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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

http://www.neuralgate.org/download/NeuralAct

Software to visualize electrocorticographic (ECoG) and possibly also other kinds of neural activity (EEG / EMG/ DOT) on a 3D model of the cortical surface. The tool has been used to produce cortical activation images and image sequences in several recent studies using ECoG. The tool is written in matlab. The package is thoroughly documented and includes a demo.

Proper citation: NeuralAct (RRID:SCR_002066) 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://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.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

http://www.mcw.edu/EPRCenter.htm

Biomedical technology research center focusing on technological innovation and application of new techniques to biological problems. The main areas of research are free radicals, spin labeling, metal complexes, and metallo proteins. Spectrometers are available for S-, X-, L-, Q- , and W-band EPR, many with ENDOR, ELDOR, saturation-transfer, saturation-recovery, and multiquantum capabilities. * Development of multiquantum Q- and W-band spectrometers, including multiquantum ELDOR, development of time-locked sub-sampling (TLSS) for broadband detection of periodically modulated signals * Development of loop-gap resonators using finite element modeling of Maxwell''s equations * Application of multifrequency (1 to 100 GHz) electron paramagnetic resonance (EPR) to characterize paramagnetic centers * Study of relaxation processes using multifrequency pulse saturation recovery * Use of nitroxide radical spin labels to measure translational and rotational diffusion in biological systems, site-directed spin labeling (SDSL), and use of EPR for the detection of nitric oxide and oxy radicals

Proper citation: National Biomedical Electron Paramagnetic Resonance Center (RRID:SCR_006601) Copy   

•   Source: SciCrunch Registry

http://nac.spl.harvard.edu/

Biomedical Technology Resource Center that develops image processing and analysis techniques for basic and clinical neurosciences. The NAC research approach emphasizes both specific core technologies and collaborative application projects. The core activity of the center is the development of algorithms and techniques for postprocessing of imaging data. New segmentation techniques aid identification of brain structures and disease. Registration methods are used for relating image data to specific patient anatomy or one set of images to another. Visualization tools allow the display of complex anatomical and quantitative information. High-performance computing hardware and associated software techniques further accelerate algorithms and methods. Digital anatomy atlases are developed for the support of both interactive and algorithmic computational tools. Although the emphasis of the NAC is on the dissemination of concepts and techniques, specific elements of the core software technologies have been made available to outside researchers or the community at large. The NAC's core technologies serve the following major collaborative projects: Alzheimer's disease and the aging brain, morphometric measures in schizophrenia and schizotypal disorder, quantitative analysis of multiple sclerosis, and interactive image-based planning and guidance in neurosurgery. One or more NAC researchers have been designated as responsible for each of the core technologies and the collaborative projects.

Proper citation: Neuroimage Analysis Center (RRID:SCR_008998) Copy   

•   Source: SciCrunch Registry

http://mialab.mrn.org/data/index.html

An MRI data set that demonstrates the utility of a mega-analytic approach by identifying the effects of age and gender on the resting-state networks (RSNs) of 603 healthy adolescents and adults (mean age: 23.4 years, range: 12-71 years). Data were collected on the same scanner, preprocessed using an automated analysis pipeline based in SPM, and studied using group independent component analysis. RSNs were identified and evaluated in terms of three primary outcome measures: time course spectral power, spatial map intensity, and functional network connectivity. Results revealed robust effects of age on all three outcome measures, largely indicating decreases in network coherence and connectivity with increasing age. Gender effects were of smaller magnitude but suggested stronger intra-network connectivity in females and more inter-network connectivity in males, particularly with regard to sensorimotor networks. These findings, along with the analysis approach and statistical framework described, provide a useful baseline for future investigations of brain networks in health and disease.

Proper citation: MIALAB - Resting State Data (RRID:SCR_008914) Copy   

•   Source: SciCrunch Registry

http://mimic.physionet.org/

Collection of comprising deidentified health related data associated with patients who stayed in critical care units of Beth Israel Deaconess Medical Center between 2001 and 2012. Database includes information such as demographics, vital sign measurements made at bedside (~1 data point per hour), laboratory test results, procedures, medications, caregiver notes, imaging reports, and mortality (both in and out of hospital).

Proper citation: Medical Information Mart for Intensive Care-III (RRID:SCR_017384) Copy   

•   Source: SciCrunch Registry

http://ligand-expo.rutgers.edu/

An integrated data resource for finding chemical and structural information about small molecules bound to proteins and nucleic acids within the structure entries of the Protein Data Bank. Tools are provided to search the PDB dictionary for chemical components, to identify structure entries containing particular small molecules, and to download the 3D structures of the small molecule components in the PDB entry. A sketch tool is also provided for building new chemical definitions from reported PDB chemical components.

Proper citation: Ligand Expo (RRID:SCR_006636) 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

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