Local Orientation Dark-field Reconstruction

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-Universität Erlangen-Nürnberg (FAU) in Germany. I finished my thesis there.

Subject

dark-field reconstruction

To reference this document use:

http://resolver.tudelft.nl/uuid:ac56f913-3eab-42c7-a380-5c6615afeae4

Part of collection

Student theses

Document type

master thesis

Rights

Files

PDF

ThesisHu.pdf

13.37 MB

Close viewer