standards > model/format > DOI:10.25504/FAIRsharing.jgzts3


ready NIfTI-1 Data Format

Abbreviation: NIFTI


General Information
The Neuroimaging Informatics Technology Initiative (nifti) file format was envisioned about a decade ago as a replacement to the then widespread, yet problematic, analyze 7.5 file format. The main problem with the previous format was perhaps the lack of adequate information about orientation in space, such that the stored data could not be unambiguously interpreted. Although the file was used by many imaging software projects, the lack of adequate information on orientation obliged some, most notably spm, to include, for every analyzed file, an accompanying file describing the orientation, such as a file with extension .mat.

Homepage http://nifti.nimh.nih.gov/nifti-1

Countries that developed this resource United States

Created in 2004

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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: Nov 27 2020 11 a.m.


Record updated: Feb. 26, 2020, 4:29 p.m. by The FAIRsharing Team.

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Related Databases (5)
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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
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Blackfynn Discover
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.

National Institute of Mental Health Data Archive
The National Institute of Mental Health Data Archive (NDA), originally established to support autism research, is an informatics platform and data repository that facilitates data sharing across all of mental health and other research communities, combining data from each of these repositories into a single resource with a single process for gaining access to all shared data. While querying and browsing data is publicly available, all subject-level data is available behind a login.

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