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Sparse sampling in helical cone-beam CT perfect reconstruction algorithms

Sparse sampling in helical cone-beam CT perfect reconstruction algorithms In the current paper we consider the Helical Cone Beam CT. This scanning method exposes the patient to large quantities of radiation and results in very large amounts of data being collected and stored. Both these facts are prime motivators for the development of an efficient, reduced rate, sampling pattern. We calculate bounds on the support in the frequency domain of the collected data and use these to suggest an efficient sampling pattern. A reduction of up to a factor of 2 in sampling rate is suggested. Indeed, we show that reconstruction quality is not affected by this reduction of sampling rates. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of X-Ray Science and Technology IOS Press

Sparse sampling in helical cone-beam CT perfect reconstruction algorithms

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Publisher
IOS Press
Copyright
Copyright © 2016 IOS Press and the authors. All rights reserved
ISSN
0895-3996
eISSN
1095-9114
DOI
10.3233/XST-160553
pmid
27257877
Publisher site
See Article on Publisher Site

Abstract

In the current paper we consider the Helical Cone Beam CT. This scanning method exposes the patient to large quantities of radiation and results in very large amounts of data being collected and stored. Both these facts are prime motivators for the development of an efficient, reduced rate, sampling pattern. We calculate bounds on the support in the frequency domain of the collected data and use these to suggest an efficient sampling pattern. A reduction of up to a factor of 2 in sampling rate is suggested. Indeed, we show that reconstruction quality is not affected by this reduction of sampling rates.

Journal

Journal of X-Ray Science and TechnologyIOS Press

Published: Jan 1, 2016

References