Literature DB >> 16685836

Fast and simple calculus on tensors in the log-Euclidean framework.

Vincent Arsigny1, Pierre Fillard, Xavier Pennec, Nicholas Ayache.   

Abstract

Computations on tensors have become common with the use of DT-MRI. But the classical Euclidean framework has many defects, and affine-invariant Riemannian metrics have been proposed to correct them. These metrics have excellent theoretical properties but lead to complex and slow algorithms. To remedy this limitation, we propose new metrics called Log-Euclidean. They also have excellent theoretical properties and yield similar results in practice, but with much simpler and faster computations. Indeed, Log-Euclidean computations are Euclidean computations in the domain of matrix logarithms. Theoretical aspects are presented and experimental results for multilinear interpolation and regularization of tensor fields are shown on synthetic and real DTI data.

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Year:  2005        PMID: 16685836     DOI: 10.1007/11566465_15

Source DB:  PubMed          Journal:  Med Image Comput Comput Assist Interv


  31 in total

1.  Robust Tensor Splines for Approximation of Diffusion Tensor MRI Data.

Authors:  Angelos Barmpoutis; Baba C Vemuri; John R Forder
Journal:  Proc IEEE Comput Soc Conf Comput Vis Pattern Recognit       Date:  2006-06-17

2.  Gene network effects on brain microstructure and intellectual performance identified in 472 twins.

Authors:  Ming-Chang Chiang; Marina Barysheva; Katie L McMahon; Greig I de Zubicaray; Kori Johnson; Grant W Montgomery; Nicholas G Martin; Arthur W Toga; Margaret J Wright; Paul Shapshak; Paul M Thompson
Journal:  J Neurosci       Date:  2012-06-20       Impact factor: 6.167

3.  Tensor splines for interpolation and approximation of DT-MRI with applications to segmentation of isolated rat hippocampi.

Authors:  Angelos Barmpoutis; Baba C Vemuri; Timothy M Shepherd; John R Forder
Journal:  IEEE Trans Med Imaging       Date:  2007-11       Impact factor: 10.048

4.  Non-local means variants for denoising of diffusion-weighted and diffusion tensor MRI.

Authors:  Nicolas Wiest-Daesslé; Sylvain Prima; Pierrick Coupé; Sean Patrick Morrissey; Christian Barillot
Journal:  Med Image Comput Comput Assist Interv       Date:  2007

5.  Statistical group comparison of diffusion tensors via multivariate hypothesis testing.

Authors:  Brandon Whitcher; Jonathan J Wisco; Nouchine Hadjikhani; David S Tuch
Journal:  Magn Reson Med       Date:  2007-06       Impact factor: 4.668

6.  Brain fiber architecture, genetics, and intelligence: a high angular resolution diffusion imaging (HARDI) study.

Authors:  Ming-Chang Chiang; Marina Barysheva; Agatha D Lee; Sarah Madsen; Andrea D Klunder; Arthur W Toga; Katie L Mcmahon; Greig I de Zubicaray; Matthew Meredith; Margaret J Wright; Anuj Srivastava; Nikolay Balov; Paul M Thompson
Journal:  Med Image Comput Comput Assist Interv       Date:  2008

7.  Rician noise removal by non-Local Means filtering for low signal-to-noise ratio MRI: applications to DT-MRI.

Authors:  Nicolas Wiest-Daesslé; Sylvain Prima; Pierrick Coupé; Sean Patrick Morrissey; Christian Barillot
Journal:  Med Image Comput Comput Assist Interv       Date:  2008

8.  Fluid registration of diffusion tensor images using information theory.

Authors:  M C Chiang; A D Leow; A D Klunder; R A Dutton; M Barysheva; S E Rose; K L McMahon; G I de Zubicaray; A W Toga; P M Thompson
Journal:  IEEE Trans Med Imaging       Date:  2008-04       Impact factor: 10.048

9.  EXPONENTIAL TENSORS: A FRAMEWORK FOR EFFICIENT HIGHER-ORDER DT-MRI COMPUTATIONS.

Authors:  Angelos Barmpoutis; Baba C Vemuri
Journal:  Proc IEEE Int Symp Biomed Imaging       Date:  2007-05-15

10.  Using perturbation theory to compute the morphological similarity of diffusion tensors.

Authors:  R Bansal; L H Staib; D Xu; A F Laine; J Royal; B S Peterson
Journal:  IEEE Trans Med Imaging       Date:  2008-05       Impact factor: 10.048

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