{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,21]],"date-time":"2026-07-21T01:49:32Z","timestamp":1784598572689,"version":"3.55.0"},"reference-count":56,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"1","license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"funder":[{"DOI":"10.13039\/100004313","name":"General Electric (GE) Healthcare","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100004313","id-type":"DOI","asserted-by":"publisher"}]},{"name":"National Institute for Health and Care Research (NIHR) University College London Hospital (UCLH) Biomedical Research Centre"},{"DOI":"10.13039\/501100000266","name":"Engineering and Physical Sciences Research Council (EPSRC) Centre for Doctoral Training i4Health","doi-asserted-by":"publisher","award":["EP\/S021930\/1"],"award-info":[{"award-number":["EP\/S021930\/1"]}],"id":[{"id":"10.13039\/501100000266","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000266","name":"EPSRC Project","doi-asserted-by":"publisher","award":["EP\/T000864\/1"],"award-info":[{"award-number":["EP\/T000864\/1"]}],"id":[{"id":"10.13039\/501100000266","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000266","name":"CCP SyneRBI through EPSRC","doi-asserted-by":"publisher","award":["EP\/T026693\/1"],"award-info":[{"award-number":["EP\/T026693\/1"]}],"id":[{"id":"10.13039\/501100000266","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Med. Imaging"],"published-print":{"date-parts":[[2023,1]]},"DOI":"10.1109\/tmi.2022.3203237","type":"journal-article","created":{"date-parts":[[2022,8,31]],"date-time":"2022-08-31T19:40:41Z","timestamp":1661974841000},"page":"29-41","source":"Crossref","is-referenced-by-count":17,"title":["An Investigation of Stochastic Variance Reduction Algorithms for Relative Difference Penalized 3D PET Image Reconstruction"],"prefix":"10.1109","volume":"42","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8871-9586","authenticated-orcid":false,"given":"Robert","family":"Twyman","sequence":"first","affiliation":[{"name":"Institute of Nuclear Medicine, UCL, London, U.K."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1292-0210","authenticated-orcid":false,"given":"Simon","family":"Arridge","sequence":"additional","affiliation":[{"name":"Department of Computer Science, UCL, London, U.K."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zeljko","family":"Kereta","sequence":"additional","affiliation":[{"name":"Department of Computer Science, UCL, London, U.K."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3775-9155","authenticated-orcid":false,"given":"Bangti","family":"Jin","sequence":"additional","affiliation":[{"name":"Department of Computer Science, UCL, London, U.K."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ludovica","family":"Brusaferri","sequence":"additional","affiliation":[{"name":"Institute of Nuclear Medicine, UCL, London, U.K."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7252-2607","authenticated-orcid":false,"given":"Sangtae","family":"Ahn","sequence":"additional","affiliation":[{"name":"GE Research, Niskayuna, NY, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Charles W.","family":"Stearns","sequence":"additional","affiliation":[{"name":"GE Healthcare, Waukesha, WI, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7481-0952","authenticated-orcid":false,"given":"Brian F.","family":"Hutton","sequence":"additional","affiliation":[{"name":"Institute of Nuclear Medicine, UCL, London, U.K."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8029-8692","authenticated-orcid":false,"given":"Irene A.","family":"Burger","sequence":"additional","affiliation":[{"name":"Nuclear Medicine Department, University Hospital Zurich, University of Zurich, Zürich, Switzerland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fotis","family":"Kotasidis","sequence":"additional","affiliation":[{"name":"GE Healthcare, Waukesha, WI, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5514-199X","authenticated-orcid":false,"given":"Kris","family":"Thielemans","sequence":"additional","affiliation":[{"name":"Institute of Nuclear Medicine, UCL, London, U.K."}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1088\/0031-9155\/51\/15\/r01"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/tns.2002.998681"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/42.538946"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1007\/s10851-010-0251-1"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1088\/0031-9155\/44\/11\/311"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/42.363108"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/42.921477"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/tns.2002.1039550"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/nss\/mic42101.2019.9059799"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/42.241889"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/tmi.2003.812251"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1088\/0031-9155\/60\/15\/5733"},{"key":"ref13","article-title":"Accelerating stochastic gradient descent using predictive variance reduction","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"26","author":"Johnson"},{"key":"ref14","article-title":"SAGA: A fast incremental gradient method with support for non-strongly convex composite objectives","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"27","author":"Defazio"},{"issue":"2","key":"ref15","first-page":"1","article-title":"A stochastic gradient method with an exponential convergence rate for finite training sets","volume":"1","author":"Roux","year":"2012","journal-title":"Nips"},{"key":"ref16","first-page":"2613","article-title":"SARAH: A novel method for machine learning problems using stochastic recursive gradient","volume-title":"Proc. 34th Int. Conf. Mach. Learn. (ICML)","author":"Nguyen"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/jproc.2020.3028013"},{"key":"ref18","first-page":"1","article-title":"Quantitatively accurate image reconstruction for clinical whole-body PET imaging","volume-title":"Proc. Conf. Handbook, Asia\u2013Pacific Signal Inf. Process. Assoc. Annu. Summit Conf. (APSIPA ASC)","author":"Asma"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1186\/s13550-020-00690-6"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1137\/17m1134834"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1088\/1361-6420\/ac2d74"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/nss\/mic42677.2020.9508105"},{"key":"ref23","first-page":"242","article-title":"Investigation of subset methodologies applied to penalised iterative PET reconstruction","volume-title":"Proc. 16th Virtual Int. Meeting Fully 3D Image Reconstruction Radiol. Nucl. Med.","volume":"14","author":"Twyman"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/tmi.1982.4307558"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/tmi.1986.4307734"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/nssmic.2016.8069458"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1137\/16m1080173"},{"key":"ref28","first-page":"1","article-title":"Large scale online learning","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Bottou"},{"key":"ref29","first-page":"1","article-title":"On biased stochastic gradient estimation","volume":"23","author":"Driggs","year":"2020","journal-title":"J. Mach. Learn. Res."},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1088\/0031-9155\/56\/4\/001"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1118\/1.3635220"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/NSS\/MIC44867.2021.9875442"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1118\/1.3480985"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1088\/0031-9155\/57\/4\/867"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/nssmic.2016.8069577"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/nssmic.2002.1239610"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/nssmic.2004.1466455"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1002\/mp.13576"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1007\/s10107-016-1030-6"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/tmi.2019.2913889"},{"key":"ref41","volume-title":"Numerical Optimization","author":"Nocedal","year":"2006"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1007\/s00259-014-2961-x"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1016\/0166-218x(92)90177-c"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.2967\/jnumed.115.159301"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1117\/12.2272946"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1088\/1361-6560\/ab3d07"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1090\/S0025-5718-1980-0572855-7"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/tmi.2017.2786865"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1137\/140954362"},{"key":"ref50","first-page":"249","article-title":"A linearly-convergent stochastic L-BFGS algorithm","volume-title":"Proc. 19th Int. Conf. Artif. Intell. Statist. (AISTATS)","author":"Moritz"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1002\/mp.13321"},{"key":"ref52","first-page":"685","article-title":"Barzilai-borwein step size for stochastic gradient descent","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Tan"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1109\/tmi.2014.2350962"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1088\/1361-6560\/ac71f1"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1088\/0031-9155\/56\/6\/011"},{"key":"ref56","first-page":"1","article-title":"Accelerated convergent motion compensated image reconstruction","volume-title":"Proc. IEEE Nucl. Sci. Symp. Med. Imag. Conf. (NSS\/MIC)","author":"Delplancke"}],"container-title":["IEEE Transactions on Medical Imaging"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/42\/10003062\/09872020.pdf?arnumber=9872020","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,2]],"date-time":"2024-03-02T06:11:33Z","timestamp":1709359893000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9872020\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,1]]},"references-count":56,"journal-issue":{"issue":"1"},"URL":"https:\/\/doi.org\/10.1109\/tmi.2022.3203237","relation":{},"ISSN":["0278-0062","1558-254X"],"issn-type":[{"value":"0278-0062","type":"print"},{"value":"1558-254X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,1]]}}}