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Techn. Fakultät Willkommen am Institut für Informatik FAU-Logo

Sebastian Käppler M. Sc.

Researcher in the X-Ray Phase-Contrast group at the Pattern Recognition Lab of the Friedrich-Alexander-Universität Erlangen-Nürnberg

Developing novel algorithms for improving image quality in Phase Contrast X-ray Imaging

Projects

Signal Decomposition for X-ray Dark-field Imaging
S. Käppler, F. Bayer, T. Weber, A. Maier, G. Anton, J. Hornegger, C. Riess et al.
  • 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.

    Articles in Conference Proceedings
    Medical Image Computing and Computer-Assisted Intervention -- MICCAI 2014 (International Conference on Medical Image Computing and Computer-Assisted Intervention), Boston, MA, USA, 15.09.2014, pp. 170-177, 2014, ISBN 978-3-319-10404-1 (BiBTeX, Who cited this?)
  • Dark-field image of an ex-vivo human breast, before and after processing.
Shading Correction for Grating-based Differential Phase Contrast X-ray Imaging
S. Käppler, J. Wandner, T. Weber, A. Maier, G. Anton, J. Hornegger, C. Riess
  • Grating-based differential phase-contrast X-ray is a novel imaging modality with excellent soft-tissue contrast. Besides standard X-ray attenuation, it provides complementary information on the differential phase shift and the dark-field signal, which reveals structure variations at (sub-)micron scale. Current experimental setups suffer from a narrow field of view of 2-4cm. Thus, multiple exposures have to be stitched together to image larger objects. However, individual exposures are inherently affected by intensity variations, such that tiling artifacts corrupt the stitched projection. These artifacts are most severe in the differential phase image and highly impact their diagnostic value.

     

    To address this issue, we propose a novel optimization-based algorithm for fully compensating these tiling artifacts. Our algorithm estimates a smooth bias field for each individual exposure with a global objective function that minimizes the intensity distortion within and across different tiles in the projection. Compared to a currently widely used heuristic, our algorithm leverages the information available from all exposures to estimate the individual bias fields. The evaluation shows the superiority of the proposed algorithm, as it produces bias-free images. To our knowledge, this is the first bias correction algorithm for differential phase images that yields images with nearly imperceptible transitions between individual exposures.

    Articles in Conference Proceedings
    2014 IEEE Nuclear Science Symposium and Medical Imaging Conference Record (NSS/MIC) ((IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC) 2014)), Seattle, WA, USA, 08.11.2014, pp. 00-00, 2014 (BiBTeX, Who cited this?)
  • Differential phase contrast image of an ex-vivo human breast, before and after processing.