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Abstract #2182

MR-based motion correction and anatomical guidance for improved PET image reconstruction in cardiac PET-MR imaging 

Camila Munoz1, Sam Ellis1, Stephan G Nekolla2, Karl P Kunze1,3, Teresa Vitadello4, Radhouene Neji1,3, René M. Botnar1, Julia A. Schnabel1, Andrew J. Reader1, and Claudia Prieto1
1School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom, 2Nuklearmedizinische Klinik und Poliklinik, Technische Universitat Munchen, Munich, Germany, 3MR Research Collaborations, Siemens Healthcare Limited, Frimley, United Kingdom, 4Department of Internal Medicine I, University hospital rechts der Isar, Technical University of Munich, Munich, Germany

Simultaneous PET-MR has shown promise for addressing several of the technical challenges that may degrade image quality in PET imaging, such as high noise levels, attenuation artefacts, and motion artefacts. While state-of-the-art PET image reconstruction techniques have addressed these issues separately, their combined effect has not been demonstrated. Here we introduce a single framework that integrates MR-based motion correction and anatomical guidance for improved simultaneous diagnostic cardiac PET-MR imaging. We evaluated the proposed framework on cardiac [18F]FDG PET-MR datasets and results show that, compared to conventional reconstruction algorithms, our framework results in sharper images, with increased contrast and reduced noise.

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