• DPG Frühjahrstagung, Hamburg, 2016 (talk)
  • X-Ray Imaging Applications in Materials Science, Garching, 2016 (poster)
FellowshipsDeutsche Physikalische Gesellschaft (DPG)
Abstract of PhD project Directional dark-field tomography with an X-ray Talbot-Lau interferometer

Grating-based X-ray phase-contrast imaging [1] has gained increasing interest. Using a Talbot-Lau interferometer three image modalities are obtained, and the X- ray phase-contrast imaging method thus provides additional information about the inner structure of materials which are not visible in conventional X-ray attenuation imaging. The X-ray dark-field image [2] in particular consists of signals generated by granular or fibrous structures on scales below the position resolution of the imaging system. Application in both medical imaging and non-destructive materials testing, therefore, offers promising opportunities. Furthermore, the dark-field signal provides information about the orientation of structures (directional dark-field imaging [3]) due to isotropic and anisotropic contributions to the scattering signal. Using computed tomography scans enables the reconstruction of alignment [4]. Our recent project deals with the tensorial reconstruction of 3D directional dark-field datasets [5] obtained using a helical tomography setup.

First steps in designing this helical imaging system have been taken. Because there is no gantry available the object itself rotates rather than the source and detector. Due to a small field of view limited by the gratings, the whole grating-detector system has to be moved with respect to the object translation (Fig. 1).

The overall aim of the project is an evaluated and optimized helical X-ray dark-field imaging scanning system which can be used for medical imaging as well as for non-destructive materials testing.

[1] F. Pfeiffer et al., Nat. Phys. 2 (4), 258-261 (2006).
[2] F. Pfeiffer et al., Nat. Mat. 7, 134-137 (2008).
[3] T. H. Jensen et al., Phys. Med. Biol. 55 (12), 3317-23 (2010).
[4] F. L. Bayer et al., PNAS, vol. 111, pp. 12699-12704, 2014.
[5] S. Hu et al., Bildverarbeitung für die Medizin, pp. 492–497, March 2015.