{"id":"https://openalex.org/W1984459542","doi":"https://doi.org/10.1109/jstsp.2012.2237380","title":"Anomaly Detection and Artifact Recovery in PET Attenuation-Correction Images Using the Likelihood Function","display_name":"Anomaly Detection and Artifact Recovery in PET Attenuation-Correction Images Using the Likelihood Function","publication_year":2013,"publication_date":"2013-01-01","ids":{"openalex":"https://openalex.org/W1984459542","doi":"https://doi.org/10.1109/jstsp.2012.2237380","mag":"1984459542","pmid":"https://pubmed.ncbi.nlm.nih.gov/24198866"},"language":"en","primary_location":{"id":"doi:10.1109/jstsp.2012.2237380","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jstsp.2012.2237380","pdf_url":null,"source":{"id":"https://openalex.org/S42167783","display_name":"IEEE Journal of Selected Topics in Signal Processing","issn_l":"1932-4553","issn":["1932-4553","1941-0484"],"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 Journal of Selected Topics in Signal Processing","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/3815546","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5011455214","display_name":"Charles M. Laymon","orcid":"https://orcid.org/0000-0002-5966-7219"},"institutions":[{"id":"https://openalex.org/I170201317","display_name":"University of Pittsburgh","ror":"https://ror.org/01an3r305","country_code":"US","type":"education","lineage":["https://openalex.org/I170201317"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Charles M. Laymon","raw_affiliation_strings":["Department of Radiology, University of Pittsburgh, Pittsburgh, PA, 15213 USA","Dept. of Radiol., Univ. of Pittsburgh, Pittsburgh, PA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Radiology, University of Pittsburgh, Pittsburgh, PA, 15213 USA","institution_ids":["https://openalex.org/I170201317"]},{"raw_affiliation_string":"Dept. of Radiol., Univ. of Pittsburgh, Pittsburgh, PA, USA","institution_ids":["https://openalex.org/I170201317"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5018434836","display_name":"J.E. Bowsher","orcid":null},"institutions":[{"id":"https://openalex.org/I170897317","display_name":"Duke University","ror":"https://ror.org/00py81415","country_code":"US","type":"education","lineage":["https://openalex.org/I170897317"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"James E. Bowsher","raw_affiliation_strings":["Department of Radiation Oncology, Duke University, Durham, NC, USA","Dept. of Radiat. Oncology, Duke Univ., Durham, NC, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Radiation Oncology, Duke University, Durham, NC, USA","institution_ids":["https://openalex.org/I170897317"]},{"raw_affiliation_string":"Dept. of Radiat. Oncology, Duke Univ., Durham, NC, USA","institution_ids":["https://openalex.org/I170897317"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.08756644,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"7","issue":"1","first_page":"137","last_page":"146"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10522","display_name":"Medical Imaging Techniques and Applications","score":1.0,"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":1.0,"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/T12386","display_name":"Advanced X-ray and CT Imaging","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.9911999702453613,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/attenuation","display_name":"Attenuation","score":0.8283286094665527},{"id":"https://openalex.org/keywords/statistical-noise","display_name":"Statistical noise","score":0.6677600145339966},{"id":"https://openalex.org/keywords/correction-for-attenuation","display_name":"Correction for attenuation","score":0.6632274985313416},{"id":"https://openalex.org/keywords/iterative-reconstruction","display_name":"Iterative reconstruction","score":0.6627112030982971},{"id":"https://openalex.org/keywords/artifact","display_name":"Artifact (error)","score":0.6566698551177979},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6550614833831787},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5764222741127014},{"id":"https://openalex.org/keywords/image-quality","display_name":"Image quality","score":0.5735776424407959},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5109645128250122},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4958556592464447},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4502347409725189},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4401931166648865},{"id":"https://openalex.org/keywords/contrast","display_name":"Contrast (vision)","score":0.42882195115089417},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.35175085067749023},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.27512896060943604},{"id":"https://openalex.org/keywords/optics","display_name":"Optics","score":0.21980801224708557}],"concepts":[{"id":"https://openalex.org/C184652730","wikidata":"https://www.wikidata.org/wiki/Q2357982","display_name":"Attenuation","level":2,"score":0.8283286094665527},{"id":"https://openalex.org/C128197687","wikidata":"https://www.wikidata.org/wiki/Q5477515","display_name":"Statistical noise","level":2,"score":0.6677600145339966},{"id":"https://openalex.org/C123688308","wikidata":"https://www.wikidata.org/wiki/Q7309537","display_name":"Correction for attenuation","level":3,"score":0.6632274985313416},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.6627112030982971},{"id":"https://openalex.org/C2779010991","wikidata":"https://www.wikidata.org/wiki/Q2720909","display_name":"Artifact (error)","level":2,"score":0.6566698551177979},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6550614833831787},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5764222741127014},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.5735776424407959},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5109645128250122},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4958556592464447},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4502347409725189},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4401931166648865},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.42882195115089417},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.35175085067749023},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.27512896060943604},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.21980801224708557},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/jstsp.2012.2237380","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jstsp.2012.2237380","pdf_url":null,"source":{"id":"https://openalex.org/S42167783","display_name":"IEEE Journal of Selected Topics in Signal Processing","issn_l":"1932-4553","issn":["1932-4553","1941-0484"],"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 Journal of Selected Topics in Signal Processing","raw_type":"journal-article"},{"id":"pmid:24198866","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/24198866","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 journal of selected topics in signal processing","raw_type":null},{"id":"pmh:oai:europepmc.org:2895353","is_oa":false,"landing_page_url":"http://europepmc.org/articles/PMC3815546","pdf_url":null,"source":{"id":"https://openalex.org/S4306400806","display_name":"Europe PMC (PubMed Central)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1303153112","host_organization_name":"European Bioinformatics Institute","host_organization_lineage":["https://openalex.org/I1303153112"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Text"},{"id":"pmh:oai:pubmedcentral.nih.gov:3815546","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/3815546","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 J Sel Top Signal Process","raw_type":"Text"}],"best_oa_location":{"id":"pmh:oai:pubmedcentral.nih.gov:3815546","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/3815546","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 J Sel Top Signal Process","raw_type":"Text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1580906815","display_name":null,"funder_award_id":"R21 CA156390","funder_id":"https://openalex.org/F4320337351","funder_display_name":"National Cancer Institute"},{"id":"https://openalex.org/G212930918","display_name":null,"funder_award_id":"U01 CA140230","funder_id":"https://openalex.org/F4320337351","funder_display_name":"National Cancer Institute"},{"id":"https://openalex.org/G2208054141","display_name":null,"funder_award_id":"P30 CA047904","funder_id":"https://openalex.org/F4320337351","funder_display_name":"National Cancer Institute"},{"id":"https://openalex.org/G5679947646","display_name":null,"funder_award_id":"R21 EB002622","funder_id":"https://openalex.org/F4320337363","funder_display_name":"National Institute of Biomedical Imaging and Bioengineering"}],"funders":[{"id":"https://openalex.org/F4320337351","display_name":"National Cancer Institute","ror":"https://ror.org/040gcmg81"},{"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":43,"referenced_works":["https://openalex.org/W1851068779","https://openalex.org/W1973637080","https://openalex.org/W1975700082","https://openalex.org/W2014362992","https://openalex.org/W2016346232","https://openalex.org/W2032237670","https://openalex.org/W2033932611","https://openalex.org/W2039010573","https://openalex.org/W2044387665","https://openalex.org/W2057770669","https://openalex.org/W2069629287","https://openalex.org/W2085670599","https://openalex.org/W2089221057","https://openalex.org/W2098628112","https://openalex.org/W2099676413","https://openalex.org/W2100686817","https://openalex.org/W2106470093","https://openalex.org/W2108248984","https://openalex.org/W2110733023","https://openalex.org/W2111203235","https://openalex.org/W2112155856","https://openalex.org/W2120975014","https://openalex.org/W2126200084","https://openalex.org/W2126639779","https://openalex.org/W2128585362","https://openalex.org/W2141991262","https://openalex.org/W2145537745","https://openalex.org/W2147492557","https://openalex.org/W2149465693","https://openalex.org/W2152494830","https://openalex.org/W2152908363","https://openalex.org/W2154744699","https://openalex.org/W2155830965","https://openalex.org/W2158287255","https://openalex.org/W2160260190","https://openalex.org/W2164818482","https://openalex.org/W2165399609","https://openalex.org/W2166887721","https://openalex.org/W2491092337","https://openalex.org/W2534113654","https://openalex.org/W2734739839","https://openalex.org/W6638881104","https://openalex.org/W6740784950"],"related_works":["https://openalex.org/W2077298793","https://openalex.org/W2951714568","https://openalex.org/W1988158806","https://openalex.org/W1963814553","https://openalex.org/W2037595954","https://openalex.org/W2507293823","https://openalex.org/W2056742148","https://openalex.org/W2386146599","https://openalex.org/W2757389719","https://openalex.org/W2158348405"],"abstract_inverted_index":{"In":[0,156],"dual":[1],"modality":[2],"PET/CT,":[3],"CT":[4,26,58],"data":[5,207],"are":[6,208],"used":[7],"to":[8,55,67,92,108,210],"generate":[9],"the":[10,15,18,25,41,46,57,74,80,83,93,114,119,139,160,163,188,192],"attenuation":[11,31,77,88,115,147,154],"correction":[12],"applied":[13],"in":[14,69,149,196],"reconstruction":[16],"of":[17,43,82,162,170,184],"PET":[19,84,96,120],"emission":[20,85,97,121],"image.":[21,155],"This":[22],"requires":[23],"converting":[24],"image":[27,98],"into":[28],"a":[29,157,182],"511-keV":[30,76],"map.":[32],"Algorithms":[33],"for":[34,126,177],"making":[35],"this":[36,110],"transformation":[37],"require":[38],"assumptions":[39],"about":[40],"makeup":[42],"material":[44,49],"within":[45],"patient.":[47],"Anomalous":[48],"such":[50],"as":[51,145,165,181],"contrast":[52,130,142],"agent":[53],"administered":[54],"enhance":[56],"scan":[59],"confounds":[60],"conversion":[61],"algorithms":[62],"and":[63,99,128,134,191],"has":[64],"been":[65],"observed":[66],"result":[68],"inaccuracies,":[70],"i.e.":[71],"inconsistencies":[72],"with":[73,198,205],"true":[75],"present":[78],"at":[79],"time":[81],"scan.":[86],"These":[87],"artifacts":[89,131,143],"carry":[90],"through":[91],"final":[94],"attenuation-corrected":[95],"can":[100],"resemble":[101],"diseased":[102],"tissue.":[103],"We":[104],"propose":[105],"an":[106,150,166],"approach":[107],"correcting":[109,129],"problem":[111],"that":[112,141],"employs":[113],"information":[116],"carried":[117],"by":[118],"data.":[122,200],"A":[123],"likelihood-based":[124],"algorithm":[125,137,190],"identifying":[127],"is":[132,174],"presented":[133],"tested.":[135],"The":[136],"exploits":[138],"fact":[140],"manifest":[144],"too-high":[146],"values":[148],"otherwise":[151],"high":[152],"quality":[153],"separate":[158],"study,":[159],"performance":[161],"loglikelihood":[164,193],"objective-function":[167],"component,":[168],"independent":[169],"any":[171],"particular":[172],"algorithm,":[173],"mapped":[175],"out":[176],"several":[178],"imaging":[179],"scenarios":[180],"function":[183],"statistical":[185],"noise.":[186],"Both":[187],"full":[189],"performed":[194],"well":[195],"studies":[197,202],"simulated":[199],"Additional":[201],"including":[203],"those":[204],"patient":[206],"required":[209],"fully":[211],"understand":[212],"their":[213],"capabilities":[214],".":[215]},"counts_by_year":[{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":2}],"updated_date":"2026-01-13T01:12:25.745995","created_date":"2025-10-10T00:00:00"}
