{"id":"https://openalex.org/W3132466470","doi":"https://doi.org/10.1109/iros45743.2020.9341556","title":"LC-GAN: Image-to-image Translation Based on Generative Adversarial Network for Endoscopic Images","display_name":"LC-GAN: Image-to-image Translation Based on Generative Adversarial Network for Endoscopic Images","publication_year":2020,"publication_date":"2020-10-24","ids":{"openalex":"https://openalex.org/W3132466470","doi":"https://doi.org/10.1109/iros45743.2020.9341556","mag":"3132466470"},"language":"en","primary_location":{"id":"doi:10.1109/iros45743.2020.9341556","doi":"https://doi.org/10.1109/iros45743.2020.9341556","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros45743.2020.9341556","pdf_url":null,"source":{"id":"https://openalex.org/S4393918188","display_name":"IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","issn_l":"2153-0858","issn":["2153-0858"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":["jufo-1","norway-1"],"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":"2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2003.04949","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101857095","display_name":"Shan Lin","orcid":"https://orcid.org/0000-0003-3874-1368","observed_orcids":["https://orcid.org/0000-0003-3874-1368"]},"institutions":[{"id":"https://openalex.org/I201448701","display_name":"University of Washington","ror":"https://ror.org/00cvxb145","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shan Lin","raw_affiliation_strings":["University of Washington, Seattle, WA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Washington, Seattle, WA, USA","institution_ids":["https://openalex.org/I201448701"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003819876","display_name":"Fangbo Qin","orcid":"https://orcid.org/0000-0002-4085-0857","observed_orcids":["https://orcid.org/0000-0002-4085-0857"]},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fangbo Qin","raw_affiliation_strings":["Institute of Automation, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Automation, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025128323","display_name":"Yangming Li","orcid":"https://orcid.org/0000-0002-9794-8054","observed_orcids":["https://orcid.org/0000-0002-9794-8054"]},"institutions":[{"id":"https://openalex.org/I155173764","display_name":"Rochester Institute of Technology","ror":"https://ror.org/00v4yb702","country_code":"US","type":"education","lineage":["https://openalex.org/I155173764"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yangming Li","raw_affiliation_strings":["Rochester Institute of Technology, Rochester, NY, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Rochester Institute of Technology, Rochester, NY, USA","institution_ids":["https://openalex.org/I155173764"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037647476","display_name":"Randall A. Bly","orcid":"https://orcid.org/0000-0001-5308-527X","observed_orcids":["https://orcid.org/0000-0001-5308-527X"]},"institutions":[{"id":"https://openalex.org/I201448701","display_name":"University of Washington","ror":"https://ror.org/00cvxb145","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Randall A. Bly","raw_affiliation_strings":["University of Washington, Seattle, WA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Washington, Seattle, WA, USA","institution_ids":["https://openalex.org/I201448701"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110528271","display_name":"Kris S. Moe","orcid":"https://orcid.org/0000-0001-6045-7756","observed_orcids":["https://orcid.org/0000-0001-6045-7756"]},"institutions":[{"id":"https://openalex.org/I201448701","display_name":"University of Washington","ror":"https://ror.org/00cvxb145","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kris S. Moe","raw_affiliation_strings":["University of Washington, Seattle, WA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Washington, Seattle, WA, USA","institution_ids":["https://openalex.org/I201448701"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5074967911","display_name":"Blake Hannaford","orcid":"https://orcid.org/0000-0001-7370-4920","observed_orcids":["https://orcid.org/0000-0001-7370-4920"]},"institutions":[{"id":"https://openalex.org/I201448701","display_name":"University of Washington","ror":"https://ror.org/00cvxb145","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Blake Hannaford","raw_affiliation_strings":["University of Washington, Seattle, WA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Washington, Seattle, WA, USA","institution_ids":["https://openalex.org/I201448701"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.9841,"has_fulltext":true,"cited_by_count":41,"citation_normalized_percentile":{"value":0.90995695,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"2914","last_page":"2920"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.7577999830245972,"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"}},"topics":[{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.7577999830245972,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.17759999632835388,"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.04309999942779541,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/image-to-image-translation","display_name":"image-to-image translation","score":0.9660000205039978},{"id":"https://openalex.org/keywords/generative-adversarial-networks","display_name":"generative adversarial networks","score":0.9440000057220459},{"id":"https://openalex.org/keywords/endoscopic-images","display_name":"endoscopic images","score":0.9599999785423279},{"id":"https://openalex.org/keywords/instrument-segmentation","display_name":"instrument segmentation","score":0.7590000033378601},{"id":"https://openalex.org/keywords/live-surgery","display_name":"live surgery","score":0.7210000157356262},{"id":"https://openalex.org/keywords/cross-domain-segmentation","display_name":"cross-domain segmentation","score":0.8999999761581421},{"id":"https://openalex.org/keywords/domain-adaptation","display_name":"domain adaptation","score":0.5899999737739563},{"id":"https://openalex.org/keywords/structural-similarity-loss","display_name":"structural similarity loss","score":0.7979999780654907},{"id":"https://openalex.org/keywords/computer-assisted-surgery","display_name":"computer-assisted surgery","score":0.6819999814033508},{"id":"https://openalex.org/keywords/robotic-surgery","display_name":"robotic surgery","score":0.5979999899864197}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8223793506622314},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8055086731910706},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6978757977485657},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6370358467102051},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.6033387780189514},{"id":"https://openalex.org/C2779757391","wikidata":"https://www.wikidata.org/wiki/Q6002292","display_name":"Image translation","level":3,"score":0.576933741569519},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.47083213925361633},{"id":"https://openalex.org/C175696284","wikidata":"https://www.wikidata.org/wiki/Q986524","display_name":"Cadaveric spasm","level":2,"score":0.4701801836490631},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4659944772720337},{"id":"https://openalex.org/C149364088","wikidata":"https://www.wikidata.org/wiki/Q185917","display_name":"Translation (biology)","level":4,"score":0.43922558426856995},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3695439100265503},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3634968400001526},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C105702510","wikidata":"https://www.wikidata.org/wiki/Q514","display_name":"Anatomy","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C105580179","wikidata":"https://www.wikidata.org/wiki/Q188928","display_name":"Messenger RNA","level":3,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/iros45743.2020.9341556","doi":"https://doi.org/10.1109/iros45743.2020.9341556","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros45743.2020.9341556","pdf_url":null,"source":{"id":"https://openalex.org/S4393918188","display_name":"IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","issn_l":"2153-0858","issn":["2153-0858"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":["jufo-1","norway-1"],"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":"2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2003.04949","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2003.04949","pdf_url":"https://arxiv.org/pdf/2003.04949","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2003.04949","doi":"https://doi.org/10.48550/arxiv.2003.04949","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2003.04949","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":false,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2003.04949","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2003.04949","pdf_url":"https://arxiv.org/pdf/2003.04949","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":null,"raw_type":"text"},"sustainable_development_goals":[{"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3","score":0.46810001134872437}],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3132466470.pdf","grobid_xml":"https://content.openalex.org/works/W3132466470.grobid-xml"},"referenced_works_count":54,"referenced_works":["https://openalex.org/W1580389772","https://openalex.org/W1599851310","https://openalex.org/W1901129140","https://openalex.org/W1903029394","https://openalex.org/W1909740415","https://openalex.org/W2078017485","https://openalex.org/W2099471712","https://openalex.org/W2133665775","https://openalex.org/W2159349609","https://openalex.org/W2194775991","https://openalex.org/W2300177233","https://openalex.org/W2302255633","https://openalex.org/W2311571231","https://openalex.org/W2418398539","https://openalex.org/W2519007024","https://openalex.org/W2552465644","https://openalex.org/W2560023338","https://openalex.org/W2592480533","https://openalex.org/W2625768866","https://openalex.org/W2657144928","https://openalex.org/W2735039185","https://openalex.org/W2767657961","https://openalex.org/W2770363598","https://openalex.org/W2782757030","https://openalex.org/W2792767783","https://openalex.org/W2793160340","https://openalex.org/W2793938489","https://openalex.org/W2824076120","https://openalex.org/W2892052962","https://openalex.org/W2896107389","https://openalex.org/W2913444875","https://openalex.org/W2916253547","https://openalex.org/W2926374707","https://openalex.org/W2928934200","https://openalex.org/W2944341780","https://openalex.org/W2955927142","https://openalex.org/W2962793481","https://openalex.org/W2963470893","https://openalex.org/W2963890275","https://openalex.org/W2963966654","https://openalex.org/W2964309882","https://openalex.org/W2964317695","https://openalex.org/W2967185966","https://openalex.org/W2981462961","https://openalex.org/W2995784156","https://openalex.org/W3008810159","https://openalex.org/W3089931213","https://openalex.org/W3098152091","https://openalex.org/W4320013936","https://openalex.org/W6635846086","https://openalex.org/W6747680804","https://openalex.org/W6758742486","https://openalex.org/W6773996751","https://openalex.org/W6960118973"],"related_works":["https://openalex.org/W2910742108","https://openalex.org/W4403569228","https://openalex.org/W3041533023","https://openalex.org/W3204249496","https://openalex.org/W2981981994","https://openalex.org/W4323338566","https://openalex.org/W3106432280","https://openalex.org/W2955927142","https://openalex.org/W3138038768","https://openalex.org/W3128248230"],"abstract_inverted_index":{"Intelligent":[0],"vision":[1],"is":[2,23,69,74],"appealing":[3],"in":[4,27,201],"computer-assisted":[5],"and":[6,25,93,111,178,195],"robotic":[7],"surgeries.":[8],"Vision-based":[9],"analysis":[10],"with":[11,109,119,154],"deep":[12,160],"learning":[13],"usually":[14],"requires":[15],"large":[16],"labeled":[17,65,135],"datasets,":[18],"but":[19],"manual":[20,41],"data":[21,42],"labeling":[22,43],"expensive":[24],"time-consuming":[26],"medical":[28],"problems.":[29],"We":[30,59,83],"investigate":[31],"a":[32,61,64],"novel":[33],"cross-domain":[34,204],"strategy":[35],"to":[36,86,106,145,182,197],"reduce":[37],"the":[38,72,88,91,103,116,123,134,143,147,159,165,174,184,202],"need":[39,144],"for":[40,138],"by":[44],"proposing":[45],"an":[46,78],"image-to-image":[47,193],"translation":[48,194],"model":[49,190],"live-cadaver":[50],"GAN":[51],"(LC-GAN)":[52],"based":[53,168],"on":[54,77,115,122],"generative":[55],"adversarial":[56],"networks":[57],"(GANs).":[58],"consider":[60],"situation":[62],"when":[63],"cadaveric":[66,92,125,136,166],"surgery":[67,81],"dataset":[68,137],"available":[70],"while":[71],"task":[73],"instrument":[75],"segmentation":[76,114,141,169,179,199,205],"unlabeled":[79],"live":[80,94,97,104,139,148],"dataset.":[82,126,149],"train":[84],"LC-GAN":[85,110,150],"learn":[87],"mappings":[89],"between":[90],"images.":[95],"For":[96],"image":[98,140,167],"segmentation,":[99],"we":[100,172],"first":[101],"translate":[102],"images":[105,108,118],"fake-cadaveric":[107,117],"then":[112],"perform":[113],"models":[120],"trained":[121],"real":[124],"The":[127],"proposed":[128,203],"method":[129],"fully":[130],"makes":[131],"use":[132],"of":[133],"without":[142],"label":[146],"has":[151],"two":[152],"generators":[153],"different":[155],"architectures":[156],"that":[157],"leverage":[158],"feature":[161],"representation":[162],"learned":[163],"from":[164],"task.":[170,206],"Moreover,":[171],"propose":[173],"structural":[175],"similarity":[176],"loss":[177,181],"consistency":[180,186],"improve":[183],"semantic":[185],"during":[187],"translation.":[188],"Our":[189],"achieves":[191],"better":[192],"leads":[196],"improved":[198],"performance":[200]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":10},{"year":2022,"cited_by_count":9},{"year":2021,"cited_by_count":7}],"updated_date":"2026-11-03T10:50:19.383937","created_date":"2021-03-01T00:00:00"}