Linked Life Data

7700191

Source:http://linkedlifedata.com/resource/pubmed/id/7700191

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
12
pubmed:dateCreated
1995-5-1
pubmed:abstractText
This paper describes a method to perform reconstruction of vascular cross-sectional images from a limited number of x-ray angiographic cone-beam projections. It is assumed that the projection data can be simplified by identifying blood vessels in each angiogram and removing signals due to other structures. Under these conditions, the x-ray attenuation coefficient, mu, can be modeled as a binary variable having a value mu 0 within the vessel and "0" outside. The reconstruction is performed by minimizing a cost function using the method of simulated annealing. In this paper, we demonstrate that the introduction of a priori information allows one to reconstruct a sphere and a simulated branched vessel from three views with, respectively, 97% and 93% of voxels having correct values. The addition of a continuity constraint for the reconstruction of the branched vessel resulted in further reduction in the percentage of misplaced voxels. Calculations require from one to six hours of CPU time on a Sun SparcStation 2 computer for the cases investigated here. The effect of noise, "cooling" schedule, and number of views on the reconstruction are examined using simulated vessel projections. Modifications to our approach to accelerate the reconstruction are also discussed.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Dec
pubmed:issn
0094-2405
pubmed:author
pubmed:issnType
Print
pubmed:volume
21
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
1839-51
pubmed:dateRevised
2008-11-21
pubmed:meshHeading
pubmed:year
1994
pubmed:articleTitle
Binary vascular reconstruction from a limited number of cone beam projections.
pubmed:affiliation
Department of Medical Biophysics, Sunnybrook Health Science Centre, University of Toronto, Ontario, Canada.
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't