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Signal Decomposition for X-ray Dark-Field Imaging

Authors :
Thomas Weber
Claudia Rauh
Matthias W. Beckmann
Gisela Anton
Andreas Maier
Rüdiger Schulz-Wendtland
Felix Heindl
Arndt Hartmann
Thilo Michel
Gueluemser Oezguel
Florian Bayer
Peter A. Fasching
Evelyn Wenkel
David L. Wachter
Jens Rieger
Michael Uder
Sebastian Kaeppler
Joachim Hornegger
Christian Riess
Georg Pelzer
Source :
Medical Image Computing and Computer-Assisted Intervention – MICCAI 2014 ISBN: 9783319104034, MICCAI (1), ResearcherID
Publication Year :
2014
Publisher :
Springer International Publishing, 2014.

Abstract

Grating-based X-ray dark-field imaging is a new imaging modality. It allows the visualization of structures at micrometer scale due to small-angle scattering of the X-ray beam. However, reading dark-field images is challenging as absorption and edge-diffraction effects also contribute to the dark-field signal, without adding diagnostic value. In this paper, we present a novel – and to our knowledge the first – algorithm for isolating small-angle scattering in dark-field images, which greatly improves their interpretability. To this end, our algorithm utilizes the information available from the absorption and differential phase images to identify clinically irrelevant contributions to the dark-field image. Experimental results on phantom and ex-vivo breast data promise a greatly enhanced diagnostic value of dark-field images.

Details

ISBN :
978-3-319-10403-4
ISBNs :
9783319104034
Database :
OpenAIRE
Journal :
Medical Image Computing and Computer-Assisted Intervention – MICCAI 2014 ISBN: 9783319104034, MICCAI (1), ResearcherID
Accession number :
edsair.doi.dedup.....28f56c32f9caec1b241737f6930d1275
Full Text :
https://doi.org/10.1007/978-3-319-10404-1_22