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http://itools.loni.usc.edu/

An infrastructure for managing of diverse computational biology resources - data, software tools and web-services. The iTools design, implementation and meta-data content reflect the broad NCBC needs and expertise (www.NCBCs.org).

Proper citation: iTools (RRID:SCR_009626) Copy   

•   Source: SciCrunch Registry

http://www.cise.ufl.edu/~abarmpou/lab/fanDTasia/

A Java applet tool for DT-MRI processing. It opens Diffusion-Weighted MRI datasets from user's computer and performs very efficient tensor field estimation using parallel threaded processing on user's browser. No installation is required. It runs on any operating system that supports Java (Windows, Mac, Linux,...). The estimated tensor field is guaranteed to be positive definite second order or higher order and is saved in user's local disc. MATLAB functions are also provided to open the tensor fields for your convenience in case you need to perform further processing. The fanDTasia Java applet provides also vector field visualization for 2nd and 4th-order tensors, as well as calculation of various anisotropic maps. Another useful feature is 3D fiber tracking (DTI-based) which is also shown using 3d graphics on the user's browser.

Proper citation: fanDTasia Java Applet: DT-MRI Processing (RRID:SCR_009624) Copy   

•   Source: SciCrunch Registry

http://www.nmr.mgh.harvard.edu/~jbm/jip/

Software toolkit for analysis of rodent and non-human primate fMRI data. The toolkit consists of binary executables, highly portable open-source c code, and image resources that enable 1) Automated registration based upon mutual information (affine, non-linear warps), with flexible control and visualization of each step; 2) visualization of 4-dimensional data using either mosaic or tri-planar display of the z/slice dimension, and integration of a general linear model for graphical display of time series analysis; 3) A simple and flexible 1st-order GLM for fMRI time series analysis, a 1st-order GLM analysis for PET data within the SRTM framework, plus a 2nd-order GLM analysis following the Worsley 2002 scheme, and 4) MRI templates to place your rodent and non-human primate data into standardized spaces.

Proper citation: JIP Analysis Toolkit (RRID:SCR_009588) Copy   

•   Source: SciCrunch Registry

http://econnectome.umn.edu/

An open-source MATLAB software package for imaging brain functional connectivity from electrophysiological signals. It provides interactive graphical interfaces for EEG/ECoG/MEG preprocessing, source estimation, connectivity analysis and visualization. Connectivity from EEG/ECoG/MEG can be mapped over sensor and source domains. This package is designed for use by researchers in neuroscience, psychology, cognitive science, clinical neurophysiology, neurology and other disciplines. The graphical interface-based platform requires little programming knowledge or experience with MATLAB. eConnectome is developed by the Biomedical Functional Imaging and Neuroengineering Laboratory at the University of Minnesota, directed by Dr. Bin He. The visualization module is jointly developed with Drs. Fabio Babiloni and Laura Astolfi at the University of Rome La Sapienza.

Proper citation: eConnectome (RRID:SCR_009618) 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.loni.usc.edu/Software/jViewbox

A portable software framework for medical imaging research. jViewbox consists of a set of Java classes organized under a simple but extensive API that provides the core functionality of 2D image presentation needed by most imaging applications. It follows Java's Swing model closely to make it easy for application developers to build GUIs where end users can use various tools in a tool bar to manipulate the image displays. No optional add-ons or native code is used, which makes jViewBox compatible with any standard Java 2 Runtime Environment (version 1.3 or later).

Proper citation: jViewbox (RRID:SCR_008274) Copy   

•   Source: SciCrunch Registry

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

A lightweight framework for setting up dependency-driven processing pipelines. The tool is essentially a configurable shell script (sh/bash), which can be included in other scripts and primarily provides a small number of utility functions for dependency checking and NFS-safe file locking for cluster processing.

Proper citation: Lightweight Data Pipeline (RRID:SCR_014135) Copy   

•   Source: SciCrunch Registry

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

A collection of methods for comparing the performance of different image algorithms. These methods generate quantitative scores that measure divergences to a standard.

Proper citation: SCORE (RRID:SCR_014165) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

http://connectomes.utah.edu/

A web-compliant application that allows connectomics visualization by converting datasets to web-optimized tiles, delivering volume transforms to client devices, and providing groups of users with connectome annotation tools and data simultaneously via conventional internet connections. Viking is an extensible tool for connectomics analysis and is generalizable to histomics applications.

Proper citation: Viking Viewer for Connectomics (RRID:SCR_005986) Copy   

•   Source: SciCrunch Registry

http://mrir.med.miami.edu:8000/midas

Software for processing, display, and analysis of magnetic resonance spectroscopic imaging data. MIDAS supports a "whole-brain" MRSI acquisition method that has been implemented on MRI systems from three major manufacturers., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: MIDAS (RRID:SCR_015704) Copy   

•   Source: SciCrunch Registry

http://www.iu.edu/~beca/

Visualization and analysis software for interactive visual exploration and mining of fiber-tracts and brain networks with their genetic determinants and functional outcomes. BECA includes an fMRI and Diseases Analysis version as well as a Genome Explorer version.

Proper citation: BECA (RRID:SCR_015846) Copy   

•   Source: SciCrunch Registry

https://www.icpsr.umich.edu/icpsrweb/content/addep/index.html

Provides access to data including wide range of topics related to disability. ADDEP data can be used to better understand and inform the implementation of Americans with Disabilities Act and other disability policies.

Proper citation: Archive of Data on Disability to Enable Policy (ADDEP) (RRID:SCR_016315) 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

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

https://cismm.web.unc.edu/

Biomedical technology research center that develops force technologies applicable over a wide range of biological settings, from the single molecule to the tissue, with integrated systems that orchestrate facile instrument control, multimodal imaging, and analysis through visualization and modeling. The Force Microscope Technologies Core designs instruments in an area of science where there are unusual opportunities: the measurement of forces and the integration with optical microscopy. Force technologies play the obvious role of both measuring events in the sample and modifying the sample during the experiment. It is through the microscope that the force data is correlated with simultaneous 3D optical images. The force technology development includes the magnetic bead technology in the 3D Force Microscope project, Atomic Force Microscopy in the nanoManipulator project, and Control Software to drive the instrumentation. This core is focused on providing the physical capability to perform the experiments and probe structure/property correlations. The Ideal User Interfaces core makes the connection between the user and the instrument, the model building, and the data. This includes control systems that allow the user to move the bead inside the cell culture with a handheld pen and the visualization techniques to view the optical microscope data as a rendered 3D image collocated with the force data. Using data to create, change, and understand a model is the focus of the Advanced Model Fitting and Analysis core. The quantitative reduction of images to structural, shape, and velocity parameters is the goal of Image Analysis. The immediate understanding of correlations across image fields and between data sets in the challenge of Visualization. The power of combining the strength of a computer science graphics group with a microscopy technology group is most evident in the Graphics Hardware Acceleration project, which seeks to harness the speed of graphics processors for microscope data analysis and simulation. The Advanced Technology core pushes the boundaries of the Human Computer Interface through the investigation of improved techniques for the interaction of users with virtual environments, the real time lighting of virtual settings, and the enabling of multi-person collaboration. These techniques are validated and evaluated through physiological measures in virtual environments effectiveness evaluation studies.

Proper citation: Computer Integrated Systems for Microscopy and Manipulation (RRID:SCR_001413) Copy   

•   Source: SciCrunch Registry

http://octresearch.org/

Biomedical technology research center that pioneers and provides access to microscopic imaging instruments for biologic and clinical research. Optical coherence tomography (OCT) has evolved over the last two decades to become a standard of care for diagnostic ophthalmic imaging and is poised to make significant impact in the fields of cardiology and gastrointestinal endoscopy. Access to state-of-the-art instrumentation, however, has been limited to a relatively few research laboratories and the optimization of instruments for new biomedical applications has hindered the investigation of new opportunities. A major focus of CBORT will be to cultivate strategic research collaborations and respond to a pressing need for application-specific OCT instrumentation and hardware.

Proper citation: Center for Biomedical OCT Research (RRID:SCR_001418) Copy   

•   Source: SciCrunch Registry

http://www.biomemsrc.org/

Biomedical technology research center that provides biomedical investigators with novel microsystems engineering tools for biological discovery, diagnostic, prognostic, and therapeutic applications. Thrust areas of interest are the development of novel living cell-based, lab-on-a-chip type devices for sorting blood cells, for high-throughput biochemistry in small volumes, and for studying cellular behavior in controlled microenvironments.

Proper citation: BioMEMS Resource Center (RRID:SCR_001417) Copy   

•   Source: SciCrunch Registry