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- W1630904681 abstract "Dark-field signals are dependent on local orientations and are sensitive to small structural variations in objects. Grating-based X-ray dark-field imaging is a novel technique for gaining image contrast for object structures at size scales below setup resolution. Consequently, dark-field imaging produces images with superior contrast for weak absorption objects and reveals morphological information, leading it particularly beneficial for medical imaging and non-destructive testing. However, up to now algorithms for fully recovering the orientation dependence in a tomographic volume are still unexplored. In this thesis, we propose a new reconstruction method for grating-based X-ray dark-field tomography. The presented algorithm is based on the formula in which an orientation-dependent signal is taken as an additional observable from a standard tomographic scan. The gradient descent method with zero constraints is the solution to the inverse problem. In detail, we extend the tomographic volume to a tensorial set of voxel data, containing the local orientation and contributions to dark-field scattering. The presented algorithm is experimentally verified with a well-defined phantom, a fibrous wooden sample, a carbon fiber reinforced carbon (CFRC) sample, a dried peanut with an opening on its shell and a cotton fiber sample. In our experiments we present the first results of several test specimen exhibiting a heterogeneous composition in micro-structure, which demonstrates the diagnostic potential of the new method. Second host university of my EM-COSSE programme is Friedrich-Alexander-Universitat Erlangen-Nurnberg (FAU) in Germany. I finished my thesis there." @default.
- W1630904681 created "2016-06-24" @default.
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- W1630904681 date "2014-03-31" @default.
- W1630904681 modified "2023-09-23" @default.
- W1630904681 title "Local Orientation Dark-field Reconstruction" @default.
- W1630904681 hasPublicationYear "2014" @default.
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