{"id":"https://openalex.org/W3185953395","doi":"https://doi.org/10.1109/tmi.2021.3101363","title":"Unsupervised CT Metal Artifact Learning Using Attention-Guided \u03b2-CycleGAN","display_name":"Unsupervised CT Metal Artifact Learning Using Attention-Guided \u03b2-CycleGAN","publication_year":2021,"publication_date":"2021-07-30","ids":{"openalex":"https://openalex.org/W3185953395","doi":"https://doi.org/10.1109/tmi.2021.3101363","mag":"3185953395","pmid":"https://pubmed.ncbi.nlm.nih.gov/34329157"},"language":"en","primary_location":{"id":"doi:10.1109/tmi.2021.3101363","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmi.2021.3101363","pdf_url":null,"source":{"id":"https://openalex.org/S58069681","display_name":"IEEE Transactions on Medical Imaging","issn_l":"0278-0062","issn":["0278-0062","1558-254X"],"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 Transactions on Medical Imaging","raw_type":"journal-article"},"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":null,"display_name":"Junghyun Lee","orcid":null},"institutions":[{"id":"https://openalex.org/I157485424","display_name":"Korea Advanced Institute of Science and Technology","ror":"https://ror.org/05apxxy63","country_code":"KR","type":"education","lineage":["https://openalex.org/I157485424"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Junghyun Lee","raw_affiliation_strings":["Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea","institution_ids":["https://openalex.org/I157485424"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Jawook Gu","orcid":"https://orcid.org/0000-0002-9291-7929"},"institutions":[{"id":"https://openalex.org/I157485424","display_name":"Korea Advanced Institute of Science and Technology","ror":"https://ror.org/05apxxy63","country_code":"KR","type":"education","lineage":["https://openalex.org/I157485424"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jawook Gu","raw_affiliation_strings":["Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea","institution_ids":["https://openalex.org/I157485424"]}]},{"author_position":"last","author":{"id":null,"display_name":"Jong Chul Ye","orcid":"https://orcid.org/0000-0001-9763-9609"},"institutions":[{"id":"https://openalex.org/I157485424","display_name":"Korea Advanced Institute of Science and Technology","ror":"https://ror.org/05apxxy63","country_code":"KR","type":"education","lineage":["https://openalex.org/I157485424"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jong Chul Ye","raw_affiliation_strings":["Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea","institution_ids":["https://openalex.org/I157485424"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I157485424"],"apc_list":null,"apc_paid":null,"fwci":3.7359,"has_fulltext":false,"cited_by_count":69,"citation_normalized_percentile":{"value":0.93921404,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"40","issue":"12","first_page":"3932","last_page":"3944"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12386","display_name":"Advanced X-ray and CT Imaging","score":0.9983000159263611,"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"}},"topics":[{"id":"https://openalex.org/T12386","display_name":"Advanced X-ray and CT Imaging","score":0.9983000159263611,"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/T11183","display_name":"Advanced X-ray Imaging Techniques","score":0.0005000000237487257,"subfield":{"id":"https://openalex.org/subfields/3108","display_name":"Radiation"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10522","display_name":"Medical Imaging Techniques and Applications","score":0.0003000000142492354,"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/artifact","display_name":"Artifact (error)","score":0.7024000287055969},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6399000287055969},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6057999730110168},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5846999883651733},{"id":"https://openalex.org/keywords/unsupervised-learning","display_name":"Unsupervised learning","score":0.5597000122070312},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5195000171661377},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.44290000200271606},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4205000102519989},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4041000008583069}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8317000269889832},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7208999991416931},{"id":"https://openalex.org/C2779010991","wikidata":"https://www.wikidata.org/wiki/Q2720909","display_name":"Artifact (error)","level":2,"score":0.7024000287055969},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6399000287055969},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6057999730110168},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5846999883651733},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.5597000122070312},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5195000171661377},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.474700003862381},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.44290000200271606},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4205000102519989},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4041000008583069},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.37950000166893005},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.359499990940094},{"id":"https://openalex.org/C2781195486","wikidata":"https://www.wikidata.org/wiki/Q289436","display_name":"Texture (cosmology)","level":3,"score":0.3465000092983246},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.34389999508857727},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.3212999999523163},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.3107999861240387},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.29679998755455017},{"id":"https://openalex.org/C63099799","wikidata":"https://www.wikidata.org/wiki/Q17147001","display_name":"Image texture","level":4,"score":0.29089999198913574},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.2840000092983246},{"id":"https://openalex.org/C189950617","wikidata":"https://www.wikidata.org/wiki/Q937228","display_name":"Property (philosophy)","level":2,"score":0.27469998598098755},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.2671999931335449},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2623000144958496},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.26100000739097595},{"id":"https://openalex.org/C163716698","wikidata":"https://www.wikidata.org/wiki/Q841267","display_name":"Tomography","level":2,"score":0.2590999901294708}],"mesh":[{"descriptor_ui":"D001288","descriptor_name":"Attention","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001288","descriptor_name":"Attention","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001288","descriptor_name":"Attention","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008670","descriptor_name":"Metals","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D008670","descriptor_name":"Metals","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D008670","descriptor_name":"Metals","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D014057","descriptor_name":"Tomography, X-Ray Computed","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D014057","descriptor_name":"Tomography, X-Ray Computed","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D014057","descriptor_name":"Tomography, X-Ray Computed","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016477","descriptor_name":"Artifacts","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016477","descriptor_name":"Artifacts","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016477","descriptor_name":"Artifacts","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true}],"locations_count":2,"locations":[{"id":"doi:10.1109/tmi.2021.3101363","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmi.2021.3101363","pdf_url":null,"source":{"id":"https://openalex.org/S58069681","display_name":"IEEE Transactions on Medical Imaging","issn_l":"0278-0062","issn":["0278-0062","1558-254X"],"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 Transactions on Medical Imaging","raw_type":"journal-article"},{"id":"pmid:34329157","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/34329157","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 transactions on medical imaging","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G7865882150","display_name":null,"funder_award_id":"NRF-2020R1A2B5B03001980","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"}],"funders":[{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":37,"referenced_works":["https://openalex.org/W2019370496","https://openalex.org/W2042580235","https://openalex.org/W2069629287","https://openalex.org/W2079127706","https://openalex.org/W2095757123","https://openalex.org/W2119408205","https://openalex.org/W2122710056","https://openalex.org/W2128272608","https://openalex.org/W2133665775","https://openalex.org/W2154129661","https://openalex.org/W2154280873","https://openalex.org/W2157812230","https://openalex.org/W2167890826","https://openalex.org/W2327037637","https://openalex.org/W2593414223","https://openalex.org/W2753044865","https://openalex.org/W2777802649","https://openalex.org/W2883683269","https://openalex.org/W2892052962","https://openalex.org/W2948149465","https://openalex.org/W2962793481","https://openalex.org/W2963073614","https://openalex.org/W2963891322","https://openalex.org/W3028088179","https://openalex.org/W3041047530","https://openalex.org/W3111841671","https://openalex.org/W4206471589","https://openalex.org/W4233762729","https://openalex.org/W6640963894","https://openalex.org/W6680834391","https://openalex.org/W6729482032","https://openalex.org/W6735913928","https://openalex.org/W6744627333","https://openalex.org/W6750804274","https://openalex.org/W6752378368","https://openalex.org/W6753412334","https://openalex.org/W6779669310"],"related_works":[],"abstract_inverted_index":{"Metal":[0],"artifact":[1,35,50,168],"reduction":[2,169],"(MAR)":[3],"is":[4,79,84,110],"one":[5],"of":[6,19,175],"the":[7,17,75,120,132,140,145,172,176],"most":[8,43],"important":[9],"research":[10],"topics":[11],"in":[12,58,139],"computed":[13],"tomography":[14],"(CT).":[15],"With":[16],"advance":[18],"deep":[20,27],"learning":[21,28,40,66,103],"approaches":[22],"for":[23,33,67,105,124],"image":[24,52],"reconstruction,":[25],"various":[26],"methods":[29,41],"have":[30],"been":[31],"suggested":[32],"metal":[34,49,146,167],"reduction,":[36],"among":[37],"which":[38],"supervised":[39],"are":[42,54],"popular.":[44],"However,":[45],"matched":[46],"metal-artifact-free":[47],"and":[48,100],"corrupted":[51],"pairs":[53],"difficult":[55,85],"to":[56,86],"obtain":[57],"real":[59],"CT":[60],"acquisition.":[61],"Recently,":[62],"a":[63,98,113],"promising":[64],"unsupervised":[65,102],"MAR":[68],"was":[69],"proposed":[70,108],"using":[71],"feature":[72,126],"disentanglement,":[73],"but":[74],"resulting":[76],"network":[77],"architecture":[78,117],"so":[80,152],"complicated":[81],"that":[82,144,153,162,170],"it":[83,154],"handle":[87],"large":[88],"size":[89],"clinical":[90],"images.":[91],"To":[92],"address":[93],"this,":[94],"here":[95],"we":[96,142,163],"propose":[97],"simple":[99],"effective":[101],"method":[104,109],"MAR.":[106],"The":[107],"based":[111],"on":[112],"novel":[114],"\u03b2":[115],"-cycleGAN":[116],"derived":[118],"from":[119],"optimal":[121],"transport":[122],"theory":[123],"appropriate":[125],"space":[127],"disentanglement.":[128],"Moreover,":[129],"by":[130],"adding":[131],"convolutional":[133],"block":[134],"attention":[135],"module":[136],"(CBAM)":[137],"layers":[138],"generator,":[141],"show":[143],"artifacts":[147],"can":[148,155,164],"be":[149,156],"more":[150],"focused":[151],"effectively":[157],"removed.":[158],"Experimental":[159],"results":[160],"confirm":[161],"achieve":[165],"improved":[166],"preserves":[171],"detailed":[173],"texture":[174],"original":[177],"image.":[178]},"counts_by_year":[{"year":2026,"cited_by_count":6},{"year":2025,"cited_by_count":19},{"year":2024,"cited_by_count":9},{"year":2023,"cited_by_count":21},{"year":2022,"cited_by_count":12},{"year":2021,"cited_by_count":2}],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2021-08-02T00:00:00"}