Medica l Image Ana lysis & Ar t i f icia l Intel l igence Symposium 2022 Nr. 11: Stefanie Kaser, MSc: Ion CT image reconstruction with the TIGRE toolbox Curriculum Vitae: Stefanie Kaser completed her BSc and MSc in Technical Physics at TU Wien. Since December 2019, she is a PhD student at the Institute of High Energy Physics (Austrian Academy of Sciences), where she investigates computed tomography with ion beams for improved cancer therapy. In her work, she focuses on image reconstruction using data from Monte Carlo simulations and from a demonstrator system installed at the MedAustron facility and tested in several beam times where she participated. As image reconstruction for ion computed tomography is an extensive computational task, efficient code is essential to obtain fast results. Therefore, she extended the GPU-based TIGRE toolbox, initially developed for x-ray CT reconstruction, for ion imaging and investigated its potential in detail. Abstract: Ion CT image reconstruction with the TIGRE toolbox Radiotherapy with ions is a well-established method to treat deep-seated tumours. For treatment planning, an x-ray computed tomography (CT) scan is measured. The resulting image is given in Hounsfield units (HU) that are converted to relative stopping powers (RSPs) to describe the behaviour of ion beams in the patient tissues. This conversion process introduces range errors that affect the treatment planning accuracy. For an improved treatment plan, the planning CT could be measured with ions, which allows extracting the RSPs from the scan without further conversion. As ions are affected by multiple Coulomb scattering (MCS), their non-straight paths through the objectto-be-imaged have to be considered in the ion CT reconstruction process. For this reason, the GPUbased TIGRE toolbox, a software framework developed initially for x-ray CT, was extended to use it for ion imaging. The code extension was tested with imaging data from Geant4/GATE Monte Carlo simulations.
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