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http://www.fmri.wfubmc.edu/cms/software

Research group based in the Department of Radiology of Wake Forest University School of Medicine devoted to the application of novel image analysis methods to research studies. The ANSIR lab also maintains a fully-automated functional and structural image processing pipeline supporting the image storage and analysis needs of a variety of scientists and imaging studies at Wake Forest. Software packages and toolkits are currently available for download from the ANSIR Laboratory, including: WFU Biological Parametric Mapping Toolbox, WFU_PickAtlas, and Adaptive Staircase Procedure for E-Prime.

Proper citation: Advanced Neuroscience Imaging Research Laboratory Software Packages (RRID:SCR_002926) Copy   

•   Source: SciCrunch Registry

http://imaging.indyrad.iupui.edu/projects/SPHARM/

A matlab-based 3D shape modeling and analysis toolkit, and is designed to aid statistical shape analysis for identifying morphometric changes in 3D structures of interest related to different conditions. SPHARM-MAT is implemented based on a powerful 3D Fourier surface representation method called SPHARM, which creates parametric surface models using spherical harmonics.

Proper citation: SPHARM-MAT (RRID:SCR_002545) Copy   

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http://www.civm.duhs.duke.edu/neuro2012ratatlas/

Multidimensional atlas of the adult Wistar rat brain based on magnetic resonance histology (MRH). The atlas has been carefully aligned with the widely used Paxinos-Watson atlas based on optical sections to allow comparisons between histochemical and immuno-marker data, and the use of the Paxinos-Watson abbreviation set. Our MR atlas attempts to make a seamless connection with the advantageous features of the Paxinos-Watson atlas, and to extend the utility of the data through the unique capabilities of MR histology: a) ability to view the brain in the skull with limited distortion from shrinkage or sectioning; b) isotropic spatial resolution, which permits sectioning along any arbitrary axis without loss of detail; c) three-dimensional (3D) images preserving spatial relationships; and d) widely varied contrast dependent on the unique properties of water protons. 3D diffusion tensor images (DTI) at what we believe to be the highest resolution ever attained in the rat provide unique insight into white matter structures and connectivity. The 3D isotropic data allow registration of multiple data sets into a common reference space to provide average atlases not possible with conventional histology. The resulting multidimensional atlas that combines Paxinos-Watson with multidimensional MRH images from multiple specimens provides a new, comprehensive view of the neuroanatomy of the rat and offers a collaborative platform for future rat brain studies. To access the atlas, click view supplementary materials in CIVMSpace at the bottom of the following webpage.

Proper citation: Adult Wistar Rat Atlas (RRID:SCR_006288) Copy   

•   Source: SciCrunch Registry

https://www.openanatomy.org/

Project aims to change anatomy atlas by building atlases through open data, community based collaborative development, and free distribution of medical knowledge. Provides access to several 2D and 3D browser based tools.

Proper citation: Open Anatomy Project (RRID:SCR_022141) Copy   

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http://www.med.unc.edu/bric/ideagroup/free-softwares/unc-infant-0-1-2-atlases

3 atlases dedicated for neonates, 1-year-olds, and 2-year-olds. Each atlas comprises a set of 3D images made up of the intensity model, tissue probability maps, and anatomical parcellation map. These atlases are constructed with the help of state-of-the-art infant MR segmentation and groupwise registration methods, on a set of longitudinal images acquired from 95 normal infants (56 males and 39 females) at neonate, 1-year-old, and 2-year-old.

Proper citation: UNC Infant 0-1-2 Atlases (RRID:SCR_002569) Copy   

•   Source: SciCrunch Registry

http://braininfo.rprc.washington.edu

Portal to neuroanatomical information on the Web that helps you identify structures in the brain and provides a variety of information about each structure by porting you to the best of 1500 web pages at 100 other neuroscience sites. BrainInfo consists of three basic components: NeuroNames, a developing database of definitions of neuroanatomic structures in four species, their most common acronyms and their names in eight languages; NeuroMaps, a digital atlas system based on 3-D canonical stereotaxic atlases of rhesus macaque and mouse brains and programs that enable one to map data to standard surface and cross-sectional views of the brains for presentation and publication; and the NeuroMaps precursor: Template Atlas of the Primate Brain, a 2-D stereotaxic atlas of the longtailed (fascicularis) macaque brain that shows the locations of some 250 architectonic areas of macaque cortex. The NeuroMaps atlases will soon include a number of overlays showing the locations of cortical areas and other neuroscientific data in the standard frameworks of the macaque and mouse atlases. Viewers are encouraged to use NeuroNames as a stable source of unique standard terms and acronyms for brain structures in publications, illustrations and indexing systems; to use templates extracted from the NeuroMaps macaque and mouse brain atlases for presenting neuroscientific information in image format; and to use the Template Atlas for warping to MRIs or PET scans of the macaque brain to estimate the stereotaxic locations of structures.

Proper citation: BrainInfo (RRID:SCR_003142) Copy   

•   Source: SciCrunch Registry

http://www.bmu.psychiatry.cam.ac.uk/software/

Suite of programs developed for fMRI analysis in a Virtual Pipeline Laboratory facilitates combining program modules from different software packages into processing pipelines to create analysis solutions which are not possible with a single software package alone. Current pipelines include fMRI analysis, statistical testing based on randomization methods and fractal spectral analysis. Pipelines are continually being added. The software is mostly written in C. This fMRI analysis package supports batch processing and comprises the following general functions at the first level of individual image analysis: movement correction (interpolation and regression), time series modeling, data resampling in the wavelet domain, hypothesis testing at voxel and cluster levels. Additionally, there is code for second level analysis - group and factorial or ANOVA mapping - after co-registration of voxel statistic maps from individual images in a standard space. The main point of difference from other fMRI analysis packages is the emphasis throughout on the use of data resampling (permutation or randomization) as a basis for inference on individual, group and factorial test statistics at voxel and cluster levels of resolution.

Proper citation: Cambridge Brain Activation (RRID:SCR_007109) Copy   

•   Source: SciCrunch Registry

https://ida.loni.usc.edu/login.jsp

Archive used for archiving, searching, sharing, tracking and disseminating neuroimaging and related clinical data. IDA is utilized for dozens of neuroimaging research projects across North America and Europe and accommodates MRI, PET, MRA, DTI and other imaging modalities.

Proper citation: LONI Image and Data Archive (RRID:SCR_007283) Copy   

•   Source: SciCrunch Registry

http://nsr.bioeng.washington.edu/

Database of physiological, pharmacological, and pathological information on humans and other organisms and integration through computational modeling. Models include everything from diagrammatic schema, suggesting relationships among elements composing a system, to fully quantitative, computational models describing the behavior of physiological systems and an organism''s response to environmental change. Each mathematical model is an internally self-consistent summary of available information, and thereby defines a working hypothesis about how a system operates. Predictions from such models are subject to test, with new results leading to new models.BR /> A Tool developed for the NSR Physiome project is JSim, an open source, free software. JSim is a Java-based simulation system for building quantitative numeric models and analyzing them with respect to experimental reference data. JSim''s primary focus is in physiology and biomedicine, however its computational engine is quite general and applicable to a wide range of scientific domains. JSim models may intermix ODEs, PDEs, implicit equations, integrals, summations, discrete events and procedural code as appropriate. JSim''s model compiler can automatically insert conversion factors for compatible physical units as well as detect and reject unit unbalanced equations. JSim also imports the SBML and CellML model archival formats. All JSim models are open source. Goals of the Physiome Project: - To develop and database observations of physiological phenomenon and interpret these in terms of mechanism (a fundamentally reductionist goal). - To integrate experimental information into quantitative descriptions of the functioning of humans and other organisms (modern integrative biology glued together via modeling). - To disseminate experimental data and integrative models for teaching and research. - To foster collaboration amongst investigators worldwide, to speed up the discovery of how biological systems work. - To determine the most effective targets (molecules or systems) for therapy, either pharmaceutic or genomic. - To provide information for the design of tissue-engineered, biocompatible implants.

Proper citation: NSR Physiome Project (RRID:SCR_007379) Copy   

•   Source: SciCrunch Registry

https://bams1.org/

Knowledge management system designed to handle neurobiological information at different levels of organization of vertebrate nervous system. Database and repository for information about neural circuitry, storing and analyzing data concerned with nomenclature, taxonomy, axonal connections, and neuronal cell types. Handles data and metadata collated from original literature, or inserted by scientists that is associated to four levels of organization of vertebrate nervous system. Data about expressed molecules, neuron types and classes, brain regions, and networks of brain regions.

Proper citation: Brain Architecture Management System (RRID:SCR_007251) Copy   

•   Source: SciCrunch Registry

https://www.mristudio.org/

An image processing program running under Windows suitable for such tasks as tensor calculation, color mapping, fiber tracking, and 3D visualization. Most of operations can be done with only a few clicks. This tool evolved from DTI Studio. Tools in the program can be grouped in the following way: * Image Viewer * Diffusion Tensor Calculations * Fiber Tracking and Editing * 3D Visualization * Image File Management * Region of Interesting (ROI) Drawing and Statistics * Image Registration

Proper citation: MRI Studio (RRID:SCR_001398) Copy   

•   Source: SciCrunch Registry

http://bmsr.usc.edu/software/pneuma/

A set of modules that are used to simulate the autoregulation of the cardiovascular and respiratory systems under conditions of changing sleep-wake state and a variety of physiological and pharmacological interventions. It models the dynamic interactions that take place among the various component mechanisms, including those involved in the chemical control of breathing, heart rate, and blood pressure, as well as the effects of changes in the sleep-wake state and arousal from sleep. PNEUMA includes the autonomic control of the cardiovascular system, chemoreflex and state-related control of breath-to-breath ventilation, state-related and chemoreflex control of upper airway potency, as well as respiratory and circulatory mechanics. The model is capable of simulating the cardiorespiratory responses to sleep onset, arousal, continuous positive airway pressure, the administration of inhaled carbon dioxide and oxygen, Valsalva and Mueller maneuvers, and Cheyne-Stokes respiration during sleep. In PNEUMA 3.0, we have extended the existing integrative model of respiratory, cardiovascular, and sleepwake state control, to incorporate a sub-model of glucoseinsulinfatty acid regulation. The extended model is capable of simulating the metabolic control of glucoseinsulin dynamics and its interactions with the autonomic nervous system. The interactions between autonomic and metabolic control include the circadian regulation of epinephrine secretion, epinephrine regulation on dynamic fluctuations in glucose and free fatty acids in plasma, metabolic coupling among tissues and organs mediated by insulin and epinephrine, as well as the effect of insulin on peripheral vascular sympathetic activity. This extended model represents a starting point from which further in silico investigations into the interaction between the autonomic nervous system and the metabolic control system can proceed. Features in PNEUMA 3.0 * Incorporates metabolic component based on prior models of glucose-insulin regulation and free fatty acid (FFA) regulation. * Changes in sympathetic activity from the autonomic portion of PNEUMA produce changes in epinephrine output, which in turn affects the metabolic sub-model. * Inputs from the dietary intake of glucose and external interventions, such as insulin injections, have also been incorporated. * Also incorporated is autonomic feedback from the metabolic component to the rest of PNEUMA: changes in insulin level lead to changes in sympathetic tone. System Requirements: PNEUMA requires Matlab R2007b or higher with the accompanying version of Simulink to be installed on your computer.

Proper citation: PNEUMA (RRID:SCR_001391) Copy   

•   Source: SciCrunch Registry

http://radiology.arizona.edu/CGRI/

Biomedical technology resource center that develops new gamma-ray imaging instruments and techniques that yield substantially improved spatial and temporal resolutions. The Center makes its imagers and expertise available to a wide community of biomedical and clinical researchers through collaborative and service-oriented interactions. The collaborative research applies these new imaging tools to basic research in functional genomics, proteomics, cancer, cardiovascular disease and cognitive neuroscience, and to clinical research in tumor detection and other selected topics. There are five core research projects: * Detector technology research and development * Reconstruction algorithms and system modeling * Data acquisition, signal processing, and system development * Image-quality assessment and system optimization * Techniques for molecular imaging

Proper citation: Center for Gamma Ray Imaging (RRID:SCR_001384) Copy   

•   Source: SciCrunch Registry

http://www.nb.uw.edu/

Biomedical technology research center that provides state-of-the-art surface analysis expertise, instrumentation, experimental protocols, and data analysis methods to address surface-related biomedical problems. NESAC/BIO develops and applies surface science methodologies that produce a full understanding of the surface composition, structure, spatial distribution, and orientation of biomaterials and adsorbed biomolecules. The NESAC/BIO program identifies areas where surface science must evolve to keep pace with the growth in biochemical knowledge and biomaterial fabrication technology, and develops instrumentation, experimental protocols, and data analysis methods to achieve this evolution. NESAC/BIO provides state-of-the-art surface analysis tools to researchers in the biomedical community. You can gain access to the NESAC/BIO facilities in one of the following ways: * Collaborative: Propose a project to collaborate on with NESAC/BIO. The project should be rewarding for both groups, and the results should reflect the utility of surface analysis for biomedical research * Service: Ask NESAC/BIO to analyze your biomaterial specimens. The spectra obtained from the analyses will be interpreted for you. * Training: Visit the University of Washington to receive training in surface analysis and personally run experiments for your individual research projects. These experiments should have a high probability for yielding useful information and should not involve the development of new ESCA techniques or methodologies.

Proper citation: National ESCA and Surface Analysis Center for Biomedical Problems (RRID:SCR_001430) Copy   

•   Source: SciCrunch Registry

http://www.farsight-toolkit.org/wiki/FARSIGHT_Toolkit

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 23, 2022. A collection of software modules for image data handling, pre-processing, segmentation, inspection, editing, post-processing, and secondary analysis. These modules can be scripted to accomplish a variety of automated image analysis tasks. All of the modules are written in accordance with software practices of the Insight Toolkit Community. Importantly, all modules are accessible through the Python scripting language which allows users to create scripts to accomplish sophisticated associative image analysis tasks over multi-dimensional microscopy image data. This language works on most computing platforms, providing a high degree of platform independence. Another important design principle is the use of standardized XML file formats for data interchange between modules.

Proper citation: Farsight Toolkit (RRID:SCR_001728) Copy   

•   Source: SciCrunch Registry

http://www.nesys.uio.no/Atlas3D/

A multi-platform visualization tool which allows import and visualization of 3-D atlas structures in combination with tomographic and histological image data. The tool allows visualization and analysis of the reconstructed atlas framework, surface modeling and rotation of selected structures, user-defined slicing at any chosen angle, and import of data produced by the user for merging with the atlas framework. Tomographic image data in NIfTI (Neuroimaging Informatics Technology Initiative) file format, VRML and PNG files can be imported and visualized within the atlas framework. XYZ coordinate lists are also supported. Atlases that are available with the tool include mouse brain structures (3-D reconstructed from The Mouse Brain in Stereotaxic Coordinates by Paxinos and Franklin (2001)) and rat brain structures (3-D reconstructed from The Rat Brain in Stereotaxic Coordinates by Paxinos and Watson (2005)). Experimental data can be imported in Atlas3D and warped to atlas space, using manual linear registration, with the possibility to scale, rotate, and position the imported data. This facilitates assignment of location and comparative analysis of signal location in tomographic images.

Proper citation: Atlas3D (RRID:SCR_001808) Copy   

•   Source: SciCrunch Registry

http://bmsr.usc.edu/software/adapt/

Software tool as plug-in developed for ImageJ/FIJI platform to automatically detect and analyse cell migration and morphodynamics. Provides whole cell analysis of multiple cells, while also returning data on individual membrane protrusion events.

Proper citation: ADAPT (RRID:SCR_006769) Copy   

•   Source: SciCrunch Registry

https://github.com/ReproBrainChart

Open data resource for mapping brain development and its associations with mental health. Integrates data from 5 large studies of brain development in youth from three continents (N = 6,346). Bifactor models were used to create harmonized psychiatric phenotypes, capturing major dimensions of psychopathology. Neuroimaging data were carefully curated and processed using consistent pipelines in a reproducible manner.

Proper citation: Reproducible Brain Charts (RRID:SCR_027837) Copy   

•   Source: SciCrunch Registry

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

Training material for the MS lesion segmentation challenge 2008 to compare different algorithms to segment the MS lesions from brain MRI scans. Data used for the workshop is composed of 54 brain MRI images and represents a range of patients and pathology which was acquired from Children's Hospital Boston and University of North Carolian. Data has initially been randomized into three groups: 20 training MRI images, 24 testing images for the qualifying and 8 for the onsite contest at the 2008 workshop. The downloadable online database consists now of the training images (including reference segmentations) and all the 32 combined testing images (without segmentations). The naming has not been changed in comparison to the workshop compeition in order to allow easy comparison between the workshop papers and the online database papers. One dataset has been removed (UNC_test1_Case02) due to considerable motion present only in its T2 image (without motion artifacts in T1 and FLAIR). Such a dataset unfairly penalizes methods that use T2 images versus methods that don't use the T2 image. Currently all cases have been segmented by expert raters at each institution. They have significant intersite variablility in segmentation. MS lesion MRI image data for this competition was acquired seperately by Children's Hospital Boston and University of North Carolina. UNC cases were acquired on Siemens 3T Allegra MRI scanner with slice thickness of 1mm and in-plane resolution of 0.5mm. To ease the segmentation process all data has been rigidly registered to a common reference frame and resliced to isotrophic voxel spacing using b-spline based interpolation. Pre-processed data is stored in NRRD format containing an ASCII readable header and a separate uncompressed raw image data file. This format is ITK compatible. If you want to join the competition, you can download data set from links here, and submit your segmentation results at http://www.ia.unc.edu/MSseg after registering your team. They require team name, password, and email address for future contact. Once experiment is completed, you can submit the segmentation data in a zip file format. Please refer submission page for uploading data format.

Proper citation: MS lesion segmentation challenge 2008 (RRID:SCR_002425) Copy   

•   Source: SciCrunch Registry

http://fmri.wfubmc.edu/software/Bpm

Software toolbox that performs SPM analysis with voxel-wise imaging covariates. The BPM toolbox incorporates information obtained from other modalities as regressors in a voxel-wise analysis, thereby permitting investigation of more sophisticated hypotheses. The BPM toolbox has been developed in Matlab with a user-friendly interface for performing analyses, including voxel-wise multimodal correlation, ANCOVA, and multiple regression. It has a high degree of integration with the SPM (statistical parametric mapping) software relying on it for visualization and statistical inference. Furthermore, statistical inference for a correlation field, rather than a widely used T-field, has been implemented in the correlation analysis for more accurate results. Requirements: * SPM2 or SPM5 * MATLAB version 6.5 or higher

Proper citation: WFU Biological Parametric Mapping Toolbox (RRID:SCR_002613) Copy   

•   Source: SciCrunch Registry