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Med. Biol."],"published-print":{"date-parts":[[2026,5,28]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Continuous depth-of-interaction (cDOI) detectors enable single-ended readout in positron emission tomography (PET) by encoding the interaction depth into the scintillation light distribution. This study presents a comprehensive performance optimization of a cDOI detector based on light distribution tailoring with crossed triangular-shaped reflectors by analyzing the effects of optical geometry based on various DOI decoding algorithms. Two parameters were systematically varied: the degree of light confinement through (1) optical segmentation and (2) crystal pitch adjustment. Five DOI decoding strategies\u2014variance, max\/sum ratio, Euclidean-distance classification, Gaussian and modified maximum-likelihood estimation, and artificial neural network (ANN) decoding\u2014were adopted with 8 \u00d7 8 SiPM readout data. Results show that moderate segmentation (2 \u00d7 2 configuration) achieved the best DOI precision, yielding a 4.7 mm full width at half maximum (FWHM) and an ANN classification accuracy of 89 %. In the pitch study, 1.5 mm-pitch detector achieved better performance than 3.0 mm-pitch, indicating that increased optical interfaces allows more accurate encoding of the depth-dependent light distribution within the SiPM array. The ANN decoder consistently outperformed in DOI resolution compared to analytical and statistical methods by learning nonlinear spatial correlations among SiPM pixels. These findings highlight the coupled importance of optical geometry and data-driven decoding for achieving high DOI sensitivity in next-generation PET detector designs.<\/jats:p>","DOI":"10.1088\/1361-6560\/ae6ead","type":"journal-article","created":{"date-parts":[[2026,5,15]],"date-time":"2026-05-15T22:56:12Z","timestamp":1778885772000},"page":"105024","update-policy":"https:\/\/doi.org\/10.1088\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Influence of scintillation light confinement on depth-of-interaction measurement performance in a single-ended readout PET detector"],"prefix":"10.1088","volume":"71","author":[{"given":"Hyeong Seok","family":"Shim","sequence":"first","affiliation":[{"name":"Seoul National University"},{"name":"Seoul National University"},{"name":"Seoul National University College of Medicine"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Min Jeong","family":"Cho","sequence":"additional","affiliation":[{"name":"Seoul National University"},{"name":"Seoul National University"},{"name":"Seoul National University College of Medicine"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wen","family":"He","sequence":"additional","affiliation":[{"name":"Stanford University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1442-2285","authenticated-orcid":true,"given":"Min Sun","family":"Lee","sequence":"additional","affiliation":[{"name":"Daegu Gyeongbuk Institute of Science and Technology"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Craig S","family":"Levin","sequence":"additional","affiliation":[{"name":"Stanford University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7623-053X","authenticated-orcid":true,"given":"Jae Sung","family":"Lee","sequence":"additional","affiliation":[{"name":"Seoul National University"},{"name":"Seoul National University"},{"name":"Seoul National University College of Medicine"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"266","published-online":{"date-parts":[[2026,6,1]]},"reference":[{"key":"pmbae6eadbib1","doi-asserted-by":"publisher","first-page":"02LT01","DOI":"10.1088\/1361-6560\/aa9dc5","type":"journal-article","article-title":"Using convolutional neural networks to estimate time-of-flight from PET detector waveforms","volume":"63","author":"Berg","year":"2018","journal-title":"Phys. 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Published on behalf of Institute of Physics and Engineering in Medicine by IOP Publishing Ltd","name":"copyright_information","label":"Copyright Information"},{"value":"2026-01-18","name":"date_received","label":"Date Received","group":{"name":"publication_dates","label":"Publication dates"}},{"value":"2026-05-15","name":"date_accepted","label":"Date Accepted","group":{"name":"publication_dates","label":"Publication dates"}},{"value":"2026-06-01","name":"date_epub","label":"Online publication date","group":{"name":"publication_dates","label":"Publication dates"}}]}}