Linked Life Data

12022624

Source:http://linkedlifedata.com/resource/pubmed/id/12022624

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
4
pubmed:dateCreated
2002-5-22
pubmed:abstractText
We present an explicit formula for B-spline convolution kernels; these are defined as the convolution of several B-splines of variable widths h(i) and degrees n(i). We apply our results to derive spline-convolution-based algorithms for two closely related problems: the computation of the Radon transform and of its inverse. First, we present an efficient discrete implementation of the Radon transform that is optimal in the least-squares sense. We then consider the reverse problem and introduce a new spline-convolution version of the filtered back-projection algorithm for tomographic reconstruction. In both cases, our explicit kernel formula allows for the use of high-degree splines; these offer better approximation performance than the conventional lower-degree formulations (e.g., piecewise constant or piecewise linear models). We present multiple experiments to validate our approach and to find the parameters that give the best tradeoff between image quality and computational complexity. In particular, we find that it can be computationally more efficient to increase the approximation degree than to increase the sampling rate.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Apr
pubmed:issn
0278-0062
pubmed:author
pubmed:issnType
Print
pubmed:volume
21
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
363-76
pubmed:dateRevised
2007-11-15
pubmed:meshHeading
pubmed:year
2002
pubmed:articleTitle
Discretization of the radon transform and of its inverse by spline convolutions.
pubmed:affiliation
Biomedical Imaging Group, IOA, STI, Swiss Federal Institute of Technology Lausanne, EPFL. horbelt@ieee.org
pubmed:publicationType
Journal Article, Comparative Study