Publication
Title
Fast tomographic reconstruction from limited data using artificial neural networks
Author
Abstract
Image reconstruction from a small number of projections is a challenging problem in tomography. Advanced algorithms that incorporate prior knowledge can sometimes produce accurate reconstructions, but they typically require long computation times. Furthermore, the required prior knowledge can be very specific, limiting the type of images that can be reconstructed. Here, we present a reconstruction method that automatically learns prior knowledge using an artificial neural network. We show that this method can be viewed as a combination of filtered backprojection steps, and, therefore, has a relatively low computational cost. Results for two different cases show that the new method is able to use the learned information to produce high quality reconstructions in a short time, even when presented with a small number of projections.
Language
English
Source (journal)
IEEE transactions on image processing. - New York, N.Y.
Publication
New York, N.Y. : 2013
ISSN
1057-7149
Volume/pages
22:12(2013), p. 5238-5251
ISI
000331203200006
Full text (Publisher's DOI)
UAntwerpen
Faculty/Department
Research group
Publication type
Subject
Affiliation
Publications with a UAntwerp address
External links
Web of Science
Record
Identification
Creation 04.04.2014
Last edited 06.10.2017
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