Abstract #3898

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

Jakub Baran^1,2, Zhaolin Chen^1,3, Francesco Sforazzini¹, Sharna Jamadar^1,4,5, Nicholas Ferris^1,6, Nadim Jon Shah^1,7, Marian Cholewa², and Gary Egan^1,4,5

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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