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MINC 2.0: A Flexible Format for Multi-Modal Images.
Vincent, Robert D; Neelin, Peter; Khalili-Mahani, Najmeh; Janke, Andrew L; Fonov, Vladimir S; Robbins, Steven M; Baghdadi, Leila; Lerch, Jason; Sled, John G; Adalat, Reza; MacDonald, David; Zijdenbos, Alex P; Collins, D Louis; Evans, Alan C.
Afiliación
  • Vincent RD; McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University Montreal, QC, Canada.
  • Neelin P; Intelerad Medical Systems Montreal, QC, Canada.
  • Khalili-Mahani N; McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University Montreal, QC, Canada.
  • Janke AL; Center for Advanced Imaging, The University of Queensland Brisbane, QLD, Australia.
  • Fonov VS; McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University Montreal, QC, Canada.
  • Robbins SM; McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University Montreal, QC, Canada.
  • Baghdadi L; Mouse Imaging Centre, The Hospital for Sick Children Toronto, ON, Canada.
  • Lerch J; Mouse Imaging Centre, The Hospital for Sick ChildrenToronto, ON, Canada; Department of Medical Biophysics, University of TorontoToronto, ON, Canada.
  • Sled JG; Mouse Imaging Centre, The Hospital for Sick ChildrenToronto, ON, Canada; Department of Medical Biophysics, University of TorontoToronto, ON, Canada.
  • Adalat R; McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University Montreal, QC, Canada.
  • MacDonald D; Autodesk Inc. Montreal, QC, Canada.
  • Zijdenbos AP; Biospective Inc. Montreal, QC, Canada.
  • Collins DL; McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill UniversityMontreal, QC, Canada; Department of Biomedical Engineering, McGill UniversityMontreal, QC, Canada.
  • Evans AC; McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University Montreal, QC, Canada.
Front Neuroinform ; 10: 35, 2016.
Article en En | MEDLINE | ID: mdl-27563289
ABSTRACT
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.
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Texto completo: 1 Bases de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Front Neuroinform Año: 2016 Tipo del documento: Article País de afiliación: Canadá

Texto completo: 1 Bases de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Front Neuroinform Año: 2016 Tipo del documento: Article País de afiliación: Canadá