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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.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://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

http://www.loni.usc.edu/Software/SHIVA

A Java-based visualization and analysis application that can process 2D and 3D image files and provides convenient methods for users to overlay multiple datasets. * Simultaneous visualization of multiple image volumes. * Tools for labeling and masking of structures. * Framework for the Mouse Atlas Project.

Proper citation: Synchronized Histological Image Viewing Architecture (RRID:SCR_002690) Copy   

•   Source: SciCrunch Registry

http://www.nirep.org/

Project to develop software tools and provide shared image validation databases for rigorous testing of non-rigid image registration algorithms. NIREP will extend the scope of prior validation projects by developing evaluation criteria and metrics using large image populations, using richly annotated image databases, using computer simulated data, and increasing the number and types of evaluation criteria. The goal of this project is to establish, maintain, and endorse a standardized set of relevant benchmarks and metrics for performance evaluation of nonrigid image registration algorithms. Furthermore, these standards will be incorporated into an exportable computer program to automatically evaluate the registration accuracy of nonrigid image registration algorithms.

Proper citation: Non-Rigid Image Registration Evaluation Project (RRID:SCR_002505) Copy   

•   Source: SciCrunch Registry

http://www.loni.usc.edu/Software/FFT

Java library used for the execution of discrete Fourier transforms in 1-D, 2-D and 3-D through the implementation of Fast Fourier Transform (FFT) algorithms. * The FFT library has been written in Java for portability across different platforms, integrated into a single jar file for easy implementation. * The FFT library provides forward and backward fast Fourier transforms in 1-D, 2-D and 3-D with an easy-to-use manner. * The FFT requires the length equal to a number with an integer power of two. This library automatically examines the input data and detects the length to prevent improper execution.

Proper citation: FFT Library (RRID:SCR_002698) 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://rover.bsd.uchicago.edu/lfepr/

Biomedical technology research center that develops instrumentation, analysis techniques, spin probes and spin traps, and methodologies for imaging physiologically relevant aspects of tissue fluids, including high-resolution oxygen maps, with very low frequency electron paramagnetic resonance imaging (EPRI). Novel bridges and high-access, low-field magnet/gradient systems have produced physiologically relevant measurements and accommodate a number of resonant structures. The Center is a consortium between the University of Chicago, the University of Denver, the University of Maryland and Novosibirsk Institute of Organic Chemistry (NIOC), Russia.

Proper citation: Center for EPR Imaging in Vivo Physiology (RRID:SCR_001410) Copy   

•   Source: SciCrunch Registry

https://bli.uci.edu/laser-microbeam-program/

Biomedical technology research center dedicated to the use of lasers and optics in biology and medicine with activities in technological research and development, collaborative research, service, training, and dissemination. One of the primary goals of LAMMP is to facilitate translational research by rapidly moving basic science and technology discoveries from blackboard to benchtop to bedside. This is accomplished by combining state of the art optical technologies with specialized resource facilities for cell and tissue engineering, histopathology, pre-clinical animal models, and clinical care. The resource center has been organized into 3 cores: * Microscopy and Microbeam Technologies (MMT) for high-resolution functional imaging and manipulation of living cells and tissues * Medical Translational Technologies (MTT) for non- and minimally-invasive monitoring, treating, and imaging pre-clinical animal models and human subjects, and * Virtual Photonics Technologies (VPT) for developing computational models and methods that advance the performance of biophotonic technologies, and enhance the information content derived from optical measurements. LAMMP cores contain complementary technologies that are capable of quantitatively characterizing, imaging, and perturbing structure and biochemical function in cells and tissues with scalable resolution and depth sensitivity ranging from micrometers to centimeters.

Proper citation: Laser Microbeam and Medical Program (RRID:SCR_001409) Copy   

•   Source: SciCrunch Registry

http://www.cmu.edu/nmr-center/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on March 19,2024. Biomedical Technology Research Center that develops methodologies for the acquisition of morphological, biochemical, cellular, and functional information in living animals using nuclear magnetic resonance imaging (MRI) and spectroscopy (MRS). Novel techniques utilizing multidimensional MR imaging, magnetic resonance microscopy (MRM), and multinuclear in vivo spectroscopy are being applied to a wide range of problems in the biomedical sciences.

Proper citation: Pittsburgh NMR Center for Biomedical Research (RRID:SCR_001408) Copy   

•   Source: SciCrunch Registry

http://www.radiology.ucsf.edu/research/labs/hyperpolarized-mri-tech

Biomedical technology research center developing, investigating, and disseminating new hyperpolarized MR techniques, new 13C agents and specialized analysis open-source software for data reconstruction and interpretation. The Technology Research & Development projects will leverage the extensive DNP facilities and experience of the project leaders to develop improved, robust hyperpolarized MRI methods. These technology developments will be driven by Collaborative Projects led by outstanding clinical and basic scientists who aim to use hyperpolarized 13C MRI to accomplish the scientific goals of their funded research. These technical developments will also be disseminated to the Service Project investigators for extramural feedback and then widely to the scientific community via a dedicated website and onsite training. This center will provide state-of-the-art training in this new metabolic imaging field and sponsor a yearly symposium focused on hyperpolarized MR technology development.

Proper citation: Hyperpolarized MRI Technology Resource Center (RRID:SCR_001405) Copy   

•   Source: SciCrunch Registry

http://www.raraf.org/

Biomedical technology research center dedicated for radiobiological research with available ionizing radiations such as protons, alpha particles, and neutrons. RARAF is well-established and highly user-friendly. The focus of RARAF is the development of high-throughput single-cell/single-particle microbeams, which can deliver defined amounts of ionizing radiation into individual cells with a spatial resolution of a few microns or better. The ability of a microbeam to put double strand break damage at any specific known location in a given cell has allowed new approaches to the study of damage signaling.

Proper citation: Radiological Research Accelerator Facility (RRID:SCR_001425) Copy   

•   Source: SciCrunch Registry

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

Biomedical technology research center dedicated to the development of novel imaging methods for the basic scientist and the application of the methods to important biomedical questions. The CIVM has played a major role in the development of magnetic resonance microscopy with specialized MR imaging systems capable of imaging at more than 500,000x higher resolution than is common in the clinical domain. The CIVM was the first to demonstrate MR images using hyperpolarized 3He which has been moved from mouse to man with recent clinical trials performed at Duke in collaboration with GE. More recently the CIVM has developed the molecular imaging workbench---a system dedicated to multimodality cardiopulmonary imaging in the rodent. Their collaborators are employing these unique imaging systems in an extraordinary range of mouse and rat models of neurologic disease, cardiopulmonary disease and cancer to illuminate the underlying biology and explore new therapies.

Proper citation: Center for In Vivo Microscopy (RRID:SCR_001426) Copy   

•   Source: SciCrunch Registry

http://www.njbiomaterials.org/resbio_main.htm

Biomedical technology research center that works to develop integrated tools and technologies that advance the discovery of polymeric biomaterials for regenerative medicine, the delivery of biological agents, and the next generation of medical implants. To achieve its mission, RESBIO's research is focused on the development of combinatorial and computational approaches to biomaterials design and optimization. Within this framework, RESBIO employs and uses: * Advanced multi-photon confocal laser microscopy to explore, understand, and control the response of cells in contact with artificial surfaces * Electron microscopy techniques to study the effect of nano-scale surface morphological features on cell behavior RESBIO research emphasizes the integration of a strong synthetic effort to create new biomaterial candidates with the development of rapid screening techniques for key material and biological properties relevant to the performance of a biomaterial in a given medical application.

Proper citation: RESBIO (RRID:SCR_001424) Copy   

•   Source: SciCrunch Registry

https://www.med.upenn.edu/CAMIPM/

Biomedical technology research center dedicated to the development and application of innovative, novel magnetic resonance and optical imaging techniques. The facility's core sections provide research and computing resources for numerous user, collaborative, and training projects. The focus of this resource is on developing instrumentation, methodologies, and data analysis techniques for the quantitative assessment of functional, structural, and metabolic parameters in humans with the use of multinuclear magnetic resonance, novel spectral, perfusion, functional, and optical imaging techniques. These technological developments are driven by collaboration with scientists from within and outside University of Pennsylvania, the primary institution. Specifically, the Resource is focused on the development of quantitative, noninvasive MR and optical imaging based biomarkers for studying tissue metabolism and function, with an eye towards clinical translation through early diagnosis. The Center also provides support in the development and evaluation of new therapies in a variety of diseases.

Proper citation: Center for Magnetic Resonance and Optical Imaging (RRID:SCR_001428) Copy   

•   Source: SciCrunch Registry

http://www.ncigt.org/

Biomedical Technology Resource Center that serves as a national resource for all aspects of research into medical procedures that are enhanced by imaging. Its common goal is to provide more effective patient care. The center is focused on the multidisciplinary development of innovative image-guided intervention technologies to enable effective, less invasive clinical treatments that are not only more economical, but also produce better results for patients. The NCIGT is helping to implement this vision by serving as a proving ground for some of the next generation of medical therapies.

Proper citation: National Center for Image-Guided Therapy (RRID:SCR_001419) Copy   

•   Source: SciCrunch Registry