Emond, EC;
Bousse, A;
Brusaferri, L;
Groves, AM;
Hutton, BF;
Thielemans, K;
(2020)
Mass Preservation for Respiratory Motion Registration in both PET and CT.
In:
Proceedings of the 2019 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC).
IEEE: Manchester, UK.
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Abstract
Registration of medical images corresponding to different respiratory states is complicated, as respiration not only moves the lungs and nearby organs, but it also causes localised density and radiotracer activity concentration changes of up to 20% in the lung. Nevertheless, few registration methods incorporate mass-preserving constraints, which could lead to suboptimal estimation of the deformation. This is especially important in the case of diffuse lung diseases for which the deformation field could provide biomarkers for pulmonary mechanical properties. This preliminary work is aimed at evaluating the impact of lung expansion in CT and PET image registration. We use patient data for which gated CT and PET acquisition data are available. We compare results of mass-preserving registration with two novel priors on the Jacobian determinant of the deformation field. Best results were observed for edge-preserving regularisation, where the mean errors in the lungs are decreased (−17.0% for CT and −4.8% for regularised PET using average regularisation), compared to warped images with no mass preservation.
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