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Found 38 result(s)
Content type(s)
NCI Imaging Data Commons (IDC) is a cloud-based repository of publicly available cancer imaging data co-located with the analysis and exploration tools and resources. IDC is a node within the broader NCI Cancer Research Data Commons (CRDC) infrastructure that provides secure access to a large, comprehensive, and expanding collection of cancer research data.
XNAT CENTRAL is a publicly accessible datasharing portal at Washinton University Medical School using XNAT software. XNAT provides neuroimaging data through a web interface and a customizable open source platform. XNAT facilitates data uploads and downloads for data sharing, processing and organization. NOTICE: Central XNAT will be decommissioned on October 15, 2023. New project creation is no longer permitted.
Content type(s)
Morphbank :: Biological Imaging is a continuously growing database of images that scientists use for international collaboration, research and education. Images deposited in Morphbank :: Biological Imaging document a wide variety of research including: specimen-based research in comparative anatomy, morphological phylogenetics, taxonomy and related fields focused on increasing our knowledge about biodiversity.
The Central Neuroimaging Data Archive (CNDA) allows for sharing of complex imaging data to investigators around the world, through a simple web portal. The CNDA is an imaging informatics platform that provides secure data management services for Washington University investigators, including source DICOM imaging data sharing to external investigators through a web portal, cnda.wustl.edu. The CNDA’s services include automated archiving of imaging studies from all of the University’s research scanners, automated quality control and image processing routines, and secure web-based access to acquired and post-processed data for data sharing, in compliance with NIH data sharing guidelines. The CNDA is currently accepting datasets only from Washington University affiliated investigators. Through this platform, the data is available for broad sharing with researchers both internal and external to Washington University.. The CNDA overlaps with data in oasis-brains.org https://www.re3data.org/repository/r3d100012182, but CNDA is a larger data set.
MIDRC aims to develop a high-quality repository for medical images related to COVID-19 and associated clinical data, and develop and foster medical image-based artificial intelligence (AI) for use in the detection, diagnosis, prognosis, and monitoring of COVID-19.
OASIS-3 is the latest release in the Open Access Series of Imaging Studies (OASIS) that aimed at making neuroimaging datasets freely available to the scientific community. By compiling and freely distributing this multi-modal dataset, we hope to facilitate future discoveries in basic and clinical neuroscience. Previously released data for OASIS-Cross-sectional (Marcus et al, 2007) and OASIS-Longitudinal (Marcus et al, 2010) have been utilized for hypothesis driven data analyses, development of neuroanatomical atlases, and development of segmentation algorithms. OASIS-3 is a longitudinal neuroimaging, clinical, cognitive, and biomarker dataset for normal aging and Alzheimer’s Disease. The OASIS datasets hosted by central.xnat.org provide the community with open access to a significant database of neuroimaging and processed imaging data across a broad demographic, cognitive, and genetic spectrum an easily accessible platform for use in neuroimaging, clinical, and cognitive research on normal aging and cognitive decline. All data is available via www.oasis-brains.org.
The NIH 3D Print Exchange (the “Exchange”) is an open, comprehensive, and interactive website for searching, browsing, downloading, and sharing biomedical 3D print files, modeling tutorials, and educational material. "Biomedical" includes models of cells, bacteria, or viruses, molecules like proteins or DNA, and anatomical models of organs, tissue, and body parts. The NIH 3D Print Exchange provides models in formats that are readily compatible with 3D printers, and offers a unique set of tools to create and share 3D-printable models related to biomedical science.
A place where researchers can publicly store and share unthresholded statistical maps, parcellations, and atlases produced by MRI and PET studies.
TheCellVision.org is a freely available and web-accessible image visualization and data browsing tool that serves as a central repository for fluorescence microscopy images and associated quantitative data produced by high-content screening experiments. Currently, TheCellVision.org hosts images and associated analysis results from two published high- content screening (HCS) projects focused on the budding yeast Saccharomyces cerevisiae. TheCellVision.org allows users to access, visualize and explore fluorescence microscopy images, and to search, compare, and extract data related to subcellular compartment morphology, protein abundance, and localization. Each dataset can be queried independently or as part of a search across multiple datasets using the advanced search option. The website also hosts computational tools associated with the available datasets, which can be applied to other projects and cell systems, a feature we demonstrate using published images of mammalian cells. Providing access to HCS data through websites such as TheCellVision.org enables new discovery and independent re-analyses of imaging data."
Country
DUGiDocs is the institutional repository of the Universitat de Girona. Its aim is to preserve, spread and make visible the intellectual production issued from research and teaching lead at the UdG, such as degree final reports, master reports and doctorate research reports by university students as well as articles in scientific periodicals. Moreover it includes indexing and content description tools, makes visualization from many other internet sites easier (interoperability) and it also includes open access.
Brain Image Library (BIL) is an NIH-funded public resource serving the neuroscience community by providing a persistent centralized repository for brain microscopy data. Data scope of the BIL archive includes whole brain microscopy image datasets and their accompanying secondary data such as neuron morphologies, targeted microscope-enabled experiments including connectivity between cells and spatial transcriptomics, and other historical collections of value to the community. The BIL Analysis Ecosystem provides an integrated computational and visualization system to explore, visualize, and access BIL data without having to download it.
All ADNI data are shared without embargo through the LONI Image and Data Archive (IDA), a secure research data repository. Interested scientists may obtain access to ADNI imaging, clinical, genomic, and biomarker data for the purposes of scientific investigation, teaching, or planning clinical research studies. "The Alzheimer’s Disease Neuroimaging Initiative (ADNI) unites researchers with study data as they work to define the progression of Alzheimer’s disease (AD). ADNI researchers collect, validate and utilize data, including MRI and PET images, genetics, cognitive tests, CSF and blood biomarkers as predictors of the disease. Study resources and data from the North American ADNI study are available through this website, including Alzheimer’s disease patients, mild cognitive impairment subjects, and elderly controls. "
The OpenNeuro project (formerly known as the OpenfMRI project) was established in 2010 to provide a resource for researchers interested in making their neuroimaging data openly available to the research community. It is managed by Russ Poldrack and Chris Gorgolewski of the Center for Reproducible Neuroscience at Stanford University. The project has been developed with funding from the National Science Foundation, National Institute of Drug Abuse, and the Laura and John Arnold Foundation.
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MyTardis began at Monash University to solve the problem of users needing to store large datasets and share them with collaborators online. Its particular focus is on integration with scientific instruments, instrument facilities and research lab file storage. Our belief is that the less effort a researcher has to expend safely storing data, the more likely they are to do so. This approach has flourished with MyTardis capturing data from areas such as protein crystallography, electron microscopy, medical imaging and proteomics and with deployments at Australian institutions such as University of Queensland, RMIT, University of Sydney and the Australian Synchrotron. Data access via https://www.massive.org.au/ and https://store.erc.monash.edu.au/experiment/view/104/ and see 'remarks'.
<<<!!!<<< The NCI CBIIT instance of the NBIA application was retired in March 2022. All data in the application has been transferred to The Cancer Image Archive https://www.re3data.org/repository/r3d100011559 and is available via the Access the Data > Search Radiology Portal menu item. The NBIA software is now maintained on GitHub, and can be built and deployed with the latest improvements and fixes that have been completed for TCIA. >>>!!!>>>
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A web-based Interface for searching and accessing a vast treasure trove of Australian geoscientific data, information, imagery, services and applications. Its main purpose is to provide access to datasets produced by Australia's geoscience research community.
PSI Open Data Provider allows users to consult open data related to experiments carried out at PSI. Data made available includes scientific datasets collected during experiments and publications if any. Users can search for data based on related metadata (both their own data and other people's public data).
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An Open Science resource that promotes scientific research and discovery in neurological diseases and accelerates the development of new treatments. It includes a growing collection of biospecimens, longitudinal clinical and neuropsychiatric information, imaging and genetic data from patients with neurological disease as well as healthy controls.
Content type(s)
Scicat allows users to access the metadata of raw and derived data which is taken at experiment facilities. Scientific datasets are linked to proposals and samples. Scientific datasets are can be linked to publications (DOI, PID). SciCat helps keeping track of data provenance (i.e. the steps leading to the final results). Scicat allows users to find data based on the metadata (both your own data and other peoples’ public data). In the long term, SciCat will help to automate scientific analysis workflows.
INDI was formed as a next generation FCP effort. INDI aims to provide a model for the broader imaging community while simultaneously creating a public dataset capable of dwarfing those that most groups could obtain individually.
CERIC Data Portal allows users to consult and manage data related to experiments carried out at CERIC (Central European Research Infrastructure Consortium) partner facilities. Data made available includes scientific datasets collected during experiments, experiment proposals, samples used and publications if any. Users can search for data based on related metadata (both their own data and other peoples' public data).
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The Astronomical Data Archives Center (ADAC) provides access to astronomical data from all over the world with links to online data catalogs, journal archives, imaging services and data archives. Users can access the VizieR catalogue service as well as the Hubble Ultra Deep Field Data by requesting password access. ADAC also provides access to the SMOKA public science data obtained through the Subaru Telescope in Hawaii as well as Schmidt Telescope at the University of Tokyo & MITSuME and KANATA Telescope at Higashi-Hiroshima Observatory. Users may need to contact the ADAC for password access or create user accounts for the various data services accessible through the ADAC site.
The Dallas Heart Study (DHS) is a multi-ethnic, population-based probability sample of Dallas County designed to define the social and the biological variables contributingto ethnic differences in cardiovascular health at the community level and to support hypothesis-driven research aimed at determining the underlying mechanisms contributing to differences in cardiovascular risk. The initial data collection from the population was performed in three sequential stages over a two year period(2000-2002) and included the collection of detailed socioeconomic, biomarker and imaging data from each participant. The underlying assumption of the study is that successful identification of new risk factors for cardiovascular disease will require the availability of an exquisitely phenotyped, multiethnic population in close proximity to the Center.