{"id":"https://openalex.org/W3209702343","doi":"https://doi.org/10.1117/12.2611292","title":"3D PET image generation with tumour masks using TGAN","display_name":"3D PET image generation with tumour masks using TGAN","publication_year":2022,"publication_date":"2022-03-31","ids":{"openalex":"https://openalex.org/W3209702343","doi":"https://doi.org/10.1117/12.2611292","mag":"3209702343"},"language":"en","primary_location":{"id":"doi:10.1117/12.2611292","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2611292","pdf_url":null,"source":{"id":"https://openalex.org/S4363607561","display_name":"Medical Imaging 2022: Image Processing","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Medical Imaging 2022: Image Processing","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2111.01866","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5014456325","display_name":"Robert V. Bergen","orcid":"https://orcid.org/0000-0002-3195-9746"},"institutions":[{"id":"https://openalex.org/I141945490","display_name":"University of British Columbia","ror":"https://ror.org/03rmrcq20","country_code":"CA","type":"education","lineage":["https://openalex.org/I141945490"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Robert V. Bergen","raw_affiliation_strings":["The Univ. of British Columbia (Canada)"],"affiliations":[{"raw_affiliation_string":"The Univ. of British Columbia (Canada)","institution_ids":["https://openalex.org/I141945490"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050095981","display_name":"Jean-Fran\u00e7ois Rajotte","orcid":"https://orcid.org/0000-0003-1615-6598"},"institutions":[{"id":"https://openalex.org/I141945490","display_name":"University of British Columbia","ror":"https://ror.org/03rmrcq20","country_code":"CA","type":"education","lineage":["https://openalex.org/I141945490"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Jean-Francois Rajotte","raw_affiliation_strings":["The Univ. of British Columbia (Canada)"],"affiliations":[{"raw_affiliation_string":"The Univ. of British Columbia (Canada)","institution_ids":["https://openalex.org/I141945490"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058744346","display_name":"Fereshteh Yousefirizi","orcid":"https://orcid.org/0000-0001-5261-6163"},"institutions":[{"id":"https://openalex.org/I141945490","display_name":"University of British Columbia","ror":"https://ror.org/03rmrcq20","country_code":"CA","type":"education","lineage":["https://openalex.org/I141945490"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Fereshteh Yousefirizi","raw_affiliation_strings":["BC Cancer Research Institute (Canada)","The Univ. of British Columbia (Canada)"],"affiliations":[{"raw_affiliation_string":"BC Cancer Research Institute (Canada)","institution_ids":[]},{"raw_affiliation_string":"The Univ. of British Columbia (Canada)","institution_ids":["https://openalex.org/I141945490"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062612986","display_name":"Ivan S. Klyuzhin","orcid":"https://orcid.org/0000-0003-0141-7628"},"institutions":[{"id":"https://openalex.org/I141945490","display_name":"University of British Columbia","ror":"https://ror.org/03rmrcq20","country_code":"CA","type":"education","lineage":["https://openalex.org/I141945490"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Ivan S. Klyuzhin","raw_affiliation_strings":["BC Cancer Research Institute (Canada)","The Univ. of British Columbia (Canada)"],"affiliations":[{"raw_affiliation_string":"BC Cancer Research Institute (Canada)","institution_ids":[]},{"raw_affiliation_string":"The Univ. of British Columbia (Canada)","institution_ids":["https://openalex.org/I141945490"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021438906","display_name":"Arman Rahmim","orcid":"https://orcid.org/0000-0002-9980-2403"},"institutions":[{"id":"https://openalex.org/I141945490","display_name":"University of British Columbia","ror":"https://ror.org/03rmrcq20","country_code":"CA","type":"education","lineage":["https://openalex.org/I141945490"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Arman Rahmim","raw_affiliation_strings":["BC Cancer Research Institute (Canada)","The Univ. of British Columbia (Canada)"],"affiliations":[{"raw_affiliation_string":"BC Cancer Research Institute (Canada)","institution_ids":[]},{"raw_affiliation_string":"The Univ. of British Columbia (Canada)","institution_ids":["https://openalex.org/I141945490"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5113567130","display_name":"Raymond T. Ng","orcid":"https://orcid.org/0000-0003-3692-8524"},"institutions":[{"id":"https://openalex.org/I141945490","display_name":"University of British Columbia","ror":"https://ror.org/03rmrcq20","country_code":"CA","type":"education","lineage":["https://openalex.org/I141945490"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Raymond T. Ng","raw_affiliation_strings":["The Univ. of British Columbia (Canada)"],"affiliations":[{"raw_affiliation_string":"The Univ. of British Columbia (Canada)","institution_ids":["https://openalex.org/I141945490"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5014456325"],"corresponding_institution_ids":["https://openalex.org/I141945490"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.00268456,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"88","issue":null,"first_page":"58","last_page":"58"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.9986000061035156,"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/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.9986000061035156,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9983999729156494,"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/T10862","display_name":"AI in cancer detection","score":0.9975000023841858,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7319216728210449},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6894481778144836},{"id":"https://openalex.org/keywords/synthetic-data","display_name":"Synthetic data","score":0.6503215432167053},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6430755853652954},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5766968131065369},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.5632674694061279},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5455167293548584},{"id":"https://openalex.org/keywords/generator","display_name":"Generator (circuit theory)","score":0.5388997793197632},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5093444585800171},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.48898112773895264},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4693912863731384},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.46186381578445435},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4383418560028076},{"id":"https://openalex.org/keywords/dice","display_name":"Dice","score":0.41509774327278137},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.19340091943740845},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.16139161586761475},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.08607146143913269}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7319216728210449},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6894481778144836},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.6503215432167053},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6430755853652954},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5766968131065369},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.5632674694061279},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5455167293548584},{"id":"https://openalex.org/C2780992000","wikidata":"https://www.wikidata.org/wiki/Q17016113","display_name":"Generator (circuit theory)","level":3,"score":0.5388997793197632},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5093444585800171},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.48898112773895264},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4693912863731384},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.46186381578445435},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4383418560028076},{"id":"https://openalex.org/C22029948","wikidata":"https://www.wikidata.org/wiki/Q45089","display_name":"Dice","level":2,"score":0.41509774327278137},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.19340091943740845},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.16139161586761475},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.08607146143913269},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1117/12.2611292","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2611292","pdf_url":null,"source":{"id":"https://openalex.org/S4363607561","display_name":"Medical Imaging 2022: Image Processing","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Medical Imaging 2022: Image Processing","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2111.01866","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2111.01866","pdf_url":"https://arxiv.org/pdf/2111.01866","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-sa","license_id":"https://openalex.org/licenses/cc-by-nc-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},{"id":"mag:3209702343","is_oa":true,"landing_page_url":"https://arxiv.org/pdf/2111.01866","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.2111.01866","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2111.01866","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2111.01866","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2111.01866","pdf_url":"https://arxiv.org/pdf/2111.01866","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-sa","license_id":"https://openalex.org/licenses/cc-by-nc-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3209702343.pdf","grobid_xml":"https://content.openalex.org/works/W3209702343.grobid-xml"},"referenced_works_count":32,"referenced_works":["https://openalex.org/W2099471712","https://openalex.org/W2123737882","https://openalex.org/W2522844972","https://openalex.org/W2535690855","https://openalex.org/W2567079332","https://openalex.org/W2739505911","https://openalex.org/W2770301434","https://openalex.org/W2789588857","https://openalex.org/W2791478600","https://openalex.org/W2807006176","https://openalex.org/W2884065486","https://openalex.org/W2914328083","https://openalex.org/W2949099979","https://openalex.org/W2951467122","https://openalex.org/W2963015987","https://openalex.org/W2964245526","https://openalex.org/W3005124029","https://openalex.org/W3013851350","https://openalex.org/W3031246127","https://openalex.org/W3152733922","https://openalex.org/W6726983635","https://openalex.org/W6731670082","https://openalex.org/W6741176310","https://openalex.org/W6741985061","https://openalex.org/W6746666563","https://openalex.org/W6752029299","https://openalex.org/W6752233107","https://openalex.org/W6755616390","https://openalex.org/W6759238902","https://openalex.org/W6773350438","https://openalex.org/W6790589072","https://openalex.org/W6793801364"],"related_works":["https://openalex.org/W3033600500","https://openalex.org/W2966196015","https://openalex.org/W3014691120","https://openalex.org/W1537869185","https://openalex.org/W2809374262","https://openalex.org/W2583599830","https://openalex.org/W2146691973","https://openalex.org/W3043972674","https://openalex.org/W2898340770","https://openalex.org/W3007148159","https://openalex.org/W3004408747","https://openalex.org/W3106431707","https://openalex.org/W3032266403","https://openalex.org/W2758203630","https://openalex.org/W2293915134","https://openalex.org/W3084971721","https://openalex.org/W3099245356","https://openalex.org/W2182306046","https://openalex.org/W3207022694","https://openalex.org/W2489612134"],"abstract_inverted_index":{"Training":[0],"computer-vision":[1],"related":[2],"algorithms":[3],"on":[4,98,137,167],"medical":[5],"images":[6,135,148],"for":[7,66,187],"disease":[8],"diagnosis":[9],"or":[10,51],"image":[11,45,49,69],"segmentation":[12,128,163],"is":[13,38,225],"difficult":[14],"due":[15],"to":[16,34,82,104],"the":[17,72,96,106,111,114,119,122,131,145,154,157,162,183,194,230,235,242],"lack":[18],"of":[19,110,121,193,203,229],"training":[20],"data,":[21,172],"labeled":[22],"samples,":[23],"and":[24,86,108,144,160,196,223],"privacy":[25],"concerns.":[26],"For":[27],"this":[28],"reason,":[29],"a":[30,127],"robust":[31],"generative":[32],"method":[33],"create":[35],"synthetic":[36,123,132,171,197,243],"data":[37,189,237,244],"highly":[39],"sought":[40],"after.":[41],"However,":[42],"most":[43],"three-dimensional":[44],"generators":[46],"require":[47],"additional":[48],"input":[50],"are":[52,80,102,141,149,179,239],"extremely":[53],"memory":[54],"intensive.":[55],"To":[56,117],"address":[57],"these":[58],"issues":[59],"we":[60,77,79,101,125],"propose":[61],"adapting":[62],"video":[63],"generation":[64],"techniques":[65],"3-":[67],"D":[68],"generation.":[70],"Using":[71],"temporal":[73],"GAN":[74],"(TGAN)":[75],"architecture,":[76],"show":[78,92,200],"able":[81,103],"generate":[83],"realistic":[84],"head":[85],"neck":[87],"PET":[88],"images.":[89,116,133],"We":[90,152],"also":[91,150,217],"that":[93,201,227],"by":[94],"conditioning":[95],"generator":[97],"tumour":[99,112,139,185],"masks,":[100],"control":[105],"geometry":[107],"location":[109],"in":[113,234,241],"generated":[115],"test":[118],"utility":[120],"images,":[124],"train":[126],"model":[129],"using":[130,156],"Synthetic":[134],"conditioned":[136],"real":[138,147,174,195,236],"masks":[140],"automatically":[142],"segmented,":[143],"corresponding":[146],"segmented.":[151],"evaluate":[153],"segmentations":[155],"Dice":[158],"score":[159],"find":[161],"algorithm":[164],"performs":[165],"similarly":[166],"both":[168],"datasets":[169],"(0.65":[170],"0.70":[173],"data).":[175],"Various":[176],"radionomic":[177,221],"features":[178,222],"then":[180],"calculated":[181,218],"over":[182],"segmented":[184],"volumes":[186],"each":[188],"set.":[190,245],"A":[191],"comparison":[192],"feature":[198,205],"distributions":[199,206],"seven":[202],"eight":[204],"had":[207],"statistically":[208],"insignificant":[209],"differences":[210],"(\ud835\udc5d":[211],"&lt;":[212],"0.05).":[213],"Correlation":[214],"coefficients":[215],"were":[216],"between":[219],"all":[220,228],"it":[224],"shown":[226],"strong":[231],"statistical":[232],"correlations":[233],"set":[238],"preserved":[240]},"counts_by_year":[],"updated_date":"2026-03-11T14:59:36.786465","created_date":"2025-10-10T00:00:00"}
