function data and video processing USB peripheral for vision research. In addition to a dual-display video processor, the DATAPixx includes an array of peripherals which often need to be synchronized to video during an experiment, including a stereo audio stimulator, a button box port for precise reaction-time measurement, triggers for electrophysiology equipment, and even a complete analog I/O subsystem. Because we implemented the video controller and peripheral control on the same circuit board, you can now successfully synchronize all of your subject I/O to video refresh with microsecond precision.
Proper citation: DATAPixx (RRID:SCR_009648) Copy
http://www.nitrc.org/projects/rbpm/
To enable widespread application of the Biological parametric mapping (BPM) approach, they introduce robust regression and non-parametric regression in the neuroimaging context of application of the general linear model. Biological parametric mapping (BPM) has extended the widely popular statistical parametric approach to enable application of the general linear model to multiple image modalities (both for regressors and regressands) along with scalar valued observations. This approach offers great promise for direct, voxelwise assessment of structural and functional relationships with multiple imaging modalities. However, as presented, the biological parametric mapping approach is not robust to outliers and may lead to invalid inferences (e.g., artifactual low p-values) due to slight mis-registration or variation in anatomy between subjects.
Proper citation: Robust Biological Parametric Mapping (RRID:SCR_009642) Copy
http://www.connectomics.org/cfflib/
A container format for multi-modal neuroimaging data. It comprises connectome objects of type: CMetadata, CNetwork, CVolume, CSurface, CTrack, CScript, CData, CTimeseries, CImagestack. The Python library cfflib provides read/write functionality.
Proper citation: Connectome File Format (RRID:SCR_009551) Copy
http://www.cise.ufl.edu/~tichen/cdfHC.zip
A Matlab demo for group wise point set registration using a novel CDF-based Havrda-Charvat Divergence, which is based on the paper: Ting Chen, Baba C. Vemuri, Anand Rangarajan and Stephan J. Eisenschenk, Group-wise Point-set registration using a novel CDF-based Havrda-Charvat Divergence. In IJCV : International Journal of Computer Vision, 86(1):111-124, January, 2010.
Proper citation: CDF-HC PointSetReg (RRID:SCR_009544) Copy
http://www.softpedia.com/get/Science-CAD/BrainVisa-Morphology-extensions.shtml
An extension projects providing computational tools for performing regional morphological measurements to assess groupwise differences and track morphological changes during maturation and aging. The extensions include computation of regional GM thickness, 3D gyrification index, sulcal lenght and depth and sulcal span. These tools are distributed in the form of plugins for a popular analysis package BrainVisa
Proper citation: BrainVisa Morphology extensions (RRID:SCR_013248) Copy
http://enigma.ini.usc.edu/protocols/dti-protocols/
Pipeline which provides tools to extract whole-brain average and regional measurements from DTI images including FA, AD, RD and MD. Protocols for preprocessing, ENIGMA-DTI processing (skeletonization and ROI extraction), and GWAS analysis are available. Software tools used for each process are listed within the protocols.
Proper citation: ENIGMA-DTI Pipeline (RRID:SCR_014649) Copy
http://www.nitrc.org/projects/xnat_extras
User software contributions for XNAT - The Extensible Neuroimaging Archive Toolkit, http://www.xnat.org
Proper citation: XNAT Extras (RRID:SCR_004759) Copy
http://wiki.biac.duke.edu/jvs:cigal
Software program that provides accurate real-time stimulus control, behavioral and physiological recording, and synchronization with external devices. It can also provide continuous real-time feedback of task performance and physiological responses. Task programming typically involves a simple text file specifying basic parameter settings (e.g. screen color) and a list of stimulus events, which can include images, animated movies, sound files, text stimuli, video graphics, or commands that communicate with external hardware devices. Multiple video and auditory stimuli can be presented simultaneously. Multi-channel response recording and real-time feedback features require no user programming. Advanced users can add customized stimulus events using CIGAL's real-time programming capabilities. Output files can be automatically created in a variety of output formats (e.g. FSL 3-column files, XML Events files, CSV trial tables).
Proper citation: CIGAL (RRID:SCR_002232) Copy
https://www.nitrc.org/projects/uncbcp_4d_atlas/
Software package for constructing longitudinal atlases, which are the necessary steps for many brain-related applications.
Proper citation: 4D Atlases Construction (RRID:SCR_002227) Copy
http://www.nitrc.org/projects/scribe/
Scribe encodes papers to populate the BrainMap Database
Proper citation: Scribe (RRID:SCR_000423) Copy
http://www.nitrc.org/projects/ontologyviz/
Software that allows user to do faceted search on an ontology and enables visualization of the search results on the 3D digital atlas. Currently supports faceted search of functional neuroanatomy.
Proper citation: Faceted Search Based Ontology Visualizer (RRID:SCR_000124) Copy
http://www.nitrc.org/projects/volbrain/
Software tool as MRI brain segmentation system to obtain automatically volumetric brain information from RI data. Works in automatic manner and is able to provide brain structure volumes without any human interaction.
Proper citation: volBrain (RRID:SCR_021020) Copy
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