Last year, Guilherme Domingues Kolinger published the first results of his HYBRID project in EJNMMI Research. In this paper he describes how the analysis of PET images can be made more reliable.
Nicolò Capobianco won a poster award at the SNMMI 2020 Annual Meeting – Virtual Edition with his poster ‘Transfer learning of AI-based uptake classification from 18F-FDG PET/CT to 68Ga-PSMA-11 PET/CT for whole-body tumor burden assessment'.
This project has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No. 764458.
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