The European Journal of Nuclear Medicine and Molecular Imaging (EJNMMI) covers a broad scope of (molecular) imaging, radiopharmaceutical therapy,...

EJNMMI strongly encourages authors to follow reporting guidelines, most commonly STARD, STROBE or PRISMA when preparing their study. These guidelines can be accessed via the Equator Network website: STARD – Reporting of diagnostic accuracy studies

European Journal of Nuclear Medicine and Molecular Imaging provides a platform for exchanging clinical and scientific information within nuclear medicine and ...

The EJNMMI Journal Family. Journal navigation. About this journal. Aims and scope Editorial board Editorial policies Ethics and disclosures Rights and Permissions Contact the journal ...

The field of interest includes advanced imaging analyses techniques and artificial intelligence application in the field of imaging. Reports on original works related to physics, dosimetry, radiation biology, radiochemistry and pharmacy, will be …

The European Journal of Nuclear Medicine and Molecular Imaging (EJNMMI) covers a broad scope of (molecular) imaging, radiopharmaceutical therapy, image guided therapy, artificial intelligence, among others, ...

Editors Editor-in-Chief Professor Ignasi Carrio, MD, FEBNM, FRSC, FRCP, Autonomous University of Barcelona, Spain Associate Editors Professor Ali Afshar-Oromieh, MD, Specialist in Nuclear Medicine, University Hospital of Bern (Inselspital), Switzerland Professor Henry Hee-Seung Bom, MD, PhD, Chonnam National University Hwasun Hospital, Hwasun, South Korea

2016年3月21日 · The aim of EJNMMI Radiopharmacy and Chemistry is to publish research in the field of new imaging and radionuclide based therapeutic agents that can be applied in nuclear medicine and molecular imaging.

Volume 10, issue 1 articles listing for EJNMMI Research. We use essential cookies to make sure the site can function. We also use optional cookies for advertising, personalisation of content, usage analysis, and social media.

2025年2月11日 · Purpose This study aims to develop and validate a deep learning framework designed to eliminate the second CT scan of dual-tracer total-body PET/CT imaging. Methods We retrospectively included three cohorts of 247 patients who underwent dual-tracer total-body PET/CT imaging on two separate days (time interval:1–11 days). Out of these, 167 underwent …