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Communication Dans Un Congrès Année : 2017

Implementation and Validation of an efficient decomposition based system matrix approach incorporating subject’s physical phenomena

Benjamin Auer
  • Fonction : Auteur
Virgile Bekaert
David Brasse

Résumé

In small animal Single Photon Emission Computed Tomography (SPECT), attenuation and scatter introduce important artifacts in the reconstructed images, which could lead to misdiagnosis for subject's follow-up. Gold standard Monte Carlo Simulation (MCS) is one of the well-established tools that has been used in SPECT image reconstruction due to its ability to accurately model photon transport. However, MCS requires extensive computation time to obtain a low noise system matrix and are therefore inappropriate for the rate of daily exams performed in both clinical and preclinical routine: an improvement in simulation speed is thus mandatory. In this work, we validated, compared to a state of the art approach and by using a modified NU-4 IQ phantom, our efficient and simplified modeling of the physical phenomena occurring in the subject. Our approach based on a system matrix decomposition, associated to a scatter pre-calculated database method, demonstrated an acceptable time on a standard computer for daily imaging small animal follow-up (around 1h), leading to a personalized image reconstruction. The reconstruction workflow leads to significant image artifacts reduction as well as a 13% (on average) improvement in terms of recovery coefficients. Results presented in this study, conduct to the validation of the developed approach in comparison with a state of the art one which appears to be far too long for a daily exam perspective.
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Dates et versions

hal-02097391 , version 1 (12-04-2019)

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Citer

Benjamin Auer, Frederic Boisson, Virgile Bekaert, David Brasse. Implementation and Validation of an efficient decomposition based system matrix approach incorporating subject’s physical phenomena. 2017 IEEE Nuclear Science Symposium and Medical Imaging Conference, Oct 2017, Atlanta, United States. ⟨10.1109/NSSMIC.2017.8532617⟩. ⟨hal-02097391⟩
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