A multi-resolution framework for diffusion tensor images

Luc Florack; Laura Astola

doi:10.1109/CVPRW.2008.4562966

A multi-resolution framework for diffusion tensor images

Luc Florack, Laura Astola

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

14 Citations (Scopus)

5 Downloads (Pure)

Abstract

A new scale space paradigm is proposed for multi-resolution analysis of diffusion tensor images (DTI). An a priori consistency requirement is stipulated, which precludes a linear model. A nonlinear adaptation is proposed to remedy the problem. Subsequently it is shown how differentiation can be operationalized. Considerations in this paper are relevant for DTI analysis in a differential geometric framework, in which the DTI image imposes a Riemannian structure. It adds further support in favor of the ldquogeometric rationalerdquo, and opens the door for a multi-resolution approach towards fibre tracking, connectivity analysis, and so forth.

Original language	English
Title of host publication	2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPR Workshops 2008, Anchorage AK, USA, June 23-28, 2008)
Place of Publication	Piscataway NJ
Publisher	Institute of Electrical and Electronics Engineers
Pages	1-7
Number of pages	7
ISBN (Print)	978-1-4244-2339-2
DOIs	https://doi.org/10.1109/CVPRW.2008.4562966
Publication status	Published - 2008

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10.1109/CVPRW.2008.4562966

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title = "A multi-resolution framework for diffusion tensor images",

abstract = "A new scale space paradigm is proposed for multi-resolution analysis of diffusion tensor images (DTI). An a priori consistency requirement is stipulated, which precludes a linear model. A nonlinear adaptation is proposed to remedy the problem. Subsequently it is shown how differentiation can be operationalized. Considerations in this paper are relevant for DTI analysis in a differential geometric framework, in which the DTI image imposes a Riemannian structure. It adds further support in favor of the ldquogeometric rationalerdquo, and opens the door for a multi-resolution approach towards fibre tracking, connectivity analysis, and so forth.",

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A multi-resolution framework for diffusion tensor images. / Florack, Luc; Astola, Laura.
2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPR Workshops 2008, Anchorage AK, USA, June 23-28, 2008). Piscataway NJ: Institute of Electrical and Electronics Engineers, 2008. p. 1-7.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

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AU - Astola, Laura

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AB - A new scale space paradigm is proposed for multi-resolution analysis of diffusion tensor images (DTI). An a priori consistency requirement is stipulated, which precludes a linear model. A nonlinear adaptation is proposed to remedy the problem. Subsequently it is shown how differentiation can be operationalized. Considerations in this paper are relevant for DTI analysis in a differential geometric framework, in which the DTI image imposes a Riemannian structure. It adds further support in favor of the ldquogeometric rationalerdquo, and opens the door for a multi-resolution approach towards fibre tracking, connectivity analysis, and so forth.

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DO - 10.1109/CVPRW.2008.4562966

M3 - Conference contribution

SN - 978-1-4244-2339-2

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BT - 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPR Workshops 2008, Anchorage AK, USA, June 23-28, 2008)

PB - Institute of Electrical and Electronics Engineers

CY - Piscataway NJ

ER -

A multi-resolution framework for diffusion tensor images

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