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By pre\u2010delivering a subset of single\u2010energy proton spots as probes, in\u2010beam PET has the potential to support online proton range verification and may inform subsequent spot delivery. However, the limited acquisition time and low yields of positron emitters result in noisy reconstructed images, and the open geometry of dual\u2010panel PET further introduces stretching artifacts.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Purpose<\/jats:title>\n                    <jats:p>To address these issues, this study proposed a 3D U\u2010Net\u2010based post\u2010processing method to enhance in\u2010beam PET image quality and evaluated its feasibility through Monte Carlo simulations and preliminary experimental validation.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      Thirteen head computed tomography (CT) phantoms were irradiated with horizontally and vertically incident single\u2010energy probes, representing two scenarios in which beams passed through relatively homogeneous and heterogeneous tissues. A phantom\u2010level split was used, with seven CT phantoms for training, two for validation, and four held\u2010out CT phantoms for testing. Proton probes in 3\u00d73, 5\u00d75, 7\u00d77, and 9\u00d79 spot patterns were simulated, with each spot delivering 2\u00d710\n                      <jats:sup>7<\/jats:sup>\n                      protons. In\u2010beam PET acquisition was performed for 30 s. Unfiltered reconstructed PET images were used as network inputs, and ground\u2010truth activity distributions served as labels. Gaussian\u2010filtered PET images served as the baseline for performance evaluation. Image quality was quantified by peak signal\u2010to\u2010noise ratio (PSNR) and structural similarity index (SSIM), and proton range verification accuracy was evaluated by absolute range error (ARE). Additional simulations with CT density perturbations were conducted to evaluate sensitivity to proton range shifts. Preliminary experimental validation was performed using an all\u2010digital PET prototype and polymethyl methacrylate (PMMA) phantoms.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>For horizontal beams, median PSNR values increased from 21.4\u201323.9 to 35.2\u201337.4, median SSIM values increased from 0.450\u20130.621 to 0.906\u20130.961, and median ARE values decreased from 1.05\u20131.18\u00a0mm to 0.52\u20130.73\u00a0mm. For vertical beams, median PSNR values improved from 21.9\u201323.2 to 29.2\u201334.1, median SSIM values improved from 0.480\u20130.560 to 0.745\u20130.895, and median ARE values decreased from 1.80\u20132.40\u00a0mm to 1.50\u20131.73\u00a0mm. The proposed method also demonstrated improved sensitivity to simulated range shifts and consistent improvements on experimental PET data.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>These findings demonstrate the preliminary feasibility of using 3D U\u2010Net\u2010based post\u2010processing to enhance dual\u2010panel in\u2010beam PET image quality and improve PET\u2010based proton range verification.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/mp.70609","type":"journal-article","created":{"date-parts":[[2026,8,3]],"date-time":"2026-08-03T12:32:46Z","timestamp":1785760366000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Improving dual\u2010panel in\u2010beam PET imaging for proton therapy monitoring using 3D 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