IDP: Detectability Indices in Directional X-ray Dark-field Tomography
Project by: Theodor Cheslerean Boghiu
Advisor:
Nassir Navab
Supervision by:
Tobias Lasser
Abstract
Medical imaging modalities such as X-ray Computed Tomography (X-ray CT) or Positron Emission Computed Tomography (PET) have been the basis of accurate diagnosis in clinical practice for decades, one particular example being the detection of tumors. But medical imaging also plays a central role during the therapy, for example when planning complex surgeries or when planning and monitoring radiation therapy treatments. Advanced X-ray imaging contrast modalities, such as phase-contrast or dark-field contrast, have recently demonstrated very promising fields of application both in diagnosis and therapy. The dark-field contrast in particular promises advanced imaging capabilities that are unprecedented and not available in other medical imaging modalities. Thanks to its directional dependence, it enables resolving micro structure orientations below the detector resolution, allowing insights into various anatomical and physiological processes, such as the connectivity of the brain. However, for practical clinical application several technical issues still have to be addressed in order to reach feasibility in terms of experimental setup, acquisition and processing times as well as dose considerations. While the directional dependence and anisotropy of the X-ray dark-field signal enables new applications, it also requires more acquisitions sampled all around the object, and thus longer acquisition times, higher dose and longer processing times compared to traditional tomographic imaging modalities.
Tasks
Aim of this project is the investigation of detectability indices as a tool for automatic selection of only a few, relevant acquisition poses in well-defined scenarios. Based on well-defined imaging scenarios with available a-priori imaging data, detectability indices allow the definition of relevant features and subsequently the selection of suitable acquisition poses in order to accurately resolve those (and only those) features in the sample. This leads to a drastic reduction in acquisition poses, yielding lower acquisition times, lower processing times and reduced radiation dose.
In this project, detectability indices are to be investigated for the Anisotropic X-ray Dark-field Tomography (AXDT) imaging modality. After theoretical considerations and modifications in order to fit existing detectability index theory to the new imaging operator of AXDT, a practical implementation phase is planned, with simulated experiments as well as real experiments on clinical samples at the lab setup provided by our partners.
Requirements
Mathematical background, C++.
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