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Abstract #3898

SPM-BASED SEGMENTATION OF AIR IN THE HUMAN HEAD FOR IMPROVED PET ATTENUATION CORRECTION IN SIMULTANEOUS PET/MR

Jakub Baran1,2, Zhaolin Chen1,3, Francesco Sforazzini1, Sharna Jamadar1,4,5, Nicholas Ferris1,6, Nadim Jon Shah1,7, Marian Cholewa2, and Gary Egan1,4,5

1Monash Biomedical Imaging, Monash University, Melbourne, Australia, 2Department of Biophysics, University of Rzeszow, Rzeszow, Poland, 3Department of Electrical and Computer Systems Engineering, Monash University, Melbourne, Australia, 4Monash Institute of Cognitive and Clinical Neurosciences and School of Psychological Sciences, Monash University, Melbourne, Australia, 5Australian Research Council Centre of Excellence for Integrative Brain Function, Monash University, Melbourne, Australia, 6Monash Imaging, Monash Health, Melbourne, Australia, 7Institute of Neuroscience and Medicine, Forschungszentrum Jülich GmbH, Jülich, Germany

Dual-echo UTE MR sequences are widely used to estimate PET attenuation coefficients in simultaneous PET/MR imaging. However, due to susceptibility artefacts, air cavities in the head together with brain tissues and bones, can be misclassified, especially around air-tissue interface regions. In this work, we propose an SPM-based air and background segmentation method to improve the PET attenuation correction for simultaneous PET/MR imaging of the human brain. We compare air segmentation methods for more accurate air classification using an in-vivo MR-PET dataset and demonstrate improved PET image reconstruction accuracy.

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