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Statistical iterative reconstruction algorithm for X-ray phase-contrast CT.

Hahn, Dieter; Thibault, Pierre; Fehringer, Andreas; Bech, Martin LU ; Koehler, Thomas; Pfeiffer, Franz and Noël, Peter B (2015) In Scientific Reports 5.
Abstract
Grating-based phase-contrast computed tomography (PCCT) is a promising imaging tool on the horizon for pre-clinical and clinical applications. Until now PCCT has been plagued by strong artifacts when dense materials like bones are present. In this paper, we present a new statistical iterative reconstruction algorithm which overcomes this limitation. It makes use of the fact that an X-ray interferometer provides a conventional absorption as well as a dark-field signal in addition to the phase-contrast signal. The method is based on a statistical iterative reconstruction algorithm utilizing maximum-a-posteriori principles and integrating the statistical properties of the raw data as well as information of dense objects gained from the... (More)
Grating-based phase-contrast computed tomography (PCCT) is a promising imaging tool on the horizon for pre-clinical and clinical applications. Until now PCCT has been plagued by strong artifacts when dense materials like bones are present. In this paper, we present a new statistical iterative reconstruction algorithm which overcomes this limitation. It makes use of the fact that an X-ray interferometer provides a conventional absorption as well as a dark-field signal in addition to the phase-contrast signal. The method is based on a statistical iterative reconstruction algorithm utilizing maximum-a-posteriori principles and integrating the statistical properties of the raw data as well as information of dense objects gained from the absorption signal. Reconstruction of a pre-clinical mouse scan illustrates that artifacts caused by bones are significantly reduced and image quality is improved when employing our approach. Especially small structures, which are usually lost because of streaks, are recovered in our results. In comparison with the current state-of-the-art algorithms our approach provides significantly improved image quality with respect to quantitative and qualitative results. In summary, we expect that our new statistical iterative reconstruction method to increase the general usability of PCCT imaging for medical diagnosis apart from applications focused solely on soft tissue visualization. (Less)
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organization
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type
Contribution to journal
publication status
published
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in
Scientific Reports
volume
5
publisher
Nature Publishing Group
external identifiers
  • pmid:26067714
  • wos:000356148800001
  • scopus:84931271582
ISSN
2045-2322
DOI
10.1038/srep10452
language
English
LU publication?
yes
id
e1848222-0980-4321-8f35-5d113af4da96 (old id 7486757)
alternative location
http://www.ncbi.nlm.nih.gov/pubmed/26067714?dopt=Abstract
date added to LUP
2015-07-08 11:50:43
date last changed
2017-10-01 04:01:39
@article{e1848222-0980-4321-8f35-5d113af4da96,
  abstract     = {Grating-based phase-contrast computed tomography (PCCT) is a promising imaging tool on the horizon for pre-clinical and clinical applications. Until now PCCT has been plagued by strong artifacts when dense materials like bones are present. In this paper, we present a new statistical iterative reconstruction algorithm which overcomes this limitation. It makes use of the fact that an X-ray interferometer provides a conventional absorption as well as a dark-field signal in addition to the phase-contrast signal. The method is based on a statistical iterative reconstruction algorithm utilizing maximum-a-posteriori principles and integrating the statistical properties of the raw data as well as information of dense objects gained from the absorption signal. Reconstruction of a pre-clinical mouse scan illustrates that artifacts caused by bones are significantly reduced and image quality is improved when employing our approach. Especially small structures, which are usually lost because of streaks, are recovered in our results. In comparison with the current state-of-the-art algorithms our approach provides significantly improved image quality with respect to quantitative and qualitative results. In summary, we expect that our new statistical iterative reconstruction method to increase the general usability of PCCT imaging for medical diagnosis apart from applications focused solely on soft tissue visualization.},
  articleno    = {10452},
  author       = {Hahn, Dieter and Thibault, Pierre and Fehringer, Andreas and Bech, Martin and Koehler, Thomas and Pfeiffer, Franz and Noël, Peter B},
  issn         = {2045-2322},
  language     = {eng},
  publisher    = {Nature Publishing Group},
  series       = {Scientific Reports},
  title        = {Statistical iterative reconstruction algorithm for X-ray phase-contrast CT.},
  url          = {http://dx.doi.org/10.1038/srep10452},
  volume       = {5},
  year         = {2015},
}