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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 Ying1,3

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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