{"id":"https://openalex.org/W4409875313","doi":"https://doi.org/10.1088/2632-2153/add1a9","title":"Quantum generative learning for high-resolution medical image generation","display_name":"Quantum generative learning for high-resolution medical image generation","publication_year":2025,"publication_date":"2025-04-28","ids":{"openalex":"https://openalex.org/W4409875313","doi":"https://doi.org/10.1088/2632-2153/add1a9"},"language":"en","primary_location":{"id":"doi:10.1088/2632-2153/add1a9","is_oa":true,"landing_page_url":"https://doi.org/10.1088/2632-2153/add1a9","pdf_url":null,"source":{"id":"https://openalex.org/S4210200687","display_name":"Machine Learning Science and Technology","issn_l":"2632-2153","issn":["2632-2153"],"is_oa":true,"is_in_doaj":true,"is_core":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning: Science and Technology","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1088/2632-2153/add1a9","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5070096336","display_name":"Amena Khatun","orcid":"https://orcid.org/0000-0002-6912-3848"},"institutions":[{"id":"https://openalex.org/I42894916","display_name":"Data61","ror":"https://ror.org/03q397159","country_code":"AU","type":"other","lineage":["https://openalex.org/I1292875679","https://openalex.org/I2801453606","https://openalex.org/I42894916","https://openalex.org/I4387156119"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Amena Khatun","raw_affiliation_strings":["Data61, CSIRO, Dutton Park, QLD 4102, Australia"],"raw_orcid":"https://orcid.org/0000-0002-6912-3848","affiliations":[{"raw_affiliation_string":"Data61, CSIRO, Dutton Park, QLD 4102, Australia","institution_ids":["https://openalex.org/I42894916"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018229951","display_name":"K\u00fcbra Yeter\u2010Aydeniz","orcid":"https://orcid.org/0000-0002-2913-3136"},"institutions":[{"id":"https://openalex.org/I44896327","display_name":"Mitre (United States)","ror":"https://ror.org/03ks2a131","country_code":"US","type":"company","lineage":["https://openalex.org/I44896327"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"K\u00fcbra Yeter Aydeniz","raw_affiliation_strings":["Emerging Engineering and Physical Sciences Department, The MITRE Corporation, Princeton, NJ 08540, United States of America"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Emerging Engineering and Physical Sciences Department, The MITRE Corporation, Princeton, NJ 08540, United States of America","institution_ids":["https://openalex.org/I44896327"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053675852","display_name":"Yaakov S. Weinstein","orcid":null},"institutions":[{"id":"https://openalex.org/I44896327","display_name":"Mitre (United States)","ror":"https://ror.org/03ks2a131","country_code":"US","type":"company","lineage":["https://openalex.org/I44896327"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yaakov S Weinstein","raw_affiliation_strings":["Emerging Engineering and Physical Sciences Department, The MITRE Corporation, Princeton, NJ 08540, United States of America"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Emerging Engineering and Physical Sciences Department, The MITRE Corporation, Princeton, NJ 08540, United States of America","institution_ids":["https://openalex.org/I44896327"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5012865362","display_name":"Muhammad Usman","orcid":"https://orcid.org/0000-0003-3476-2348"},"institutions":[{"id":"https://openalex.org/I165779595","display_name":"The University of Melbourne","ror":"https://ror.org/01ej9dk98","country_code":"AU","type":"education","lineage":["https://openalex.org/I165779595"]},{"id":"https://openalex.org/I4210154771","display_name":"CSIRO Manufacturing","ror":"https://ror.org/04sx9wp33","country_code":"AU","type":"facility","lineage":["https://openalex.org/I1292875679","https://openalex.org/I2801453606","https://openalex.org/I4210154771","https://openalex.org/I4387156119"]},{"id":"https://openalex.org/I42894916","display_name":"Data61","ror":"https://ror.org/03q397159","country_code":"AU","type":"other","lineage":["https://openalex.org/I1292875679","https://openalex.org/I2801453606","https://openalex.org/I42894916","https://openalex.org/I4387156119"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Muhammad Usman","raw_affiliation_strings":["Data61, CSIRO, Research Way, Clayton 3168, Victoria, Australia","School of Physics, The University of Melbourne, Parkville 3010, Victoria, Australia"],"raw_orcid":"https://orcid.org/0000-0003-3476-2348","affiliations":[{"raw_affiliation_string":"Data61, CSIRO, Research Way, Clayton 3168, Victoria, Australia","institution_ids":["https://openalex.org/I4210154771","https://openalex.org/I42894916"]},{"raw_affiliation_string":"School of Physics, The University of Melbourne, Parkville 3010, Victoria, Australia","institution_ids":["https://openalex.org/I165779595"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1600,"currency":"GBP","value_usd":1962},"apc_paid":{"value":1600,"currency":"GBP","value_usd":1962},"fwci":28.1403,"has_fulltext":false,"cited_by_count":16,"citation_normalized_percentile":{"value":0.9953648,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"6","issue":"2","first_page":"025032","last_page":"025032"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10682","display_name":"Quantum Computing Algorithms and Architecture","score":0.8637999892234802,"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"}},"topics":[{"id":"https://openalex.org/T10682","display_name":"Quantum Computing Algorithms and Architecture","score":0.8637999892234802,"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"}},{"id":"https://openalex.org/T13650","display_name":"Computational Physics and Python Applications","score":0.8185999989509583,"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/generative-grammar","display_name":"Generative grammar","score":0.7131479978561401},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4753008782863617},{"id":"https://openalex.org/keywords/quantum","display_name":"Quantum","score":0.45384496450424194},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.44476377964019775},{"id":"https://openalex.org/keywords/resolution","display_name":"Resolution (logic)","score":0.4270938038825989},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.42137718200683594},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.40666937828063965},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3270914554595947},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.17383810877799988},{"id":"https://openalex.org/keywords/quantum-mechanics","display_name":"Quantum mechanics","score":0.10181543231010437}],"concepts":[{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.7131479978561401},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4753008782863617},{"id":"https://openalex.org/C84114770","wikidata":"https://www.wikidata.org/wiki/Q46344","display_name":"Quantum","level":2,"score":0.45384496450424194},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.44476377964019775},{"id":"https://openalex.org/C138268822","wikidata":"https://www.wikidata.org/wiki/Q1051925","display_name":"Resolution (logic)","level":2,"score":0.4270938038825989},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.42137718200683594},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.40666937828063965},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3270914554595947},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.17383810877799988},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.10181543231010437}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1088/2632-2153/add1a9","is_oa":true,"landing_page_url":"https://doi.org/10.1088/2632-2153/add1a9","pdf_url":null,"source":{"id":"https://openalex.org/S4210200687","display_name":"Machine Learning Science and Technology","issn_l":"2632-2153","issn":["2632-2153"],"is_oa":true,"is_in_doaj":true,"is_core":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning: Science and Technology","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:1909a4381c444e4e8b07967a8207154d","is_oa":true,"landing_page_url":"https://doaj.org/article/1909a4381c444e4e8b07967a8207154d","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Machine Learning: Science and Technology, Vol 6, Iss 2, p 025032 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1088/2632-2153/add1a9","is_oa":true,"landing_page_url":"https://doi.org/10.1088/2632-2153/add1a9","pdf_url":null,"source":{"id":"https://openalex.org/S4210200687","display_name":"Machine Learning Science and Technology","issn_l":"2632-2153","issn":["2632-2153"],"is_oa":true,"is_in_doaj":true,"is_core":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning: Science and Technology","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":47,"referenced_works":["https://openalex.org/W2475287302","https://openalex.org/W2581082771","https://openalex.org/W2592929672","https://openalex.org/W2798945316","https://openalex.org/W2798967590","https://openalex.org/W2962690307","https://openalex.org/W2974883009","https://openalex.org/W3003301247","https://openalex.org/W3004252283","https://openalex.org/W3007309629","https://openalex.org/W3014721989","https://openalex.org/W3016399951","https://openalex.org/W3028045665","https://openalex.org/W3035574324","https://openalex.org/W3040266635","https://openalex.org/W3090958492","https://openalex.org/W3092977835","https://openalex.org/W3096831136","https://openalex.org/W3159331020","https://openalex.org/W3170510435","https://openalex.org/W3202656664","https://openalex.org/W3207697613","https://openalex.org/W3211207279","https://openalex.org/W3215219470","https://openalex.org/W4220747861","https://openalex.org/W4220903258","https://openalex.org/W4308033654","https://openalex.org/W4308486497","https://openalex.org/W4312189222","https://openalex.org/W4320032187","https://openalex.org/W4387042027","https://openalex.org/W4387223545","https://openalex.org/W4390872826","https://openalex.org/W4406276557","https://openalex.org/W6631190155","https://openalex.org/W6685352114","https://openalex.org/W6735913928","https://openalex.org/W6738027021","https://openalex.org/W6741832134","https://openalex.org/W6755312952","https://openalex.org/W6755964158","https://openalex.org/W6765779288","https://openalex.org/W6766978945","https://openalex.org/W6780507278","https://openalex.org/W6782302300","https://openalex.org/W6797179183","https://openalex.org/W6843302064"],"related_works":["https://openalex.org/W4365211920","https://openalex.org/W3014948380","https://openalex.org/W4391584540","https://openalex.org/W4380551139","https://openalex.org/W4317695495","https://openalex.org/W4395044357","https://openalex.org/W4287117424","https://openalex.org/W4387506531","https://openalex.org/W2087346071","https://openalex.org/W2967848559"],"abstract_inverted_index":{"Abstract":[0],"Integration":[1],"of":[2,57,100,120,127],"quantum":[3,27,69,82,86],"computing":[4],"in":[5,161],"generative":[6,28,71],"machine":[7],"learning":[8,42,72],"models":[9,159],"has":[10],"the":[11,25,51,97,108,112,145,162],"potential":[12],"to":[13,33,38,115,152],"offer":[14],"benefits":[15],"such":[16],"as":[17],"training":[18],"speed-up":[19],"and":[20,54,135,156],"superior":[21,142],"feature":[22],"extraction.":[23],"However,":[24],"existing":[26],"adversarial":[29],"networks":[30],"(QGANs)":[31],"fail":[32],"generate":[34,116],"high-quality":[35,76],"images":[36,98,131],"due":[37],"their":[39],"patch-based,":[40],"pixel-wise":[41],"approaches.":[43],"These":[44],"methods":[45],"capture":[46],"only":[47],"local":[48],"details,":[49],"ignoring":[50],"global":[52],"structure":[53],"semantic":[55],"information":[56],"images.":[58],"In":[59],"this":[60],"work,":[61],"we":[62,106],"address":[63],"these":[64],"challenges":[65],"by":[66,92],"proposing":[67],"a":[68,117,124],"image":[70,78],"(QIGL)":[73],"approach":[74,88],"for":[75],"medical":[77,121,136],"generation.":[79],"Our":[80],"proposed":[81],"generator":[83],"leverages":[84],"variational":[85],"circuit":[87],"addressing":[89],"scalability":[90],"issues":[91],"extracting":[93],"principal":[94],"components":[95],"from":[96,132],"instead":[99],"dividing":[101],"them":[102],"into":[103],"patches.":[104],"Additionally,":[105],"integrate":[107],"Wasserstein":[109],"distance":[110,149],"within":[111],"QIGL":[113],"framework":[114],"diverse":[118],"set":[119,126],"samples.":[122],"Through":[123],"systematic":[125],"simulations":[128],"on":[129],"x-ray":[130],"knee":[133],"osteoarthritis":[134],"MNIST":[137],"datasets,":[138],"our":[139],"model":[140],"demonstrates":[141],"performance,":[143],"achieving":[144],"lowest":[146],"Fr\u00e9chet":[147],"inception":[148],"scores":[150],"compared":[151],"its":[153],"classical":[154],"counterpart":[155],"advanced":[157],"QGAN":[158],"reported":[160],"literature.":[163]},"counts_by_year":[{"year":2026,"cited_by_count":9},{"year":2025,"cited_by_count":7}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}