Matthias Hofmann1,2, Florian Steinke1, Ilja Bezrukov1,2, Armin Kolb2, Philip Aschoff2, Matthias Lichy2, Michael Erb2, Thomas Ngele2, Michael Brady3, Bernhard Schlkopf1, Bernd Pichler2
1Max Planck Institute for Biological Cybernetics, Tuebingen, Germany; 2Department of Radiology, University of Tuebingen, Tuebingen, Germany; 3Wolfson Medical Vision Laboratory, University of Oxford, Oxford, UK
There has recently been a growing interest in combining PET and MR. Attenuation correction (AC), which accounts for radiation attenuation properties of the tissue, is mandatory for quantitative PET. In the case of PET/MR the attenuation map needs to be determined from the MR image. This is intrinsically difficult as MR intensities are not related to the electron density information of the attenuation map. Using ultra-short echo (UTE) acquisition, atlas registration and machine learning, we present methods that allow prediction of the attenuation map based on the MR image both for brain and whole body imaging.