{"id":"https://openalex.org/W3214032575","doi":"https://doi.org/10.1109/tmi.2022.3181813","title":"A Fast Convergent Ordered-Subsets Algorithm With Subiteration-Dependent Preconditioners for PET Image Reconstruction","display_name":"A Fast Convergent Ordered-Subsets Algorithm With Subiteration-Dependent Preconditioners for PET Image Reconstruction","publication_year":2022,"publication_date":"2022-06-09","ids":{"openalex":"https://openalex.org/W3214032575","doi":"https://doi.org/10.1109/tmi.2022.3181813","mag":"3214032575","pmid":"https://pubmed.ncbi.nlm.nih.gov/35679379"},"language":"en","primary_location":{"id":"doi:10.1109/tmi.2022.3181813","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmi.2022.3181813","pdf_url":null,"source":{"id":"https://openalex.org/S58069681","display_name":"IEEE Transactions on Medical Imaging","issn_l":"0278-0062","issn":["0278-0062","1558-254X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Medical Imaging","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/9810102","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5027986102","display_name":"Jianfeng Guo","orcid":"https://orcid.org/0000-0002-2527-9939"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jianfeng Guo","raw_affiliation_strings":["School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-2527-9939","affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011869870","display_name":"C. Ross Schmidtlein","orcid":"https://orcid.org/0000-0003-0485-3601"},"institutions":[{"id":"https://openalex.org/I1334819555","display_name":"Memorial Sloan Kettering Cancer Center","ror":"https://ror.org/02yrq0923","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I1334819555"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"C. Ross Schmidtlein","raw_affiliation_strings":["Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, USA"],"raw_orcid":"https://orcid.org/0000-0003-0485-3601","affiliations":[{"raw_affiliation_string":"Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, USA","institution_ids":["https://openalex.org/I1334819555"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042768449","display_name":"Andrzej Kr\u00f3l","orcid":"https://orcid.org/0000-0002-2669-4704"},"institutions":[{"id":"https://openalex.org/I20388574","display_name":"SUNY Upstate Medical University","ror":"https://ror.org/040kfrw16","country_code":"US","type":"education","lineage":["https://openalex.org/I20388574"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Andrzej Krol","raw_affiliation_strings":["Departments of Radiology and Pharmacology, SUNY Upstate Medical University, Syracuse, NY, USA"],"raw_orcid":"https://orcid.org/0000-0002-2669-4704","affiliations":[{"raw_affiliation_string":"Departments of Radiology and Pharmacology, SUNY Upstate Medical University, Syracuse, NY, USA","institution_ids":["https://openalex.org/I20388574"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100391306","display_name":"Si Li","orcid":"https://orcid.org/0000-0001-5590-7759"},"institutions":[{"id":"https://openalex.org/I139024713","display_name":"Guangdong University of Technology","ror":"https://ror.org/04azbjn80","country_code":"CN","type":"education","lineage":["https://openalex.org/I139024713"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Si Li","raw_affiliation_strings":["School of Computer Science and Technology, Guangdong University of Technology, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Guangdong University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I139024713"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077925676","display_name":"Yizun Lin","orcid":"https://orcid.org/0000-0003-1400-278X"},"institutions":[{"id":"https://openalex.org/I159948400","display_name":"Jinan University","ror":"https://ror.org/02xe5ns62","country_code":"CN","type":"education","lineage":["https://openalex.org/I159948400"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yizun Lin","raw_affiliation_strings":["Department of Mathematics, College of Information Science and Technology, Jinan University, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0003-1400-278X","affiliations":[{"raw_affiliation_string":"Department of Mathematics, College of Information Science and Technology, Jinan University, Guangzhou, China","institution_ids":["https://openalex.org/I159948400"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059008417","display_name":"Sangtae Ahn","orcid":"https://orcid.org/0000-0001-7252-2607"},"institutions":[{"id":"https://openalex.org/I4210134512","display_name":"GE Global Research (United States)","ror":"https://ror.org/03e06qt98","country_code":"US","type":"company","lineage":["https://openalex.org/I4210134512"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sangtae Ahn","raw_affiliation_strings":["GE Research, Niskayuna, NY, USA"],"raw_orcid":"https://orcid.org/0000-0001-7252-2607","affiliations":[{"raw_affiliation_string":"GE Research, Niskayuna, NY, USA","institution_ids":["https://openalex.org/I4210134512"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000434695","display_name":"C.W. Stearns","orcid":"https://orcid.org/0000-0002-7074-6663"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Charles Stearns","raw_affiliation_strings":["GE Healthcare, Waukesha, WI, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"GE Healthcare, Waukesha, WI, USA","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5026572582","display_name":"Yuesheng Xu","orcid":"https://orcid.org/0000-0003-3965-3087"},"institutions":[{"id":"https://openalex.org/I81365321","display_name":"Old Dominion University","ror":"https://ror.org/04zjtrb98","country_code":"US","type":"education","lineage":["https://openalex.org/I81365321"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yuesheng Xu","raw_affiliation_strings":["Department of Mathematics and Statistics, Old Dominion University, Norfolk, VA, USA"],"raw_orcid":"https://orcid.org/0000-0003-3965-3087","affiliations":[{"raw_affiliation_string":"Department of Mathematics and Statistics, Old Dominion University, Norfolk, VA, USA","institution_ids":["https://openalex.org/I81365321"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5027986102"],"corresponding_institution_ids":["https://openalex.org/I157773358"],"apc_list":null,"apc_paid":null,"fwci":0.8663,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.70111882,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"41","issue":"11","first_page":"3289","last_page":"3300"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10522","display_name":"Medical Imaging Techniques and Applications","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T10522","display_name":"Medical Imaging Techniques and Applications","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10378","display_name":"Advanced MRI Techniques and Applications","score":0.9980999827384949,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9962000250816345,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/preconditioner","display_name":"Preconditioner","score":0.8017957210540771},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.7201586365699768},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.6404669880867004},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5389173626899719},{"id":"https://openalex.org/keywords/iterative-reconstruction","display_name":"Iterative reconstruction","score":0.494973361492157},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.4351693391799927},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.41731345653533936},{"id":"https://openalex.org/keywords/expectation\u2013maximization-algorithm","display_name":"Expectation\u2013maximization algorithm","score":0.416110634803772},{"id":"https://openalex.org/keywords/iterative-method","display_name":"Iterative method","score":0.326913058757782},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.1702875792980194},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.07713577151298523}],"concepts":[{"id":"https://openalex.org/C167431342","wikidata":"https://www.wikidata.org/wiki/Q1754327","display_name":"Preconditioner","level":3,"score":0.8017957210540771},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.7201586365699768},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.6404669880867004},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5389173626899719},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.494973361492157},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.4351693391799927},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.41731345653533936},{"id":"https://openalex.org/C182081679","wikidata":"https://www.wikidata.org/wiki/Q1275153","display_name":"Expectation\u2013maximization algorithm","level":3,"score":0.416110634803772},{"id":"https://openalex.org/C159694833","wikidata":"https://www.wikidata.org/wiki/Q2321565","display_name":"Iterative method","level":2,"score":0.326913058757782},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.1702875792980194},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.07713577151298523},{"id":"https://openalex.org/C49781872","wikidata":"https://www.wikidata.org/wiki/Q1045555","display_name":"Maximum likelihood","level":2,"score":0.0}],"mesh":[{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D014057","descriptor_name":"Tomography, X-Ray Computed","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D014057","descriptor_name":"Tomography, X-Ray Computed","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D014057","descriptor_name":"Tomography, X-Ray Computed","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D019047","descriptor_name":"Phantoms, Imaging","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D019047","descriptor_name":"Phantoms, Imaging","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D019047","descriptor_name":"Phantoms, Imaging","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D049268","descriptor_name":"Positron-Emission Tomography","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D049268","descriptor_name":"Positron-Emission Tomography","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D049268","descriptor_name":"Positron-Emission Tomography","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":3,"locations":[{"id":"doi:10.1109/tmi.2022.3181813","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmi.2022.3181813","pdf_url":null,"source":{"id":"https://openalex.org/S58069681","display_name":"IEEE Transactions on Medical Imaging","issn_l":"0278-0062","issn":["0278-0062","1558-254X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Medical Imaging","raw_type":"journal-article"},{"id":"pmid:35679379","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/35679379","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on medical imaging","raw_type":null},{"id":"pmh:oai:pubmedcentral.nih.gov:9810102","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/9810102","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Trans Med Imaging","raw_type":"Text"}],"best_oa_location":{"id":"pmh:oai:pubmedcentral.nih.gov:9810102","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/9810102","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Trans Med Imaging","raw_type":"Text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2332028470","display_name":null,"funder_award_id":"11771464","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3238581596","display_name":null,"funder_award_id":"2022A1515012379","funder_id":"https://openalex.org/F4320321921","funder_display_name":"Natural Science Foundation of Guangdong Province"},{"id":"https://openalex.org/G5110314844","display_name":null,"funder_award_id":"P30 CA008748","funder_id":"https://openalex.org/F4320337351","funder_display_name":"National Cancer Institute"},{"id":"https://openalex.org/G6469444137","display_name":null,"funder_award_id":"R21CA263876","funder_id":"https://openalex.org/F4320337351","funder_display_name":"National Cancer Institute"},{"id":"https://openalex.org/G7015792876","display_name":null,"funder_award_id":"DMS-1912958","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G7223463451","display_name":null,"funder_award_id":"R21CA263876","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"},{"id":"https://openalex.org/G7564606733","display_name":null,"funder_award_id":"2021007","funder_id":"https://openalex.org/F4320330330","funder_display_name":"Guangdong Province Key Laboratory of Computational Science"},{"id":"https://openalex.org/G7795818187","display_name":null,"funder_award_id":"2021A1515110541","funder_id":"https://openalex.org/F4320337111","funder_display_name":"Basic and Applied Basic Research Foundation of Guangdong Province"},{"id":"https://openalex.org/G8094914596","display_name":null,"funder_award_id":"21620352","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321921","display_name":"Natural Science Foundation of Guangdong Province","ror":null},{"id":"https://openalex.org/F4320330330","display_name":"Guangdong Province Key Laboratory of Computational Science","ror":null},{"id":"https://openalex.org/F4320332161","display_name":"National Institutes of Health","ror":"https://ror.org/01cwqze88"},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null},{"id":"https://openalex.org/F4320337111","display_name":"Basic and Applied Basic Research Foundation of Guangdong Province","ror":null},{"id":"https://openalex.org/F4320337351","display_name":"National Cancer Institute","ror":"https://ror.org/040gcmg81"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":42,"referenced_works":["https://openalex.org/W186085407","https://openalex.org/W1511443099","https://openalex.org/W1568288633","https://openalex.org/W1647554959","https://openalex.org/W1967581593","https://openalex.org/W1970997001","https://openalex.org/W2000594266","https://openalex.org/W2005277084","https://openalex.org/W2017162022","https://openalex.org/W2036837878","https://openalex.org/W2045995543","https://openalex.org/W2048417186","https://openalex.org/W2052419043","https://openalex.org/W2069629287","https://openalex.org/W2075119726","https://openalex.org/W2092663520","https://openalex.org/W2100556411","https://openalex.org/W2103559027","https://openalex.org/W2109812509","https://openalex.org/W2124541940","https://openalex.org/W2128456478","https://openalex.org/W2130217200","https://openalex.org/W2135468550","https://openalex.org/W2139518045","https://openalex.org/W2154744699","https://openalex.org/W2154852444","https://openalex.org/W2160260190","https://openalex.org/W2221881442","https://openalex.org/W2496899299","https://openalex.org/W2609292681","https://openalex.org/W2776756710","https://openalex.org/W2888335855","https://openalex.org/W2900779353","https://openalex.org/W2903184369","https://openalex.org/W2918100930","https://openalex.org/W2936995161","https://openalex.org/W3104999358","https://openalex.org/W4255034812","https://openalex.org/W6607493213","https://openalex.org/W6636952455","https://openalex.org/W6682466571","https://openalex.org/W6761030284"],"related_works":["https://openalex.org/W4285325102","https://openalex.org/W2358739842","https://openalex.org/W2185794209","https://openalex.org/W2138831083","https://openalex.org/W1844423250","https://openalex.org/W2128367053","https://openalex.org/W2107386309","https://openalex.org/W2545869789","https://openalex.org/W2141090006","https://openalex.org/W1556040568"],"abstract_inverted_index":{"We":[0,133],"investigated":[1],"the":[2,26,31,40,55,61,64,67,76,99,107,136,147,165,170,192,216,220],"imaging":[3],"performance":[4],"of":[5,28,66,131,139,146,151,222],"a":[6,112,128,179,223],"fast":[7],"convergent":[8],"ordered-subsets":[9],"algorithm":[10],"with":[11,30,39,209],"subiteration-dependent":[12],"preconditioners":[13],"(SDPs)":[14],"for":[15,121],"positron":[16],"emission":[17],"tomography":[18],"(PET)":[19],"image":[20,227],"reconstruction.":[21],"In":[22],"particular,":[23],"we":[24,161,205],"considered":[25],"use":[27],"SDP":[29],"block":[32],"sequential":[33],"regularized":[34],"expectation":[35,114],"maximization":[36,115],"(BSREM)":[37],"approach":[38],"relative":[41,110],"difference":[42],"prior":[43,49],"(RDP)":[44],"regularizer":[45],"due":[46],"to":[47,94,111,175],"its":[48],"clinical":[50,158],"adaptation":[51],"by":[52,86,142],"vendors.":[53],"Because":[54],"RDP":[56],"regularization":[57],"promotes":[58],"smoothness":[59],"in":[60,69,82,98,106,190,207],"reconstructed":[62],"image,":[63],"directions":[65],"gradients":[68],"smooth":[70,100],"areas":[71,101,109],"more":[72],"accurately":[73],"point":[74],"toward":[75],"objective":[77,194],"function's":[78],"minimizer":[79],"than":[80,197,229],"those":[81],"variable":[83,108],"areas.":[84],"Motivated":[85],"this":[87],"observation,":[88],"two":[89],"SDPs":[90],"have":[91,134,162],"been":[92],"designed":[93],"increase":[95],"iteration":[96,104],"step-sizes":[97,105],"and":[102,157,178,200,212,232],"reduce":[103],"conventional":[113,176,198,230],"preconditioner.":[116,148],"The":[117],"momentum":[118],"technique":[119],"used":[120],"convergence":[122,138,171],"acceleration":[123],"can":[124],"be":[125],"viewed":[126],"as":[127,173,182],"special":[129],"case":[130],"SDP.":[132],"proved":[135],"global":[137],"SDP-BSREM":[140,166,185,217],"algorithms":[141,167,186,218],"assuming":[143],"certain":[144],"characteristics":[145],"By":[149],"means":[150],"numerical":[152],"experiments":[153],"using":[154],"both":[155],"simulated":[156],"PET":[159],"data,":[160],"shown":[163],"that":[164,215],"substantially":[168],"improve":[169],"rate,":[172],"compared":[174],"BSREM":[177,199,231],"vendor's":[180],"implementation":[181],"Q.Clear.":[183],"Specifically,":[184],"converge":[187],"35%-50%":[188],"faster":[189,228],"reaching":[191],"same":[193],"function":[195],"value":[196],"commercial":[201,233],"Q.Clear":[202,234],"algorithms.":[203,235],"Moreover,":[204],"showed":[206],"phantoms":[208],"hot,":[210],"cold":[211],"background":[213],"regions":[214],"approached":[219],"values":[221],"highly":[224],"converged":[225],"reference":[226]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
