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)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/7486757
- author
- Hahn, Dieter
; Thibault, Pierre
; Fehringer, Andreas
; Bech, Martin
LU
; Koehler, Thomas
; Pfeiffer, Franz
and Noël, Peter B
- organization
- publishing date
- 2015
- type
- Contribution to journal
- publication status
- published
- subject
- in
- Scientific Reports
- volume
- 5
- article number
- 10452
- publisher
- Nature Publishing Group
- external identifiers
-
- pmid:26067714
- wos:000356148800001
- scopus:84931271582
- pmid:26067714
- 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
- 2016-04-01 13:00:06
- date last changed
- 2022-04-06 01:55:26
@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.}},
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 = {{https://lup.lub.lu.se/search/files/3100611/8610854}},
doi = {{10.1038/srep10452}},
volume = {{5}},
year = {{2015}},
}