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  • 1. Berthon, B.
    et al.
    Häggström, Ida
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Apte, A.
    Beattie, B.
    Kirov, A.
    Humm, J.
    Marshall, C.
    Spezi, E.
    Larsson, Anne
    Umeå University, Faculty of Medicine, Department of Radiation Sciences.
    Schmidtlein, C.
    A Fast Positron Emission Tomography Simulator for Synthetic Lesion Simulation2014In: European Journal of Nuclear Medicine and Molecular Imaging, ISSN 1619-7070, E-ISSN 1619-7089, Vol. 41, no 2, p. S367-S367Article in journal (Other academic)
  • 2.
    Berthon, Beatrice
    et al.
    Wales Research and Diagnostic PET Imaging Centre, Cardiff University, Cardiff, UK.
    Häggström, Ida
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Apte, Aditya
    Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, USA.
    Beattie, Bradley J.
    Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, USA.
    Kirov, Assen S.
    Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, USA.
    Humm, John L.
    Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, USA.
    Marshall, Christopher
    Wales Research and Diagnostic PET Imaging Centre, Cardiff University, Cardiff, UK.
    Spezi, Emiliano
    School of Engineering, Cardiff University, Cardiff, Wales, UK.
    Larsson, Anne
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Schmidtlein, C. Ross
    Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, USA.
    PETSTEP: generation of synthetic PET lesions for fast evaluation of segmentation methods2015In: Physica medica (Testo stampato), ISSN 1120-1797, E-ISSN 1724-191X, Vol. 31, no 8, p. 969-980Article in journal (Refereed)
    Abstract [en]

    Purpose: This work describes PETSTEP (PET Simulator of Tracers via Emission Projection): a faster and more accessible alternative to Monte Carlo (MC) simulation generating realistic PET images, for studies assessing image features and segmentation techniques.

    Methods: PETSTEP was implemented within Matlab as open source software. It allows generating threedimensional PET images from PET/CT data or synthetic CT and PET maps, with user-drawn lesions and user-set acquisition and reconstruction parameters. PETSTEP was used to reproduce images of the NEMA body phantom acquired on a GE Discovery 690 PET/CT scanner, and simulated with MC for the GE Discovery LS scanner, and to generate realistic Head and Neck scans. Finally the sensitivity (S) and Positive Predictive Value (PPV) of three automatic segmentation methods were compared when applied to the scanner-acquired and PETSTEP-simulated NEMA images.

    Results: PETSTEP produced 3D phantom and clinical images within 4 and 6 min respectively on a single core 2.7 GHz computer. PETSTEP images of the NEMA phantom had mean intensities within 2% of the scanner-acquired image for both background and largest insert, and 16% larger background Full Width at Half Maximum. Similar results were obtained when comparing PETSTEP images to MC simulated data. The S and PPV obtained with simulated phantom images were statistically significantly lower than for the original images, but led to the same conclusions with respect to the evaluated segmentation methods.

    Conclusions: PETSTEP allows fast simulation of synthetic images reproducing scanner-acquired PET data and shows great promise for the evaluation of PET segmentation methods.

  • 3.
    Häggström, Ida
    Umeå University, Facult