IDP/Klinisches Anwendungsprojekt: Regularization of spherical functions in medical imaging of X-ray anisotropic dark-field signals
Project by: Stefan Haninger
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. New X-ray contrast modalities, such as phase-contrast and dark-field contrast, are being developed in the last few years, based on a break-through in grating interferometry, with many promising clinical applications, ranging from breast cancer detection to diagnosis of osteoporosis.
Tasks
The aim of this project is the investigation of the X-ray dark-field contrast with an eye towards application in medical imaging of lung and brain. In particular, regularization techniques are to be investigated for the recently introduced anisotropic X-ray dark-field tomography (AXDT) imaging modality. Based on the existing C++ framework “CampRecon”, which already incorporates iterative reconstruction methods without regularization for AXDT reconstruction, regularization techniques, such as total variation regularization, are to be implemented and evaluated. These regularization techniques should be applied component-wise to the spherical harmonics coefficients of the AXDT reconstruction problem. The resulting code will be implemented in the “CampRecon” framework and will be applied to clinical samples provided by our partners.
Requirements
Scientific programming, strong mathematic background, C++
Contact