Digital Imaging and COmmunications in Medicine
How to cite this record FAIRsharing.org: DICOM; Digital Imaging and COmmunications in Medicine; DOI: https://doi.org/10.25504/FAIRsharing.b7z8by; Last edited: Jan. 8, 2019, 1:40 p.m.; Last accessed: Oct 22 2019 9:34 a.m.
Record updated: June 21, 2017, 2:01 p.m. by The FAIRsharing Team.
Edits to 'https://fairsharing.org/FAIRsharing.b7z8by' by 'The FAIRsharing Team' at 14:53, 23 Sep 2016 (approved): 'contactName' has been modified: Before: Dicom Nema After: DICOM Help Added: Removed:
Edits to 'https://fairsharing.org/FAIRsharing.b7z8by' by 'The FAIRsharing Team' at 19:19, 04 Sep 2016 (approved): 'contactName' has been modified: Before: DICOM NEMA After: Dicom Nema Support links have changed: Previous values: http://dicom.nema.org/dicom/faqs.html email@example.com http://dicom.nema.org/handbook.html comp.protocols.dicom[at]googlegroups.com http://dicom.nema.org/standard.html http://dicom.nema.org/dicom/geninfo/Brochure.pdf New values: http://dicom.nema.org/dicom/faqs.html firstname.lastname@example.org http://dicom.nema.org/handbook.html email@example.com http://dicom.nema.org/standard.html http://dicom.nema.org/dicom/geninfo/Brochure.pdf http://dicom.nema.org/standard.html Added: Removed:
|online documentation||http://dicom.nema.org/dicom/geninfo/Broc ...|
No XSD schemas defined
Conditions of Use
Multi-series DICOM: an extension of DICOM that stores a whole study in a single object.
Ismail M,Philbin J
J Digit Imaging 2013
Models and Formats
No syntax standards defined
No identifier schema standards defined
No metrics standards defined
National Database for Autism Research (NDAR) is an extensible, scalable informatics platform for austism spectrum disorder-relevant data at all levels of biological and behavioral organization (molecules, genes, neural tissue, behavioral, social and environmental interactions) and for all data types (text, numeric, image, time series, etc.). NDAR was developed to share data across the entire ASD field and to facilitate collaboration across laboratories, as well as interconnectivity with other informatics platforms.
The Cancer Imaging Archive
The Cancer Imaging Archive (TCIA) is a large archive of medical images of cancer accessible for public download. All images are stored in DICOM file format. The images are organized as "Collections", typically patients related by a common disease (e.g. lung cancer), image modality (MRI, CT, etc) or research focus.
SICAS medical image repository
The Sicas Medical Image Repository is a centralized storage system where the data such as Images, Segmentations, SSM can be used to build and shared statistical shape models. Dicom, ITK based images and statistical models in the statismo format can be stored on SMIR.
The CancerData site is an effort of the Medical Informatics and Knowledge Engineering team (MIKE for short) of Maastro Clinic, Maastricht, The Netherlands. It offers a central, online repository for the sustained storage of clinical protocols, publications and research datasets. The data that are offered can vary from documents, spreadsheets to (bio-)medical images and treatment simulations. CancerData is a registered member of DataCite, which is an international consortium and member of the International DOI Foundation. Via DataCite, we have the ability to offer persistent identifiers to the datasets via the registration of Digital Object Identifiers (DOI).
Curie Image Database
In addition to data used in on-going collaborations, this database host images from France Bio Imaging microscopy facility with public access either associated to publications, either that make interest from an image processing point of view (such as challenges for developpers or for use in metrology). This resource requires a log in account, however some projects are available with a guest account.
Structual and functional MRI data
MRI data for brain and mind research incl. simultaneous recording of EEG and electrophysiology. This resource has restricted access.
Brain Imaging Network Data Repository
We are a leading national institution in brain MR imaging and molecular imaging (given cyclotron and radiopharmacy facilities). These pillars create the core medical imaging equipment infrastructure in Portugal with relevant scientific productivity now expanding to all levels of multimodal imaging. We have unique expertise and equipment for development of imaging markers and studies in brain imaging and respective repositories. This resource has restricted access. Please use the contact details provided to request access.
Blackfynn Discover is a public resource for accessing large public Neuroscience datasets. Blackfynn Discover was developed through grants from the NIH NIDA, NIH CommonFund, DARPA, and others to provide a sustainable solution for fostering collaboration in the Neurosciences.
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