{"id":"https://openalex.org/W1975979438","doi":"https://doi.org/10.1088/0031-9155/53/3/006","title":"Maximuma posteriorireconstruction of the Patlak parametric image from sinograms in dynamic PET","display_name":"Maximuma posteriorireconstruction of the Patlak parametric image from sinograms in dynamic PET","publication_year":2008,"publication_date":"2008-01-10","ids":{"openalex":"https://openalex.org/W1975979438","doi":"https://doi.org/10.1088/0031-9155/53/3/006","mag":"1975979438","pmid":"https://pubmed.ncbi.nlm.nih.gov/18199904"},"language":"en","primary_location":{"id":"doi:10.1088/0031-9155/53/3/006","doi":"https://doi.org/10.1088/0031-9155/53/3/006","is_oa":false,"landing_page_url":"https://doi.org/10.1088/0031-9155/53/3/006","pdf_url":null,"source":{"id":"https://openalex.org/S20241394","display_name":"Physics in Medicine and Biology","issn_l":"0031-9155","issn":["0031-9155","1361-6560"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","dongbi-d","doyens","jufo-2","ki-jl-1","medline","norway-1","poland-100","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310320083","host_organization_name":"IOP Publishing","host_organization_lineage":["https://openalex.org/P4310320083","https://openalex.org/P4310311669"],"host_organization_lineage_names":["IOP Publishing","Institute of Physics"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Physics in Medicine and Biology","raw_type":"journal-article"},"volume":null,"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5057150859","display_name":"Guobao Wang","orcid":"https://orcid.org/0000-0001-6526-1533","observed_orcids":["https://orcid.org/0000-0001-6526-1533"]},"institutions":[{"id":"https://openalex.org/I84218800","display_name":"University of California, Davis","ror":"https://ror.org/05rrcem69","country_code":"US","type":"education","lineage":["https://openalex.org/I84218800"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Guobao Wang","raw_affiliation_strings":["Department of Biomedical Engineering, University of California, Davis, CA 95616, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Biomedical Engineering, University of California, Davis, CA 95616, USA","institution_ids":["https://openalex.org/I84218800"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079645279","display_name":"Lin Fu","orcid":"https://orcid.org/0000-0002-9368-8881","observed_orcids":["https://orcid.org/0000-0002-9368-8881"]},"institutions":[{"id":"https://openalex.org/I84218800","display_name":"University of California, Davis","ror":"https://ror.org/05rrcem69","country_code":"US","type":"education","lineage":["https://openalex.org/I84218800"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Lin Fu","raw_affiliation_strings":["University of California at Davis"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of California at Davis","institution_ids":["https://openalex.org/I84218800"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5010514255","display_name":"Jinyi Qi","orcid":"https://orcid.org/0000-0002-5428-0322","observed_orcids":["https://orcid.org/0000-0002-5428-0322"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jinyi Qi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":3325,"currency":"USD","value_usd":3325},"apc_paid":null,"fwci":6.7908,"has_fulltext":false,"cited_by_count":84,"citation_normalized_percentile":{"value":0.96976922,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":88,"max":99},"biblio":{"volume":"53","issue":"3","first_page":"593","last_page":"604"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10522","display_name":"Medical Imaging Techniques and Applications","score":0.9994999766349792,"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":0.9994999766349792,"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/T10688","display_name":"Image and Signal Denoising Methods","score":9.999999747378752e-05,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11205","display_name":"Numerical methods in inverse problems","score":0.0,"subfield":{"id":"https://openalex.org/subfields/2610","display_name":"Mathematical Physics"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/patlak-graphical-analysis","display_name":"Patlak graphical analysis","score":0.8040000200271606},{"id":"https://openalex.org/keywords/parametric-image-reconstruction","display_name":"parametric image reconstruction","score":0.8799999952316284},{"id":"https://openalex.org/keywords/dynamic-pet","display_name":"dynamic PET","score":0.7770000100135803},{"id":"https://openalex.org/keywords/maximum-a-posteriori-estimation","display_name":"maximum a posteriori estimation","score":0.8740000128746033},{"id":"https://openalex.org/keywords/bayesian-reconstruction","display_name":"Bayesian reconstruction","score":0.6830000281333923},{"id":"https://openalex.org/keywords/preconditioned-conjugate-gradient-method","display_name":"preconditioned conjugate gradient","score":0.8479999899864197},{"id":"https://openalex.org/keywords/time-activity-curves","display_name":"time-activity curves","score":0.7239999771118164},{"id":"https://openalex.org/keywords/small-animal-pet","display_name":"small animal PET","score":0.7279999852180481}],"concepts":[{"id":"https://openalex.org/C9810830","wikidata":"https://www.wikidata.org/wiki/Q635384","display_name":"Maximum a posteriori estimation","level":3,"score":0.7188500165939331},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.6026424765586853},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5260676741600037},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5056629180908203},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.484418660402298},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.44593971967697144},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.44544166326522827},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3964313864707947},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.39231523871421814},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.34798598289489746},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3142928183078766},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.13592752814292908},{"id":"https://openalex.org/C49781872","wikidata":"https://www.wikidata.org/wiki/Q1045555","display_name":"Maximum likelihood","level":2,"score":0.0726935863494873}],"mesh":[{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000818","descriptor_name":"Animals","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001921","descriptor_name":"Brain","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":true},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D007089","descriptor_name":"Image Enhancement","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D007090","descriptor_name":"Image Interpretation, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D012680","descriptor_name":"Sensitivity and Specificity","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D015203","descriptor_name":"Reproducibility of Results","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016013","descriptor_name":"Likelihood Functions","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":"D021621","descriptor_name":"Imaging, Three-Dimensional","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D049268","descriptor_name":"Positron-Emission Tomography","qualifier_ui":"Q000295","qualifier_name":"instrumentation","is_major_topic":false},{"descriptor_ui":"D049268","descriptor_name":"Positron-Emission Tomography","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D051379","descriptor_name":"Mice","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":2,"locations":[{"id":"doi:10.1088/0031-9155/53/3/006","doi":"https://doi.org/10.1088/0031-9155/53/3/006","is_oa":false,"landing_page_url":"https://doi.org/10.1088/0031-9155/53/3/006","pdf_url":null,"source":{"id":"https://openalex.org/S20241394","display_name":"Physics in Medicine and Biology","issn_l":"0031-9155","issn":["0031-9155","1361-6560"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","dongbi-d","doyens","jufo-2","ki-jl-1","medline","norway-1","poland-100","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310320083","host_organization_name":"IOP Publishing","host_organization_lineage":["https://openalex.org/P4310320083","https://openalex.org/P4310311669"],"host_organization_lineage_names":["IOP Publishing","Institute of Physics"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Physics in Medicine and Biology","raw_type":"journal-article"},{"id":"pmid:18199904","doi":null,"is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/18199904","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,"listed_in":[],"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":"Physics in medicine and biology","raw_type":"Evaluation Study"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[{"id":"https://openalex.org/G4331661095","display_name":"Optimization of PET Imaging","funder_award_id":"R01EB000194","funder_id":"https://openalex.org/F4320337363","funder_display_name":"National Institute of Biomedical Imaging and Bioengineering"}],"funders":[{"id":"https://openalex.org/F4320332161","display_name":"National Institutes of Health","ror":"https://ror.org/01cwqze88"},{"id":"https://openalex.org/F4320337363","display_name":"National Institute of Biomedical Imaging and Bioengineering","ror":"https://ror.org/00372qc85"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W161293699","https://openalex.org/W1796663898","https://openalex.org/W1907188474","https://openalex.org/W1963934004","https://openalex.org/W1982039560","https://openalex.org/W1982980803","https://openalex.org/W1996001296","https://openalex.org/W2009564280","https://openalex.org/W2025773263","https://openalex.org/W2047015463","https://openalex.org/W2051228374","https://openalex.org/W2058032697","https://openalex.org/W2084090004","https://openalex.org/W2092078486","https://openalex.org/W2097398381","https://openalex.org/W2100177742","https://openalex.org/W2101301278","https://openalex.org/W2103037384","https://openalex.org/W2105467440","https://openalex.org/W2108724455","https://openalex.org/W2131706886","https://openalex.org/W2134130504","https://openalex.org/W2147067144","https://openalex.org/W2153172062","https://openalex.org/W2155574073","https://openalex.org/W2163794208","https://openalex.org/W2164562550","https://openalex.org/W2329652406"],"related_works":["https://openalex.org/W2150136752","https://openalex.org/W3165339207","https://openalex.org/W2966724615","https://openalex.org/W2119103933","https://openalex.org/W2037187667","https://openalex.org/W1532994760","https://openalex.org/W2028886014","https://openalex.org/W2307061571","https://openalex.org/W2101301278","https://openalex.org/W2112046912"],"abstract_inverted_index":{"Parametric":[0],"imaging":[1],"using":[2],"the":[3,38,50,56,65,93,98,111,125,130,142,149,171,174,180,190,196,202,212],"Patlak":[4,18,34,66,83,94,172],"graphical":[5,35],"method":[6,80,119,151,176,204,217],"has":[7,218],"been":[8,219],"widely":[9],"used":[10,108,169],"to":[11,48,70,109,154,188,221],"analyze":[12],"dynamic":[13,28,159,166,222],"PET":[14,135,225],"data.":[15],"Conventionally":[16],"a":[17,25,78,113,207,228],"parametric":[19,84,213],"image":[20,99],"is":[21,45,61,107,120,152,177],"generated":[22],"by":[23,91],"reconstructing":[24,82],"sequence":[26],"of":[27,148,157,211],"images":[29,85],"first":[30],"and":[31],"then":[32],"performing":[33],"analysis":[36],"on":[37],"time-activity":[39],"curves":[40],"pixel-by-pixel.":[41],"However,":[42],"because":[43,129],"it":[44],"rather":[46],"difficult":[47],"model":[49,96],"noise":[51,59,132],"distribution":[52,133],"in":[53,64,134,141,170,206],"reconstructed":[54],"images,":[55],"spatially":[57],"variant":[58],"correlation":[60],"simply":[62],"ignored":[63],"analysis,":[67,173],"which":[68],"leads":[69],"sub-optimal":[71],"results.":[72],"In":[73],"this":[74],"paper":[75],"we":[76],"present":[77],"Bayesian":[79],"for":[81],"directly":[86],"from":[87,227],"raw":[88],"sinogram":[89],"data":[90,136,226],"incorporating":[92],"plot":[95],"into":[97],"reconstruction":[100,155],"procedure.":[101],"A":[102],"preconditioned":[103],"conjugate":[104],"gradient":[105],"algorithm":[106],"find":[110],"maximum":[112],"posteriori":[114],"solution.":[115],"The":[116,145,215],"proposed":[117,191,203,216],"direct":[118,143,150,175,192],"statistically":[121],"more":[122,163,208],"efficient":[123],"than":[124,164,179],"conventional":[126,181,197],"indirect":[127,182,198],"approach":[128,199],"Poisson":[131],"can":[137],"be":[138],"accurately":[139],"modeled":[140],"reconstruction.":[144],"computation":[146],"cost":[147],"similar":[153],"time":[156],"two":[158,165],"frames.":[160],"Therefore,":[161],"when":[162],"frames":[167],"are":[168],"faster":[178],"approach.":[183],"We":[184],"conduct":[185],"computer":[186],"simulations":[187],"validate":[189],"method.":[193],"Comparisons":[194],"with":[195],"show":[200],"that":[201],"results":[205],"accurate":[209],"estimate":[210],"image.":[214],"applied":[220],"fully":[223],"3D":[224],"microPET":[229],"scanner.":[230]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":3},{"year":2015,"cited_by_count":7},{"year":2014,"cited_by_count":9},{"year":2013,"cited_by_count":6},{"year":2012,"cited_by_count":7}],"updated_date":"2026-11-04T10:54:05.112534","created_date":"2016-06-24T00:00:00"}