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on page 1 showing 20 out of 690 results from 1 sources

Cite this (2009 Grantees Meeting, RRID:SCR_014081)

URL: http://www.nitrc.org/projects/nihgrantees

Resource Type: Resource, meeting resource, training resource

This project is meant for planning the NITRC Grantee meetings. The meetings introduce NITRC participants to one another, promote discussion of common interests, and identify opportunities for collaboration and interoperability. The 2009 meeting for NITRC enhancement grant awardees was held on June 18, 2009 (8:00 AM - 5:00 PM) in San Francisco at the San Francisco Marriott.

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Cite this (3DBar, RRID:SCR_008896)

URL: http://www.3dbar.org

Resource Type: Resource, production service resource, analysis service resource, reference atlas, software resource, service resource, atlas, data or information resource

Software package for reconstructing three-dimensional models of brain structures from 2-D delineations using a customizable and reproducible workflow. 3dBAR also works as an on-line service (http://service.3dbar.org) offering a variety of functions for the hosted datasets: * downloading reconstructions of desired brain structures in predefined quality levels in various supported formats as well as created using customizable settings, * previewing models as bitmap thumbnails and (for webGL enabled browsers) interactive manipulation (zooming, rotating, etc.) of the structures, * downloading slides from available datasets as SVG drawings. 3dBAR service can also be used by other websites or applications to enhance their functionality. * Operating System: Linux * Programming Language: Python * Supported Data Format: NIfTI-1, Other Format, VRML

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Cite this (3D DTI Atlas of the Rat Brain In Postnatal Day 5 14 and Adulthood, RRID:SCR_009437)

URL: http://www.nitrc.org/projects/dti_rat_atlas/

Resource Type: Resource, atlas, reference atlas, data or information resource

3D DTI anatomical rat brain atlases have been created by the UNC- Chapel Hill Department of Psychiatry and the CAMID research collaboration. There are three age groups, postnatal day 5, postnatal day 14, and postnatal day 72. The subjects were Sprague-Dawley rats that were controls in a study on cocaine abuse and development. The P5 and P14 templates were made from scans of twenty rats each (ten female, ten male); the P72, from six females. The individual cases have been resampled to isotropic resolution, manually skull-stripped, and deformably registered via an unbiased atlas building method to create a template for each age group. Each template was then manually segmented using itk-SNAP software. Each atlas is made up of 3 files, a template image, a segmentation, and a label file.

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Cite this (3D Interactive Chemical Shift Imaging, RRID:SCR_002581)

URL: https://www.nitrc.org/projects/threedicsi/

Resource Type: Resource, software resource, software application, data processing software

A user-friendly and comprehensive software program for multi-dimensional CSI data visualization, spectral processing, localization, quantification and multi-variate analysis.

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Cite this (3DMeshMetric, RRID:SCR_000043)

URL: http://www.nitrc.org/projects/meshmetric3d/

Resource Type: Resource, data visualization software, software application, data processing software, software resource

A visualization tool based on the VTK library. Its main feature is to measure and display surface-to-surface distance between two triangle meshes using user-specified uniform sampling ( based on the source code of MeshValmet ). 3dMeshMetric also offers all the basic tools to visualize meshes such as color, opacity, smoothing, down sampling or type of representation.

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Cite this (3dsvm, RRID:SCR_014083)

URL: http://www.nitrc.org/projects/afni_3dsvm/

Resource Type: Resource, software resource, image analysis software, data processing software, software application

A command-line program and plugin for AFNI built around SVM-Light. It performs support vector machine (SVM) analysis on fMRI data and runs on Unix+X11+Motif systems, including SGI, Solaris, Linux, and Mac OS X.

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Cite this (4D Atlases Construction, RRID:SCR_002227)

URL: http://www.med.unc.edu/bric/ideagroup/free-softwares/4d-atlases-construction

Resource Type: Resource, software resource

Software package for constructing longitudinal atlases, which are the necessary steps for many brain-related applications.

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Cite this (4D-PARSeR Pathological Anatomy Regression via Segmentation and Registration, RRID:SCR_002480)

URL: http://www.nitrc.org/projects/parser_4d/

Resource Type: Resource, segmentation software, image analysis software, data processing software, software application, software resource, registration software

A tool for analyzing 4D images with pathology. Originally developed for processing longitudinal images of patients with traumatic brain injury, the tool contains new image analysis algorithms that combine registration and segmentation in a coherent framework, accounting for extreme changes due to extensive tissue damage.

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Cite this (7T Structural MRI scans ATAG, RRID:SCR_014084)

URL: http://www.nitrc.org/projects/atag_mri_scans/

Resource Type: Resource, data set, atlas, data or information resource

Data sets from the atlasing of the basal ganglia (ATAG) consortium, which provides ultra-high resolution 7Tesla (T) magnetic resonance imaging (MRI) scans from young, middle-aged, and elderly participants. They include whole-brain and reduced field-of-view MP2RAGE and T2 scans with ultra-high resolution at a sub millimeter scale. The data can be used to develop new algorithms that help building new high-resolution atlases both in the basic and clinical neurosciences. They can also be used to inform the exact positioning of deep-brain electrodes relevant in patients with Parkinsons disease and neuropsychiatric diseases.

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Cite this (ABC (Atlas Based Classification), RRID:SCR_005981)

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

Resource Type: Resource, software resource, image analysis software, workflow software, data processing software, software application

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.

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Cite this (aBEAT, RRID:SCR_002238)

URL: http://www.med.unc.edu/bric/ideagroup/free-softwares/abeat-a-toolbox-for-consistent-analysis-of-longitudinal-adult-brain-mri

Resource Type: Resource, image analysis software, data processing software, software application, software resource, software toolkit, image processing software

A 4D adult brain extraction and analysis toolbox with graphical user interfaces to consistently analyze 4D adult brain MR images. Single-time-point images can also be analyzed. Main functions of the software include image preprocessing, 4D brain extraction, 4D tissue segmentation, 4D brain labeling, ROI analysis. Linux operating system (64 bit) is required. A computer with 8G memory (or more) is recommended for processing many images simultaneously. The graphical user interfaces and overall framework of the software are implemented in MATLAB. The image processing functions are implemented with the combination of C/C++, MATLAB, Perl and Shell languages. Parallelization technologies are used in the software to speed up image processing.

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Cite this (ABIDE, RRID:SCR_003612)

URL: http://fcon_1000.projects.nitrc.org/indi/abide/

Resource Type: Resource, data set, data or information resource

Resting state functional magnetic resonance imaging (R-fMRI) datasets from 539 individuals with autism spectrum disorder (ASD) and 573 typical controls. This initiative involved 16 international sites, sharing 20 samples yielding 1112 datasets composed of both MRI data and an extensive array of phenotypic information common across nearly all sites. This effort is expected to facilitate discovery science and comparisons across samples. All datasets are anonymous, with no protected health information included.

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Cite this (ABSORB: Atlas Building by Self-Organized Registration and Bundling, RRID:SCR_007018)

URL: http://bric.unc.edu/ideagroup/free-softwares/ABSORB/

Resource Type: Resource, image analysis software, data processing software, source code, software application, software resource, registration software

This software package implements an algorithm for effective groupwise registration. The required input is a set of 3D MR intensity images (in Analyze format with paired .hdr and .img files) with a text file (.txt) listing all header file (.hdr) names. The output is the set of registered images together with the corresponding dense deformation fields. This software has been tested on Windows XP (32-bit) and Linux (64-bit, kernel version 2.6.18-194.el5). The images should be pre-processed before applying ABSORB: * All brain MR images used as inputs to ABSORB should be in the same situation (e.g., skull-stripped or not, cerebellum removed or not, etc.). * The input images should be in Analyze format with paired header and image files. This software was developed in IDEA group in UNC-Chapel Hill.

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Cite this (ADHD-200 Preprocessed Data, RRID:SCR_000576)

URL: http://neurobureau.projects.nitrc.org/ADHD200/Introduction.html

Resource Type: Resource, data set, data or information resource

Preprocessed versions of the ADHD-200 Global Competition data including both preprocessed versions of structural and functional datasets previously made available by the ADHD-200 consortium, as well as initial standard subject-level analyses. The ADHD-200 Sample is pleased to announce the unrestricted public release of 776 resting-state fMRI and anatomical datasets aggregated across 8 independent imaging sites, 491 of which were obtained from typically developing individuals and 285 in children and adolescents with ADHD (ages: 7-21 years old). Accompanying phenotypic information includes: diagnostic status, dimensional ADHD symptom measures, age, sex, intelligence quotient (IQ) and lifetime medication status. Preliminary quality control assessments (usable vs. questionable) based upon visual timeseries inspection are included for all resting state fMRI scans. In accordance with HIPAA guidelines and 1000 Functional Connectomes Project protocols, all datasets are anonymous, with no protected health information included. They hope this release will open collaborative possibilities and contributions from researchers not traditionally addressing brain data so for those whose specialties lay outside of MRI and fMRI data processing, the competition is now one step easier to join. The preprocessed data is being made freely available through efforts of The Neuro Bureau as well as the ADHD-200 consortium. They ask that you acknowledge both of these organizations in any publications (conference, journal, etc.) that make use of this data. None of the preprocessing would be possible without the freely available imaging analysis packages, so please also acknowledge the relevant packages and resources as well as any other specific release related acknowledgements. You must be logged into NITRC to download the ADHD-200 datasets, http://www.nitrc.org/projects/neurobureau

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Cite this (ADHD-200 Sample, RRID:SCR_005358)

URL: http://fcon_1000.projects.nitrc.org/indi/adhd200/index.html#

Resource Type: Resource, disease-related portal, data set, topical portal, portal, data or information resource

A grassroots initiative dedicated to accelerating the scientific community''''s understanding of the neural basis of ADHD through the implementation of open data-sharing and discovery-based science. They believe that a community-wide effort focused on advancing functional and structural imaging examinations of the developing brain will accelerate the rate at which neuroscience can inform clinical practice. The ADHD-200 Global Competition invited participants to develop diagnostic classification tools for ADHD diagnosis based on functional and structural magnetic resonance imaging (MRI) of the brain. Applying their tools, participants provided diagnostic labels for previously unlabeled datasets. The competition assessed diagnostic accuracy of each submission and invited research papers describing novel, neuroscientific ideas related to ADHD diagnosis. Twenty-one international teams, from a mix of disciplines, including statistics, mathematics, and computer science, submitted diagnostic labels, with some trying their hand at imaging analysis and psychiatric diagnosis for the first time. The data for the competition was provided by the ADHD-200 Consortium. Consortium members from institutions around the world provided de-identified, HIPAA compliant imaging datasets from almost 800 children with and without ADHD. A phenotypic file including all of the test set subjects and their diagnostic codes can be downloaded. Winner is presented. The ADHD-200 consortium included: * Brown University, Providence, RI, USA (Brown) * The Kennedy Krieger Institute, Baltimore, MD, USA (KKI) * The Donders Institute, Nijmegen, The Netherlands (NeuroImage) * New York University Medical Center, New York, NY, USA (NYU) * Oregon Health and Science University, Portland, OR, USA (OHSU) * Peking University, Beijing, P.R.China (Peking 1-3) * The University of Pittsburgh, Pittsburgh, PA, USA (Pittsburgh) * Washington University in St. Louis, St. Louis, MO, USA (WashU)

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Cite this (ADJUST, RRID:SCR_009526)

URL: http://www.unicog.org/pm/pmwiki.php/MEG/RemovingArtifactsWithADJUST

Resource Type: Resource, software resource

A completely automatic algorithm for artifact identification and removal in EEG data. ADJUST is based on Independent Component Analysis (ICA), a successful but unsupervised method for isolating artifacts from EEG recordings. ADJUST identifies artifacted ICA components by combining stereotyped artifact-specific spatial and temporal features. Features are optimised to capture blinks, eye movements and generic discontinuities. Once artifacted IC are identified, they can be simply removed from the data while leaving the activity due to neural sources almost unaffected.

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Cite this (Advanced Connectivity Analysis (ACA), RRID:SCR_014195)

URL: http://www.nitrc.org/projects/aca_rc

Resource Type: Resource, software resource, data acquisition software, data processing software, software application

A large scale functional connectivity data mining software package which enables large-scale seed-based analysis and brain-behavior analysis. It can examine a large number of seed regions with minimal user input. ACA has a brain-behavior analysis component to delineate associations among imaging biomarkers and one or more behavioral variables.

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Cite this (Age Related Atrophy Dataset, RRID:SCR_009528)

URL: http://www.bsl.ece.vt.edu/index.php?page=ara-dataset

Resource Type: Resource, data set, source code, software resource, data or information resource

Dataset of structural MR images of 70 subjects collected during 2008-2010 across a wide range of ages. The dataset also contains resting state fMRI for most subjects. The structural images are T1 weighted, T2 weighted-FLAIR, 25 direction DTI, and the T1 mapping DESPOT [1] sequence. Reconstructed T1 maps for each subject are also available. The aquisition protocol was designed to study structural differences between young and older adults including both shape and intensity changes. Anonymized DICOM image sessions and processed images for each subject are available. The data is licensed under the Creative Commons Attribution License. It may be used freely for commercial, academic, or other use, as long as the original source is properly cited. http://www.bsl.ece.vt.edu/index.php?page=ara-dataset

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Cite this (AHEAD, RRID:SCR_008890)

URL: http://www.nitrc.org/projects/ahead/

Resource Type: Resource, segmentation software, image analysis software, data processing software, software resource, software application

Open-source turnkey software for automatic hippocampus segmentation. Its primary use is for delineating hippocampus in T1-weighted MRI images. AHEAD is developed by Jung W. Suh, Hongzhi Wang, Sandhitsu Das, Brian Avants, Philip Cook, John Pluta and Paul Yushkevich, and colleagues at the Penn Image Computing and Science Laboratory (PICSL) at the University of Pennsylvania.

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Cite this (Allen Brain Atlas API, RRID:SCR_005984)

URL: http://www.brain-map.org/api/index.html

Resource Type: Resource, software resource, software application, source code

API and demo application for accessing the Allen Brain Atlas Mouse Brain data. Data available via the API includes download high resolution images, expression data from a 3D volume, 3D coordinates of the Allen Reference Atlas, and searching genes with similar gene expression profiles using NeuroBlast. Data made available includes: * High resolution images for gene expression, connectivity, and histology experiments, as well as annotated atlas images * 3-D expression summaries registered to a reference space for the Mouse Brain and Developing Mouse Brain * Primary microarray results for the Human Brain and Non-Human Primate * RNA sequencing results for the Developing Human Brain * MRI and DTI files for Human Brain The API consists of the following resources: * RESTful model access * Image download service * 3-D expression summary download service * Differential expression search services * NeuroBlast correlative searches * Image-to-image synchronization service * Structure graph download service

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