Adaptive recursive Bayesian estimation using expectation maximization for respiratory motion correction in Nuclear Medicine

Rhodri L. Smith, Ashrani Aizzuddin Abd Rahni, John Jones, Kevin Wells

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

A method to correct for irregular, non stationary respiratory motion is required to improve quantitative and qualitative accuracy of Nuclear Medicine Images. Solutions to date rely on temporally regular respiratory motion with static models learnt from training data. An adaptive approach with dynamic parameter learning of motion models is required. To this avail we cast respiratory motion estimation as a Hidden Markov model. An expectation maximization based Kalman smoother algorithm is utilized to infer hidden states of motion from observations of the patient's chest motion alone. The framework is validated using a computational anthropomorphic phantom (XCAT) with seven respiratory cycles with varying amplitude and frequency. A PET study is simulated with four 16mm lung lesions to assess the effectiveness of the approach. Preliminary tests are also performed on dynamic MRI data of a single volunteer. The likelihood of dynamical model fitting is monitored for individual respiratory cycles. Optimal estimates of previously unseen motion are made using the Kalman smoother. The proposed method can correct for respiratory motion to the order of 1.5mm. A thirty percent increase in mean uptake value for the corrected tumors in the simulated PET study was observed.

Original languageEnglish
Title of host publicationIEEE Nuclear Science Symposium Conference Record
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Print)9781479905348
DOIs
Publication statusPublished - 2013
Externally publishedYes
Event2013 60th IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2013 - Seoul
Duration: 27 Oct 20132 Nov 2013

Other

Other2013 60th IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2013
CitySeoul
Period27/10/132/11/13

Fingerprint

nuclear medicine
Nuclear Medicine
static models
cycles
chest
lungs
lesions
learning
casts
Volunteers
education
Thorax
tumors
Learning
Lung
estimates

Keywords

  • Respiratory motion correction adaptive recursive Bayesian estimation

ASJC Scopus subject areas

  • Radiation
  • Nuclear and High Energy Physics
  • Radiology Nuclear Medicine and imaging

Cite this

Smith, R. L., Abd Rahni, A. A., Jones, J., & Wells, K. (2013). Adaptive recursive Bayesian estimation using expectation maximization for respiratory motion correction in Nuclear Medicine. In IEEE Nuclear Science Symposium Conference Record [6829066] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/NSSMIC.2013.6829066

Adaptive recursive Bayesian estimation using expectation maximization for respiratory motion correction in Nuclear Medicine. / Smith, Rhodri L.; Abd Rahni, Ashrani Aizzuddin; Jones, John; Wells, Kevin.

IEEE Nuclear Science Symposium Conference Record. Institute of Electrical and Electronics Engineers Inc., 2013. 6829066.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Smith, RL, Abd Rahni, AA, Jones, J & Wells, K 2013, Adaptive recursive Bayesian estimation using expectation maximization for respiratory motion correction in Nuclear Medicine. in IEEE Nuclear Science Symposium Conference Record., 6829066, Institute of Electrical and Electronics Engineers Inc., 2013 60th IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2013, Seoul, 27/10/13. https://doi.org/10.1109/NSSMIC.2013.6829066
Smith RL, Abd Rahni AA, Jones J, Wells K. Adaptive recursive Bayesian estimation using expectation maximization for respiratory motion correction in Nuclear Medicine. In IEEE Nuclear Science Symposium Conference Record. Institute of Electrical and Electronics Engineers Inc. 2013. 6829066 https://doi.org/10.1109/NSSMIC.2013.6829066
Smith, Rhodri L. ; Abd Rahni, Ashrani Aizzuddin ; Jones, John ; Wells, Kevin. / Adaptive recursive Bayesian estimation using expectation maximization for respiratory motion correction in Nuclear Medicine. IEEE Nuclear Science Symposium Conference Record. Institute of Electrical and Electronics Engineers Inc., 2013.
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