{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,9]],"date-time":"2026-04-09T14:23:45Z","timestamp":1775744625218,"version":"3.50.1"},"reference-count":40,"publisher":"Wiley","issue":"2","license":[{"start":{"date-parts":[[2026,1,27]],"date-time":"2026-01-27T00:00:00Z","timestamp":1769472000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,1,27]],"date-time":"2026-01-27T00:00:00Z","timestamp":1769472000000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["aapm.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Medical Physics"],"published-print":{"date-parts":[[2026,2]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>The development of PET scanners dedicated to high temporal and spatial resolution organ\u2010specific imaging is an active research area, motivated by the need for cost reduction, improved lesion detectability and quantification in specific clinical scenarios, as well as by ongoing hardware and software innovations.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Purpose<\/jats:title>\n                    <jats:p>This study investigates and compares various image reconstruction strategies for a dual\u2010panel prostate\u2010dedicated PET scanner (ProVision), which features four\u2010layered dual\u2010readout time\u2010of\u2010flight depth\u2010of\u2010interaction detectors and a 22\u2010position acquisition protocol to improve angular coverage.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Materials and methods<\/jats:title>\n                    <jats:p>A list\u2010mode MLEM algorithm with multi\u2010ray modeling was developed and optimized using a scaled NEMA image quality phantom to determine optimal number of rays and iterations. These parameters were then used to reconstruct data from both simulation and experimental acquisitions, including an anthropomorphic pelvis phantom, named Adam\u2010PETer. Four reconstruction approaches were evaluated: classical MLEM; MLEM with embedded shift\u2010variant point spread function (PSF) modeling; a hybrid list\u2010mode reconstruction; and a Swin\u2010UNETR\u2010based deep learning model applied as a post\u2010reconstruction enhancement to MLEM images. Performance was assessed using contrast recovery coefficient (CRC), contrast\u2010to\u2010noise ratio (CNR), and contrast\u2010to\u2010noise consistency (CNC), on both a scaled NEMA phantom and an experimental anthropomorphic phantom.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>In the scaled NEMA phantom simulation, the Swin\u2010based method yielded the highest CNR and CNC, especially for the smallest spheres, thereby outperforming both standard MLEM and the hybrid algorithm. In the Adam\u2010PETer experimental prostate phantom, the CNR was 10.43 for MLEM, 14.48 for Hybrid, and 13.85 for Swin for the larger lesion (10\u00a0mm). The CNR values were 2.28, 3.03, and 4.35, respectively, for the smaller lesion (8\u00a0mm). CNC values also varied across methods, with Swin achieving the best result for the smaller lesion. These findings indicate that model\u2010based and learned methods offer complementary strengths depending on lesion contrast and size.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>The PET scanner\u2010adapted reconstruction combined with deep learning refinement improves image quality in dedicated, limited\u2010angle PET systems.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/mp.70298","type":"journal-article","created":{"date-parts":[[2026,1,27]],"date-time":"2026-01-27T10:00:43Z","timestamp":1769508043000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Image reconstruction and elongation artifact reduction for a dual\u2010panel dedicated prostate PET scanner"],"prefix":"10.1002","volume":"53","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7327-2558","authenticated-orcid":false,"given":"Abdollah","family":"Saberi Manesh","sequence":"first","affiliation":[{"name":"Division of Nuclear Medicine and Molecular Imaging Geneva University Hospital  Geneva Switzerland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4370-680X","authenticated-orcid":false,"given":"Mehdi","family":"Amini","sequence":"additional","affiliation":[{"name":"Division of Nuclear Medicine and Molecular Imaging Geneva University Hospital  Geneva Switzerland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1233-9576","authenticated-orcid":false,"given":"Yazdan","family":"Salimi","sequence":"additional","affiliation":[{"name":"Division of Nuclear Medicine and Molecular Imaging Geneva University Hospital  Geneva Switzerland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Katayoun","family":"Doroud","sequence":"additional","affiliation":[{"name":"Picotech  St Genis Pouilly France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Crispin","family":"Williams","sequence":"additional","affiliation":[{"name":"Picotech  St Genis Pouilly France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Themistoklis","family":"Williams","sequence":"additional","affiliation":[{"name":"Picotech  St Genis Pouilly France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6526-0960","authenticated-orcid":false,"given":"Hossein","family":"Arabi","sequence":"additional","affiliation":[{"name":"Division of Nuclear Medicine and Molecular Imaging Geneva University Hospital  Geneva 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