Abstract #1337

Comparison of UTE-based Attenuation Correction Methods for Simultaneous PET/MR Imaging of the Children's Brain

Chang Gao¹, Junshen Xu¹, Bowen Fan¹, Jiajin Liu², and Kui Ying^1,3

¹Department of Engineering Physics, Tsinghua University, Beijing, People's Republic of China, ²Department of Nuclear Medicine, Chinese PLA General Hospital, People's Republic of China, ³Key Laboratory of Particle and Radiation Imaging, Ministry of Education, Medical Physics and Engineering Institute, Tsinghua University, Beijing, People's Republic of China

In simultaneous PET/MR imaging, PET attenuation correction is based on MRI, unlike PET/CT systems, which directly use CT measurements. Various approaches have been developed based on templates, atlas information, direct segmentation of T1-weighted MR images. In the present study, we introduced two approaches of UTE-based attenuation correction for simultaneous PET/MR imaging focusing on children’s brain, including segmentation-based method and Support Vector Machine (SVM) regression method. The results have been compared with Gaussian Mixture Regression (GMR) model method.

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