Publication
Title
Super-resolution for computed tomography based on discrete tomography
Author
Abstract
In computed tomography (CT), partial volume effects impede accurate segmentation of structures that are small with respect to the pixel size. In this paper, it is shown that for objects consisting of a small number of homogeneous materials, the reconstruction resolution can be substantially increased without altering the acquisition process. A super-resolution reconstruction approach is introduced that is based on discrete tomography, in which prior knowledge about the materials in the object is assumed. Discrete tomography has already been used to create reconstructions from a low number of projection angles, but in this paper, it is demonstrated that it can also be applied to increase the reconstruction resolution. Experiments on simulated and real mu CT data of bone and foam structures show that the proposed method indeed leads to significantly improved structure segmentation and quantification compared with what can be achieved from conventional reconstructions.
Language
English
Source (journal)
IEEE transactions on image processing. - New York, N.Y.
Publication
New York, N.Y. : 2014
ISSN
1057-7149
Volume/pages
23:3(2014), p. 1181-1193
ISI
000331551100004
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 01.11.2017
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