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Project

Quantitative model-based tomography.

Conventional analytical methods for CT reconstruction result in artifacts for non-ideal, constrained, CT acquisitions such as when only a limited angular range is available, or when only few projection images can be acquired due to time constraints and when the image formation model is simply inadequate. I will focus on the development of novel reconstruction techniques that take advantage of prior knowledge (e.g. sample shape, materials, energy spectra) in both X-ray absorption and quantitative phase contrast tomography to solve these issues and I will interconnect the developed algorithms with equally flexible image acquisition hardware, thereby taking advantage of prior knowledge of the object to be scanned and as well as of the imaging hardware itself.
Date:1 Oct 2018 →  30 Sep 2023
Keywords:TOMOGRAPHY
Disciplines:Multimedia processing, Biological system engineering, Signal processing, Medical imaging and therapy, Other paramedical sciences