Nuklearmedizin 2019; 58(02): 124
DOI: 10.1055/s-0039-1683526
Vorträge
Medizinische Physik
Georg Thieme Verlag KG Stuttgart · New York

Optical Flow Parameter Optimization for Whole-body PET Motion Detection

S Pösse
1   University of Münster, European Institute for Molecular Imaging, Münster
,
F Büther
2   University Hospital of Münster, Department of Nuclear Medicine, Münster
,
M Schäfers
2   University Hospital of Münster, Department of Nuclear Medicine, Münster
,
KP Schäfers
1   University of Münster, European Institute for Molecular Imaging, Münster
› Author Affiliations
Further Information

Publication History

Publication Date:
27 March 2019 (online)

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    Ziel/Aim:

    PET is well known to be affected by respiration. Therefore motion correction methods have been introduced using optical flow techniques. In this study, optical flow parameters were optimized based on PET to receive optimal motion vector fields covering the real physiological respiratory motion.

    Methodik/Methods:

    PET/CT listmode data and a respiratory signal (ANZAI belt system) of 17 patients were acquired on an integrated PET/CT, 1h p.i. of F-18-FDG (4MBq/kg body weight). Data was sorted into 10 respiratory gates with the ANZAI signal and reconstructed. Optical flow, based on a multi-level approach by Horn-Schunck (1), was applied to gate 10 (reference gate 1) by varying the intrinsic parameters (480 combinations): regularization α, step size of the algorithm (tau), number of iterations, number of multi-levels and mode. The evaluation of these vector fields was based on a volume of 11 × 11 × 11 voxels with a FDG positive lesion at the center. For each lesion, the mean 3D vector length was calculated and compared to the manually determined displacement. In addition, the angle between the computed and manually determined vector was calculated. The parameter set leading to the lowest deviation regarding vector length and orientation is assumed to best cover the real physiological motion.

    Ergebnisse/Results:

    40 lesions were included in the optimization process. Considering all evaluated cases, different parameter sets exist leading to similar optimal results regarding vector length and orientation. We found one common parameter set for all lesions with parameters alpha = 0.01, tau = 0.1, number of iterations = 7500, number of multi-level = 10, mode = no mass preservation.

    Schlussfolgerungen/Conclusions:

    Parameter optimization for optical flow is an important preprocessing step in motion detection approaches to achieve reasonable physiological motion vectors. A common optimal set of parameters could be defined that results in excellent motion vector fields for all evaluated PET cases.

    Literatur/References:

    [1] M. Dawood, et al., “Respiratory motion correction in 3-D PET data with advanced optical flow algorithms.” IEEE transactions on medical imaging, vol. 27, no. 8, pp. 1164 – 75, 2008.


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