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Similar Tensor Arrays - A Framework for Storage of Tensor Array Data
Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology. Linköping University, Center for Medical Image Science and Visualization (CMIV). Centre for Image Analysis, SLU, Uppsala, Sweden.
Universidad de Valladolid Laboratorio de Procesado de Imagen (LPI), Dept. Teoría de la Señal y Comunicaciones e Ingeniería Telemática Spain.
Boğaziçi University 5 Electrical & Electronics Engineering Department Istanbul Turkey.
Universidad de Valladolid Laboratorio de Procesado de Imagen (LPI), Dept. Teoría de la Señal y Comunicaciones e Ingeniería Telemática Spain.
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2009 (English)In: Tensors in Image Processing and Computer Vision / [ed] Santiago Aja-Fern´andez, Rodrigo de Luis Garc´ıa, Dacheng Tao, Xuelong Li, Springer Science+Business Media B.V., 2009, 1, 407-428 p.Chapter in book (Refereed)
Abstract [en]

This chapter describes a framework for storage of tensor array data, useful to describe regularly sampled tensor fields. The main component of the framework, called Similar Tensor Array Core (STAC), is the result of a collaboration between research groups within the SIMILAR network of excellence. It aims to capture the essence of regularly sampled tensor fields using a minimal set of attributes and can therefore be used as a “greatest common divisor” and interface between tensor array processing algorithms. This is potentially useful in applied fields like medical image analysis, in particular in Diffusion Tensor MRI, where misinterpretation of tensor array data is a common source of errors. By promoting a strictly geometric perspective on tensor arrays, with a close resemblance to the terminology used in differential geometry, (STAC) removes ambiguities and guides the user to define all necessary information. In contrast to existing tensor array file formats, it is minimalistic and based on an intrinsic and geometric interpretation of the array itself, without references to other coordinate systems.

Place, publisher, year, edition, pages
Springer Science+Business Media B.V., 2009, 1. 407-428 p.
Series
Advances in Pattern Recognition, ISSN 1617-7916
National Category
Computer Vision and Robotics (Autonomous Systems)
Identifiers
URN: urn:nbn:se:liu:diva-58091DOI: 10.1007/978-1-84882-299-3_19ISBN: 978-1-84882-298-6 (print)ISBN: 978-1-84882-299-3 (print)OAI: oai:DiVA.org:liu-58091DiVA: diva2:331961
Conference
Tensor in Image Processing and Computer Vision
Available from: 2010-07-29 Created: 2010-07-29 Last updated: 2015-08-19Bibliographically approved

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Publisher's full textfind book at a swedish library/hitta boken i ett svenskt bibliotek

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Brun, AndersSigfridsson, AndreasSvensson, BjörnHerberthson, MagnusKnutsson, Hans

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