MINC 2.0: a flexible format for multi-modal images

Frontiers in Neuroinformatics

David MacDonald¹  Alex P. Zijdenbos²  Peter Neelin³  Robert D. Vincent⁴  Reza Adalat⁴  D. Louis Collins⁴  Steven M. Robbins⁴  Najmeh Khalili-Mahani⁴  Vladimir S. Fonov⁴  Alan Charles Evans⁴  Leila Baghdadi⁵  Andrew Lindsay Janke⁶  Jason Lerch⁷  John G. Sled⁷ 

[1] Autodesk, Inc.;Biospective, Inc.;Intelerad Medical Systems;McGill University;The Hospital for Sick Children;The University of Queensland;University of Toronto;

关键词: Neuroimaging;    data management;    metadata;    provenance;    HDF5;    data format;   

DOI  :  10.3389/fninf.2016.00035

来源: DOAJ

【 摘 要 】

It is often useful that an imaging data format can afford rich metadata, be flexible, scale to very large file sizes, support multi-modal data, and have strong inbuilt mechanisms for data provenance. Beginning in 1992, MINC was developed as a system for flexible, self-documenting representation of neuroscientific imaging data with arbitrary orientation and dimensionality. The MINC system incorporates three broad components: a file format specification, a programming library, and a growing set of tools.In the early 2000's the MINC developers created MINC 2.0, which added support for 64-bit file sizes, internal compression, and a number of other modern features. Because of its extensible design, it has been easy to incorporate details of provenance in the header metadata, including an explicit processing history, unique identifiers, and vendor-specific scanner settings. This makes MINC ideal for use in large scale imaging studies and databases. It also makes it easy to adapt to new scanning sequences and modalities.

【 授权许可】

Unknown