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Amplitude-based data selection for optimal retrospective reconstruction in micro-SPECT

Marine Breuilly 1, 2 Grégoire Malandain 1, 3 Julien Guglielmi 2 Robert Marsault 2 Thierry Pourcher 2 Philippe Franken 4 Jacques Darcourt 2
1 ASCLEPIOS - Analysis and Simulation of Biomedical Images
CRISAM - Inria Sophia Antipolis - Méditerranée
3 MORPHEME - Morphologie et Images
CRISAM - Inria Sophia Antipolis - Méditerranée , IBV - Institut de Biologie Valrose : U1091, Laboratoire I3S - SIS - Signal, Images et Systèmes
Abstract : Respiratory motion can blur the tomographic reconstruction of PET or SPECT images, which subsequently impair quantitative measurements, e.g. in the upper abdomen area. Respiratory signal phase-based gated reconstruction addresses this problem, but deteriorates the signal-to-noise ratio and other intensity-based quality measures. This article proposes a 3D reconstruction method dedicated to micro-SPECT imaging of mice. From a 4D acquisition, the phase images exhibiting motion are identified and the associated list-mode data are discarded, which enables the reconstruction of a 3D image without respiratory artefacts. The proposed method allows a motion-free reconstruction exhibiting both satisfactory count statistics and accuracy of measures. With respect to standard 3D reconstruction (NG3D) without breathing motion correction, an increase of 14.6% of the mean SUV has been observed, while, with respect to a gated 4D reconstruction (G4D), up to 60% less noise and an increase of up to 124% of the SNR have been demonstrated.
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Submitted on : Tuesday, March 12, 2013 - 10:57:05 AM
Last modification on : Tuesday, December 7, 2021 - 4:10:46 PM
Long-term archiving on: : Monday, June 17, 2013 - 12:02:10 PM


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Marine Breuilly, Grégoire Malandain, Julien Guglielmi, Robert Marsault, Thierry Pourcher, et al.. Amplitude-based data selection for optimal retrospective reconstruction in micro-SPECT. Physics in Medicine and Biology, IOP Publishing, 2013, 58 (8), pp.2657-2674. ⟨10.1088/0031-9155/58/8/2657⟩. ⟨hal-00799381⟩



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