Signal decomposition for X-ray dark-field imaging

Käppler S, Bayer F, Weber T, Maier A, Anton G, Hornegger J, Beckmann M, Fasching P, Hartmann A, Heindl F, Michel T, Oezguel G, Pelzer G, Rauh C, Rieger J, Schulz-Wendtland R, Uder M, Wachter D, Wenkel E, Riess C (2014)

Publication Type: Conference contribution, Original article

Publication year: 2014


Book Volume: 17

Pages Range: 170-177

Conference Proceedings Title: MICCAI 2014

Issue: Pt 1


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 darkfield 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.

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How to cite


Käppler, S., Bayer, F., Weber, T., Maier, A., Anton, G., Hornegger, J.,... Riess, C. (2014). Signal decomposition for X-ray dark-field imaging. In MICCAI 2014 (pp. 170-177).


Käppler, Sebastian, et al. "Signal decomposition for X-ray dark-field imaging." Proceedings of the MICCAI 2014: Medical Image Computing and Computer-Assisted Intervention 2014. 170-177.

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