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SciCrunch Registry is a curated repository of scientific resources, with a focus on biomedical resources, including tools, databases, and core facilities - visit SciCrunch to register your resource.

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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   


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   


  • RRID:SCR_001417

    This resource has 1+ mentions.

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   


  • RRID:SCR_014649

    This resource has 50+ mentions.

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   


  • RRID:SCR_002066

    This resource has 10+ mentions.

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   


  • RRID:SCR_018733

    This resource has 1+ mentions.

https://www.biosimulations.org/

Web tool for sharing and re-using biomodels, simulations, and visualizations of simulations results. Supports variety of modeling frameworks including kinetic, constraint based, and logical modeling, model formats including BNGL, CellML, SBML, and simulation tools including COPASI, libRoadRunner/tellurium, NFSim, VCell.

Proper citation: BioSimulations (RRID:SCR_018733) Copy   


  • RRID:SCR_025563

    This resource has 1+ mentions.

https://brainlife.io/docs/using_ezBIDS/

Web-based BIDS conversion tool to convert neuroimaging data and associated metadata to BIDS standard. Guided standardization of neuroimaging data interoperable with major data archives and platforms.

Proper citation: ezBIDS (RRID:SCR_025563) Copy   


  • RRID:SCR_008914

    This resource has 10+ mentions.

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   


  • RRID:SCR_002569

    This resource has 1+ mentions.

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   


  • RRID:SCR_006288

    This resource has 1+ mentions.

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   


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   


https://yeatmanlab.github.io/pyAFQ/

Software package focused on automated delineation of major fiber tracts in individual human brains, and quantification of tissue properties within the tracts.Software for automated processing and analysis of diffusion MRI data. Automates tractometry.

Proper citation: Automated Fiber Quantification in Python (RRID:SCR_023366) Copy   


  • RRID:SCR_016911

    This resource has 1+ mentions.

https://github.com/QTIM-Lab/DeepNeuro

Software Python package for neuroimaging data. Framework to design and train neural network architectures. Used in medical imaging community to ensure consistent performance of networks across variable users, institutions, and scanners.

Proper citation: DeepNeuro (RRID:SCR_016911) Copy   


https://kimlab.io/brain-map/DevCCF/

Open access multimodal 3D atlases of developing mouse brain that can be used to integrate mouse brain imaging data for visualization, education, cell census mapping, and more. Atlas ages include E11.5, E13.5, E15.5, E18.5, P4, P14, and P56. Web platform can be utilized to visualize and explore the atlas in 3D. Downloadable atlas can be used to align multimodal mouse brain data. Morphologically averaged symmetric template brains serve as the basis reference space and coordinate system. Anatomical labels are manually drawn in 3D based on the prosomeric model. For additional references, the P56 template includes templates and annotations from the aligned Allen Mouse Brain Common Coordinate Framework (Allen CCFv3) and aligned Molecular Atlas of the Adult Mouse Brain.

Proper citation: 3D Developmental Mouse Brain Common Coordinate Framework (RRID:SCR_025544) Copy   


  • RRID:SCR_007283

    This resource has 100+ mentions.

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   


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   


  • RRID:SCR_014165

    This resource has 100+ mentions.

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   


  • RRID:SCR_017449

    This resource has 100+ mentions.

https://neuron.yale.edu/neuron/

Software for computational neurophysiology. Simulation environment is used for building and using computational models of neurons and networks of neurons. NEURON Users Group can participate in collaborative development of documentation, tutorials, and software.

Proper citation: NEURON (RRID:SCR_017449) Copy   


  • RRID:SCR_013152

    This resource has 10+ mentions.

http://surfer.nmr.mgh.harvard.edu/fswiki/Tracula

Software tool developed for automatically reconstructing a set of major white matter pathways in the brain from diffusion weighted images using probabilistic tractography. This method utilizes prior information on the anatomy of the pathways from a set of training subjects. By incorporating this prior knowledge in the reconstruction procedure, our method obviates the need for manual intervention with the tract solutions at a later stage and thus facilitates the application of tractography to large studies. The trac-all script is used to preprocess raw diffusion data (correcting for eddy current distortion and B0 field inhomogenities), register them to common spaces, model and reconstruct major white matter pathways (included in the atlas) without any manual intervention. trac-all may be used to execute all the above steps or parts of it depending on the dataset and user''''s preference for analyzing diffusion data. Alternatively, scripts exist to execute chunks of each processing pipeline, and individual commands may be run to execute a single processing step. To explore all the options in running trac-all please refer to the trac-all wiki. In order to use this script to reconstruct tracts in Diffusion images, all the subjects in the dataset must have Freesurfer Recons.

Proper citation: TRACULA (RRID:SCR_013152) Copy   


  • RRID:SCR_017448

https://github.com/nebneuron/neural-ideal

Software package for extracting neural activity codes.

Proper citation: Neural Ideal (RRID:SCR_017448) Copy   



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