Paper Info
Title
ODF maxima extraction in spherical harmonic representation via analytical search space reduction.
Abstract
By revealing complex fiber structure through the orientation distribution function (ODF), q-ball imaging has recently become a popular reconstruction technique in diffusion-weighted MRI. In this paper, we propose an analytical dimension reduction approach to ODF maxima extraction. We show that by expressing the ODF, or any antipodally symmetric spherical function, in the common fourth order real and symmetric spherical harmonic basis, the maxima of the two-dimensional ODF lie on an analytically derived one-dimensional space, from which we can detect the ODF maxima. This method reduces the computational complexity of the maxima detection, without compromising the accuracy. We demonstrate the performance of our technique on both artificial and human brain data.
Year
DOI
Venue
2010
10.1007/978-3-642-15745-5_11
MICCAI (2)
Keywords
Field
DocType
analytical dimension reduction approach,maxima extraction,analytical search space reduction,spherical harmonic representation,complex fiber structure,antipodally symmetric spherical function,symmetric spherical harmonic basis,orientation distribution function,odf maxima extraction,odf maximum,two-dimensional odf lie,maxima detection,popular reconstruction technique,spherical function,spherical harmonics,reduction,dimension reduction,fibers,search space,spherical harmonic,computational complexity,extraction,diffusion,analytic functions,distribution
Computer vision,Dimensionality reduction,Fourth order,Analytic function,Spherical harmonics,Zonal spherical function,Artificial intelligence,Maxima,Distribution function,Mathematics,Computational complexity theory
Conference
Volume
Issue
ISSN
13
Pt 2
0302-9743
ISBN
Citations 
PageRank 
3-642-15744-0
9
0.62
References 
Authors
5
3
Name
Order
Citations
PageRank
Iman Aganj119518.93
Christophe Lenglet288056.06
Guillermo Sapiro3148131051.92