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

A method for group-wise image registration by pairwisely registering similar images identified using graph theoretic techniques. Particularly, they use sparse coding to estimate image similarity measures among images to be registered, yielding asymmetric, group-wise image similarity measures for each image to others in the group.

Proper citation: Groupwise Image Registration Toolbox (RRID:SCR_009492) Copy   

•   Source: SciCrunch Registry

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

An international effort to establish resources necessary to study the application of neuroimaging measures as (surrogate) biomarkers in Huntington''s Disease (HD). The primary aims are to develop and apply software tools, imaging protocols, quality control procedures, data archiving, data distribution, and participation guidelines that will accelerate existing and prospective imaging studies.

Proper citation: HD Neuro-Informatics (RRID:SCR_009493) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

http://www.restfmri.net

A user-friendly convenient toolkit to calculate Functional Connectivity (FC), Regional Homogeneity (ReHo), Amplitude of Low-Frequency Fluctuation (ALFF), Fractional ALFF (fALFF), Gragner causality and perform statistical analysis. You also can use REST to view your data, perform Monte Carlo simulation similar to AlphaSim in AFNI, calculate your images, regress out covariates, extract Region of Interest (ROI) time courses, reslice images, and sort DICOM files.

Proper citation: REST: a toolkit for resting-state fMRI (RRID:SCR_009641) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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

Quadratically constrained quadratic programing (QCQP) technique in medical image analysis. QCQP based tools are provided for classification, segmentation, and bias field correction.

Proper citation: QCQP (RRID:SCR_009640) Copy   

•   Source: SciCrunch Registry

http://www.columbia.edu/~dx2103/brainimagescope.html

Software package for processing diffusion tensor imaging data. The following functions are included: 1. Converting imaging data in DICOME format to ANALYZE format 2. Extracting binary brain mask for quick scalp-removing 3. Correcting eddy-current induced distortion 4. Optimized tensor estimation based on noisy diffusion-weighted imaging (DWI) data 5. Scalp removal using a brain mask image 6. Corregistering imaging data and generating deformation field for mapping images from individual spaces to a template or target space 7. Spatial Normalization and Warping DTI 8. Fiber tracking 9. Clustering fiber tracts 10. Identifying brain ventricles and generating binary masks for the baseline and DW imaging data 11. Deriving diffusion anisotropy indices (DAIs) and principal directions (PD) and the corresponding color-coded PD-map.

Proper citation: DTI BrainImageScope (RRID:SCR_009559) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

http://cocomac.org/WWW/paxinos3D/index.html

An interactive interface of macaque stereotaxic atlas with a connectivity database, allowing integrated data analysis and mapping between 3D structures with database vocabularies. These Java-based tools are capable of reading stacks of polygons described in svg vector format and arrange them in 3D space so that the corresponding structures can be viewed and manipulated individually. An additional excel (currently v. 1997-2003) file maintains the structure abbreviations and their mapping to the terminology of databases that provide supplementary information. Here in particular we have manually drawn the cortical, striatal, thalamic and amygdaloid structures of the 151 frontal sections from the Rhesus Monkey Brain in Stereotactic Coordinates authored by Paxinos and colleagues in 1999. After loading the excel file and a set of the svg files, the view can be rotated, zoomed and individual brain structures be selected for identification and simple geometric measures. A stereotaxic grid is a display option. The abbreviations of the brain structures are mapped to entities recorded in the CoCoMac database of primate brain connectivity. Thereby one can retrieve mapping and connectivity information for the selected structure as text or connecting arrows.

Proper citation: CoCoMac-Paxinos3D viewer (RRID:SCR_009548) Copy   

•   Source: SciCrunch Registry

http://invizian.loni.usc.edu

A visualization environment that enables you, via your computer, to display and interact with hundreds of neuroimaging data sets at once ?bringing together brain image data from some of the world?s best neuroscience research teams. INVIZIAN empowers both researchers and students of neuroscience to explore and understand the human brain using a simple yet powerful user interface for neuroimaging data exploration and discovery. See a beautiful example of a cloud of individual brains tumbling around in the INVIZIAN interface in Vimeo (http://vimeo.com/67984681). Visit often to see how we are making continuing progress to make Invizian even more amazing.

Proper citation: INVIZIAN (RRID:SCR_009549) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

http://www.ohsu.edu/xd/

As the state''s only health and research university, OHSU brings together patient care, research, education of the next generation of health care providers and scientists and community service to improve the health and well-being of all Oregonians.

Proper citation: Oregon Health and Science University; Oregon; USA (RRID:SCR_009665) Copy   

•   Source: SciCrunch Registry

http://www.commerce.gov/

Executive department of the federal government concerned with promoting economic growth. Among its tasks are gathering economic and demographic data for business and government decision-making, and helping to set industrial standards.

Proper citation: U.S. Department of Commerce (RRID:SCR_009859) Copy   

•   Source: SciCrunch Registry

http://www.usgs.gov/

Scientific agency of the United States government. The scientists of the USGS study the landscape of the United States, its natural resources, and the natural hazards that threaten it. The organization's work spans the disciplines of biology, geography, geology, and hydrology.

Proper citation: U.S. Geological Survey (RRID:SCR_010168) Copy   

•   Source: SciCrunch Registry

http://purl.bioontology.org/ontology/BOF

An ontology of biodiversity of INPA

Proper citation: Biodiversity Ontology (RRID:SCR_010204) Copy   

•   Source: SciCrunch Registry

http://www.allseq.com/default.aspx

Free online tools to find the best Sequencing Service provider for your project.

Proper citation: AllSeq (RRID:SCR_010053) Copy   

•   Source: SciCrunch Registry

http://purl.bioontology.org/ontology/COGAT

Ontology that characterizes the state of current thought in cognitive science. It defines a set of mental concepts along with a set of mental tasks, and the measurement relations between those classes.

Proper citation: Cognitive Atlas Ontology (RRID:SCR_010295) Copy   

•   Source: SciCrunch Registry

http://purl.bioontology.org/ontology/CTCAE

A coding system for reporting adverse events that occur in the course of cancer therapy. It was derived from the Common Toxicity Criteria (CTC) v2.0 and is maintained by the Cancer Therapy Evaluation Program (CTEP) at the National Cancer Institution (NCI).

Proper citation: Common Terminology Criteria for Adverse Events (RRID:SCR_010296) Copy   

•   Source: SciCrunch Registry

http://sourceforge.net/apps/mediawiki/cdao/

A formalization of concepts and relations relevant to evolutionary comparative analysis, such as phylogenetic trees, OTUs (operational taxonomic units) and compared characters (including molecular characters as well as other types). CDAO is being developed by scientists in biology, evolution, and computer science

Proper citation: Comparative Data Analysis Ontology (RRID:SCR_010297) Copy   

•   Source: SciCrunch Registry

http://purl.bioontology.org/ontology/CARELEX

Categories and terms used to classify content (documents, images, etc) in electronic content repositories for life science / BioPharma. Initial version contains content model for use with clinical trial electronic Trial Master Files or eTMF archives. A Content model contains content classification categories (classes) and metadata properties (data properties). Data properties should be assigned to each Content Type. Recent changes include: addition of electronic signature support, medical imaging classifications.

Proper citation: Content Archive Resource Exchange Lexicon (RRID:SCR_010298) Copy   

•   Source: SciCrunch Registry