{"id":"https://openalex.org/W1517161638","doi":"https://doi.org/10.1109/isbi.2015.7164085","title":"Theoretical analysis of lesion detectability in penalized maximum-likelihood patlak parametric image reconstruction using dynamic PET","display_name":"Theoretical analysis of lesion detectability in penalized maximum-likelihood patlak parametric image reconstruction using dynamic PET","publication_year":2015,"publication_date":"2015-04-01","ids":{"openalex":"https://openalex.org/W1517161638","doi":"https://doi.org/10.1109/isbi.2015.7164085","mag":"1517161638"},"language":"en","primary_location":{"id":"doi:10.1109/isbi.2015.7164085","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi.2015.7164085","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"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/A5101712357","display_name":"Li Yang","orcid":"https://orcid.org/0000-0001-6741-6658"},"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":"Li Yang","raw_affiliation_strings":["Department of Biomedical Engineering, University of California, Davis, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Biomedical Engineering, University of California, Davis, CA, USA","institution_ids":["https://openalex.org/I84218800"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057150859","display_name":"Guobao Wang","orcid":"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, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Biomedical Engineering, University of California, Davis, CA, USA","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"},"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":"Jinyi Qi","raw_affiliation_strings":["Department of Biomedical Engineering, University of California, Davis, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Biomedical Engineering, University of California, Davis, CA, USA","institution_ids":["https://openalex.org/I84218800"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I84218800"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1188","last_page":"1191"},"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":0.9988999962806702,"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/T10378","display_name":"Advanced MRI Techniques and Applications","score":0.9933000206947327,"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/iterative-reconstruction","display_name":"Iterative reconstruction","score":0.7213572859764099},{"id":"https://openalex.org/keywords/parametric-statistics","display_name":"Parametric statistics","score":0.6767145991325378},{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.6327071189880371},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.5358551740646362},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4736819565296173},{"id":"https://openalex.org/keywords/reconstruction-algorithm","display_name":"Reconstruction algorithm","score":0.4470250904560089},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.44395753741264343},{"id":"https://openalex.org/keywords/positron-emission-tomography","display_name":"Positron emission tomography","score":0.426113098859787},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4069393277168274},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.38875648379325867},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3462543487548828},{"id":"https://openalex.org/keywords/nuclear-medicine","display_name":"Nuclear medicine","score":0.3042812943458557},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.13871100544929504},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.09723824262619019}],"concepts":[{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.7213572859764099},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.6767145991325378},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.6327071189880371},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.5358551740646362},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4736819565296173},{"id":"https://openalex.org/C2779898584","wikidata":"https://www.wikidata.org/wiki/Q7820109","display_name":"Reconstruction algorithm","level":3,"score":0.4470250904560089},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44395753741264343},{"id":"https://openalex.org/C2775842073","wikidata":"https://www.wikidata.org/wiki/Q208376","display_name":"Positron emission tomography","level":2,"score":0.426113098859787},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4069393277168274},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.38875648379325867},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3462543487548828},{"id":"https://openalex.org/C2989005","wikidata":"https://www.wikidata.org/wiki/Q214963","display_name":"Nuclear medicine","level":1,"score":0.3042812943458557},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.13871100544929504},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.09723824262619019}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isbi.2015.7164085","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi.2015.7164085","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11","score":0.6899999976158142}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W1975979438","https://openalex.org/W1982098879","https://openalex.org/W2059350395","https://openalex.org/W2068668125","https://openalex.org/W2078913455","https://openalex.org/W2079434336","https://openalex.org/W2098217486","https://openalex.org/W2116198402","https://openalex.org/W2156612134","https://openalex.org/W2160260190"],"related_works":["https://openalex.org/W4386634531","https://openalex.org/W2077694017","https://openalex.org/W2087312114","https://openalex.org/W2031629850","https://openalex.org/W2031832834","https://openalex.org/W2055365636","https://openalex.org/W2077148454","https://openalex.org/W2753113106","https://openalex.org/W2901124942","https://openalex.org/W2537408670"],"abstract_inverted_index":{"Detecting":[0],"cancerous":[1],"lesion":[2,23,129,141,159,198],"is":[3,110,164],"a":[4,66,122],"major":[5],"clinical":[6],"application":[7],"in":[8,25,112,131,193],"emission":[9],"tomography.":[10],"In":[11,56,85],"previous":[12],"work,":[13],"we":[14,29],"have":[15,143],"studied":[16],"penalized":[17],"maximum-likelihood":[18],"(PML)":[19],"image":[20,54,105],"reconstruction":[21,37,47,50,106,109,118,196],"for":[22,51,138,197],"detection":[24],"static":[26,35],"PET.":[27,40],"Here":[28],"extend":[30],"our":[31],"theoretical":[32,174,183],"analysis":[33,77],"of":[34,68,151,189],"PET":[36,70,195],"to":[38,127,148,156],"dynamic":[39,69,194],"We":[41,120],"study":[42],"both":[43,113],"the":[44,79,100,104,114,132,140,149,152,158,187,190],"conventional":[45],"indirect":[46,57,115],"and":[48,73,116,146,176],"direct":[49,86,117,191],"Patlak":[52,59,76,88,101,133],"parametric":[53,60,89],"estimation.":[55],"reconstruction,":[58,87],"images":[61,71,90],"are":[62,91,180],"generated":[63],"by":[64,98],"reconstructing":[65],"sequence":[67],"first":[72],"then":[74],"performing":[75],"on":[78],"time":[80],"activity":[81],"curves":[82],"(TACs)":[83],"pixel-by-pixel.":[84],"estimated":[92],"directly":[93],"from":[94],"raw":[95],"sinogram":[96],"data":[97],"incorporating":[99],"model":[102],"into":[103],"procedure.":[107],"PML":[108],"used":[111],"methods.":[119],"use":[121],"channelized":[123],"Hotelling":[124],"observer":[125],"(CHO)":[126],"assess":[128],"detectability":[130,142],"slope":[134],"image.":[135],"Simplified":[136],"expressions":[137],"evaluating":[139],"been":[144],"derived":[145],"applied":[147],"selection":[150],"regularization":[153],"parameter":[154],"value":[155],"maximize":[157],"detectability.":[160],"The":[161,182],"proposed":[162],"method":[163,192],"validated":[165],"using":[166],"computer-based":[167],"Monte":[168,177],"Carlo":[169,178],"simulation.":[170],"Good":[171],"agreements":[172],"between":[173],"predictions":[175],"results":[179],"observed.":[181],"formula":[184],"also":[185],"shows":[186],"benefit":[188],"detection.":[199]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}