Joint PET-MR respiratory motion models for clinical PET motion correction

نویسندگان

  • Hadi Fayad
  • Freddy Odille
  • Holger Schmidt
چکیده

Patient motion due to respiration can lead to artefacts and blurring in positron emission tomography (PET) images, in addition to quantification errors. The integration of PET with magnetic resonance (MR) imaging in PET-MR scanners provides complementary clinical information, and allows the use of high spatial resolution and high contrast MR images to monitor and correct motion-corrupted PET data. In this paper we build on previous work to form a methodology for respiratory motion correction of PET data, and show it can improve PET image quality whilst having minimal impact on clinical PET-MR protocols. We introduce a joint PET-MR motion model, using only 1 min per PET bed position of simultaneously acquired PET and MR data to provide a respiratory motion correspondence model that captures inter-cycle and intracycle breathing variations. In the model setup, 2D multi-slice MR provides the dynamic imaging component, and PET data, via low spatial resolution framing and principal component analysis, provides the model surrogate. We evaluate different motion models (1D and 2D linear, and 1D and 2D polynomial) by computing model-fit and model-prediction errors on dynamic R Manber et al Joint PET-MR respiratory motion models for clinical PET motion correction Printed in the UK 6515 PMB © 2016 Institute of Physics and Engineering in Medicine 2016 61 Phys. Med. Biol.

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تاریخ انتشار 2016