{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,3]],"date-time":"2026-04-03T14:56:54Z","timestamp":1775228214319,"version":"3.50.1"},"reference-count":32,"publisher":"Wiley","issue":"7","license":[{"start":{"date-parts":[[2023,5,16]],"date-time":"2023-05-16T00:00:00Z","timestamp":1684195200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":["aapm.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Medical Physics"],"published-print":{"date-parts":[[2023,7]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Background<\/jats:title><jats:p>Given the large number of readout pixels in clinical positron emission tomography (PET) scanners, signal multiplexing is an indispensable feature to reduce scanner complexity, power consumption, heat output, and\u00a0cost.<\/jats:p><\/jats:sec><jats:sec><jats:title>Purpose<\/jats:title><jats:p>In this paper, we introduce interleaved multiplexing (iMux) scheme that utilizes the characteristic light\u2010sharing pattern of depth\u2010encoding Prism\u2010PET detector modules with single\u2010ended readout.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>In the iMux readout, four anodes from every other silicon photomultiplier (SiPM) pixels across rows and columns, which overlap with four distinct light guides, are connected to the same application\u2010specific integrated circuit (ASIC) channel. The 4\u2010to\u20101 coupled Prism\u2010PET detector module was used which consisted of a 16\u00a0\u00d7 \u00a016 array of 1.5 \u00d7 1.5 \u00d7 20 mm<jats:sup>3<\/jats:sup> lutetium yttrium oxyorthosilicate (LYSO) scintillator crystals coupled to an 8 \u00d7 8 array with 3\u00a0\u00d7 \u00a03\u00a0mm<jats:sup>2<\/jats:sup> SiPM pixels. A deep learning\u2010based demultiplexing model was investigated to recover the encoded energy signals. Two different experiments were performed with non\u2010multiplexed and multiplexed readouts to evaluate the spatial, depth of interaction (DOI), and timing resolutions of our proposed iMux\u00a0scheme.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>The measured flood histograms, using the decoded energy signals from our deep learning\u2010based demultiplexing architecture, achieved perfect crystal identification of events with negligible decoding error. The average energy, DOI, and timing resolutions were 9.6 \u00b1 1.5%, 2.9 \u00b1 0.9\u00a0mm, and 266 \u00b1 19\u00a0ps for non\u2010multiplexed readout and 10.3 \u00b1 1.6%, 2.8 \u00b1 0.8\u00a0mm, and 311 \u00b1 28\u00a0ps for multiplexed readout,\u00a0respectively.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions<\/jats:title><jats:p>Our proposed iMux scheme improves on the already cost\u2010effective and high\u2010resolution Prism\u2010PET detector module and provides 16\u2010to\u20101 crystal\u2010to\u2010readout multiplexing without appreciable performance degradation. Also, only four SiPM pixels are shorted together in the 8\u00a0\u00d7 \u00a08 array to achieve 4\u2010to\u20101 pixel\u2010to\u2010readout multiplexing, resulting in lower capacitance per multiplexed\u00a0channel.<\/jats:p><\/jats:sec>","DOI":"10.1002\/mp.16456","type":"journal-article","created":{"date-parts":[[2023,5,16]],"date-time":"2023-05-16T12:00:46Z","timestamp":1684238446000},"page":"4234-4243","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["Interleaved signal multiplexing readout in depth encoding Prism\u2010PET detectors"],"prefix":"10.1002","volume":"50","author":[{"given":"Yixin","family":"Li","sequence":"first","affiliation":[{"name":"Department of Electrical and Computer Engineering College of Engineering and Applied Sciences Stony Brook University, Stony Brook  New York USA"},{"name":"Department of Radiology Weill Cornell Medical College Cornell University, New York  New York 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