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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.
https://sourceforge.net/projects/sivic/
Software framework and application suite for processing and visualization of DICOM MR Spectroscopy data. Through the use of DICOM, SIVIC aims to facilitate the application of MRS in medical imaging studies.
Proper citation: Spectroscopic Imaging, VIsualization, and Computing (SIVIC) (RRID:SCR_027875) Copy
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
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
http://code.google.com/p/annotare/
A software tool for annotating biomedical investigations and the resulting data, then producing a MAGE-TAB file. This software is a standalone desktop which features: an editor function, an annotation modifier, incorporation of terms from biomedical ontologies, standard templates for common experiment types, a design aid to help create a new document, and a validator that checks for syntactic and semantic violations.
Proper citation: Annotare (RRID:SCR_000319) 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
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
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://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
http://web.mit.edu/spectroscopy/facilities/lbrc.html
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on July 31,2025. Biomedical technology research center that develops basic scientific understanding and new techniques required for advancing clinical applications of lasers and spectroscopy. LBRC merges optical spectroscopy, imaging, scattering, and interferometry techniques to study biophysics and biochemistry of healthy and diseased biological structures from subcellular to entire-organ scale.
Proper citation: Laser Biomedical Research Center (RRID:SCR_000106) Copy
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
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
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
https://github.com/Washington-University/HCPpipelines
Software package as set of tools, primarily shell scripts, for processing multi-modal, high-quality MRI images for the Human Connectome Project. Minimal preprocessing pipelines for structural, functional, and diffusion MRI that were developed by the HCP to accomplish many low level tasks, including spatial artifact/distortion removal, surface generation, cross-modal registration, and alignment to standard space.
Proper citation: HCP Pipelines (RRID:SCR_026575) Copy
Biomedical technology research center that focuses on development of unique magnetic resonance (MR) imaging and spectroscopy methodologies and instrumentation for the acquisition of structural, functional, and biochemical information non-invasively in humans, and utilizing this capability to investigate organ function in health and disease. The distinctive feature of this resource is the emphasis on ultrahigh magnetic fields (7 Tesla and above), which was pioneered by this BTRC. This emphasis is based on the premise that there exists significant advantages to extracting biomedical information using ultrahigh magnetic fields, provided difficulties encountered by working at high frequencies corresponding to such high field strengths can be overcome by methodological and engineering solutions. This BTRC is home to some of the most advanced MR instrumentation in the world, complemented by human resources that provide unique expertise in imaging physics, engineering, and signal processing. No single group of scientists can successfully carry out all aspects of this type of interdisciplinary biomedical research; by bringing together these multi-disciplinary capabilities in a synergistic fashion, facilitating these interdisciplinary interactions, and providing adequate and centralized support for them under a central umbrella, this BTRC amplifies the contributions of each of these groups of scientists to basic and clinical biomedical research. Collectively, the approaches and instrumentation developed in this BTRC constitute some of the most important tools used today to study system level organ function and physiology in humans for basic and translational research, and are increasingly applied world-wide. CMRR Faculty conducts research in a variety of areas including: * High field functional brain mapping in humans; methodological developments, mechanistic studies, and neuroscience applications * Metabolism, bioenergetics, and perfusion studies of human pathological states (tumors, obesity, diabetes, hepatic encephalopathy, cystic fibrosis, and psychiatric disorders) * Cardiac bioenergetics under normal and pathological conditions * Automated magnetic field shimming methods that are critical for spectroscopy and ultrafast imaging at high magnetic fields * Development of high field magnetic resonance imaging and spectroscopy techniques for anatomic, physiologic, metabolic, and functional studies in humans and animal models * Radiofrequency (RF) pulse design based on adiabatic principles * Development of magnetic resonance hardware for high fields (e.g. RF coils, pre-amplifiers, digital receivers, phased arrays, etc.) * Development of software for data analysis and display for functional brain mapping.
Proper citation: Center for Magnetic Resonance Research (RRID:SCR_003148) Copy
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
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
http://www.imagwiki.nibib.nih.gov/
Special interest group that brings together program officers who have a shared interest in applying modeling and analysis methods to biomedical systems. The meetings are formatted to facilitate an open discussion of what is currently being supported, and for planning future directions in these areas. At each meeting, time is allotted to hear focused presentations from one or two participants to discuss issues relating to modeling and analysis across the government agencies. Discussions also occur online, and participants are informed of talks, conferences and other activities of interest to the group. IMAG recognized that the modeling community is on the forefront of thinking across the biological continuum, rather than just focusing at one scale or level of resolution. In addition IMAG identified a strong desire among modelers to form multi-disciplinary partnerships across varied research communities. Overall Intent of IMAG through the MSM Consortium is: * To develop new methodologies that span across biological scales * To develop multiscale methodologies applicable to biomedical, biological and behavioral research * To develop methodologies within the local multidisciplinary team and within the larger Framework environment * To further promote multiscale modeling through model sharing This wiki contains information relevant to the IMAG (Interagency Modeling and Analysis Group) and the MSM (Multi-scale Modeling Consortium).
Proper citation: Interagency Modeling and Analysis Group and Multi-scale Modeling Consortium Wiki (RRID:SCR_008046) Copy
http://www.fz-juelich.de/ime/spm_anatomy_toolbox
A MATLAB toolbox which uses three dimensional probabilistic cytoarchitechtonic maps to correlate microscopic, anatomic and functional data of the cerebral cortex. Correlating the activation foci identified in functional imaging studies of the human brain with structural (e.g., cytoarchitectonic) information on the activated areas is a major methodological challenge for neuroscience research. We here present a new approach to make use of three-dimensional probabilistic cytoarchitectonic maps, as obtained from the analysis of human post-mortem brains, for correlating microscopical, anatomical and functional imaging data of the cerebral cortex. We introduce a new, MATLAB based toolbox for the SPM2 software package which enables the integration of probabilistic cytoarchitectonic maps and results of functional imaging studies. The toolbox includes the functionality for the construction of summary maps combining probability of several cortical areas by finding the most probable assignment of each voxel to one of these areas. Its main feature is to provide several measures defining the degree of correspondence between architectonic areas and functional foci. The software, together with the presently available probability maps, is available as open source software to the neuroimaging community. This new toolbox provides an easy-to-use tool for the integrated analysis of functional and anatomical data in a common reference space.
Proper citation: SPM Anatomy Toolbox (RRID:SCR_013273) Copy
https://www.nature.com/articles/s41467-018-03367-w
Nanodroplet processing platform for deep and quantitative proteome profiling of 10 to 100 mammalian cells. It enhances efficiency and recovery of sample processing by downscaling processing volumes.
Proper citation: nanoPOTS (RRID:SCR_017129) Copy
http://www.bioconductor.org/packages/release/bioc/html/flowBin.html
A software package to combine flow cytometry data that has been multiplexed into multiple tubes with common markers between them. It establishes common bins across tubes in terms of the common markers, then determines expression within each tube for each bin in terms of the tube-specific markers.
Proper citation: flowBin (RRID:SCR_000051) Copy
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