Respiratory motion correction for PET oncology applications using affine transformation of list mode data
Phys. Med. Biol.. 2006-12-12; 52(1): 121-140
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1. Phys Med Biol. 2007 Jan 7;52(1):121-40. Epub 2006 Dec 12.
Respiratory motion correction for PET oncology applications using affine
transformation of list mode data.
Lamare F(1), Cresson T, Savean J, Cheze Le Rest C, Reader AJ, Visvikis D.
(1)INSERM U650, Laboratoire du Traitement de l’information medicale (LaTIM),
Université de Bretagne occidentale, Brest, France.
Respiratory motion is a source of artefacts and reduced image quality in PET.
Proposed methodology for correction of respiratory effects involves the use of
gated frames, which are however of low signal-to-noise ratio. Therefore a method
accounting for respiratory motion effects without affecting the statistical
quality of the reconstructed images is necessary. We have implemented an affine
transformation of list mode data for the correction of respiratory motion over
the thorax. The study was performed using datasets of the NCAT phantom at
different points throughout the respiratory cycle. List mode data based PET
simulated frames were produced by combining the NCAT datasets with a Monte Carlo
simulation. Transformation parameters accounting for respiratory motion were
estimated according to an affine registration and were subsequently applied on
the original list mode data. The corrected and uncorrected list mode datasets
were subsequently reconstructed using the one-pass list mode EM (OPL-EM)
algorithm. Comparison of corrected and uncorrected respiratory motion average
frames suggests that an affine transformation in the list mode data prior to
reconstruction can produce significant improvements in accounting for respiratory
motion artefacts in the lungs and heart. However, the application of a common set
of transformation parameters across the imaging field of view does not
significantly correct the respiratory effects on organs such as the stomach,
liver or spleen.
PMID: 17183132 [Indexed for MEDLINE]