The integration of PET and MR into a single scanner entails challenges as well as potential, both of which this thesis addresses with mathematical methods. An example is correction for positron range in PET imaging, for which a new, simulation-based method is presented that accounts for the scanner’s magnetic field. Another example is parametric PET imaging, which is susceptible to noise, but which can be improved with high-resolution anatomical MRI data. Evaluations were performed using a newly developed reconstruction framework and include clinical data from a Biograph mMR scanner.
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The integration of PET and MR into a single scanner entails challenges as well as potential, both of which this thesis addresses with mathematical methods. An example is correction for positron range in PET imaging, for which a new, simulation-based method is presented that accounts for the scanner’s magnetic field. Another example is parametric PET imaging, which is susceptible to noise, but which can be improved with high-resolution anatomical MRI data. Evaluations were performed using a newly...
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