NIfTI-1 Data Format
How to cite this record FAIRsharing.org: NIFTI; NIfTI-1 Data Format; DOI: https://doi.org/10.25504/FAIRsharing.jgzts3; Last edited: Feb. 27, 2020, 11:32 a.m.; Last accessed: Aug 15 2020 6:02 a.m.
Record updated: Feb. 26, 2020, 4:29 p.m. by The FAIRsharing Team.
Edits to 'https://fairsharing.org/FAIRsharing.jgzts3' by 'The FAIRsharing Team' at 16:29, 26 Feb 2020 (approved): 'onto_disciplines' has been modified: Before: Life Science Neurobiology After: Life Science Neurobiology Ontology and Terminology Added: Ontology and Terminology Removed: 'miriam_id' has been modified: Before: None After: 'contactORCID' has been modified: Before: After: 0000-0001-6043-0166
No XSD schemas defined
Conditions of Use
No publications available
No semantic standards defined
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.
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.
Human Connectome Project
The HCP is mapping the human connectome as accurately as possible in a large number of normal adults and is making this data freely available to the scientific community using a powerful, user-friendly informatics platform.
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.
This record is not implemented by any policy.
This record is in need of a maintainer. If you login, you'll be able to claim this record.
U.S. National Library of Medicine (Government body)