{"id":"https://openalex.org/W4408521437","doi":"https://doi.org/10.1109/bhi62660.2024.10913669","title":"SR - TGAN: Smoke Removal with Temporal Generative Adversarial Models in Robot-assisted Surgery","display_name":"SR - TGAN: Smoke Removal with Temporal Generative Adversarial Models in Robot-assisted Surgery","publication_year":2024,"publication_date":"2024-11-10","ids":{"openalex":"https://openalex.org/W4408521437","doi":"https://doi.org/10.1109/bhi62660.2024.10913669"},"language":"en","primary_location":{"id":"doi:10.1109/bhi62660.2024.10913669","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bhi62660.2024.10913669","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE EMBS International Conference on Biomedical and Health Informatics (BHI)","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/A5057223988","display_name":"Mengya Xu","orcid":"https://orcid.org/0000-0002-4338-7079"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"HK","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Mengya Xu","raw_affiliation_strings":["The Chinese University of Hong Kong,Department of Electronic Engineering,Hong Kong SAR,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Chinese University of Hong Kong,Department of Electronic Engineering,Hong Kong SAR,China","institution_ids":["https://openalex.org/I177725633"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5093460664","display_name":"Omer Raza","orcid":null},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Omer Raza","raw_affiliation_strings":["Purdue University,Department of Computer Science,West Lafayette,Indiana,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Purdue University,Department of Computer Science,West Lafayette,Indiana,USA","institution_ids":["https://openalex.org/I219193219"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100419954","display_name":"An Wang","orcid":"https://orcid.org/0000-0001-5515-0653"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"HK","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"An Wang","raw_affiliation_strings":["The Chinese University of Hong Kong,Department of Electronic Engineering,Hong Kong SAR,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Chinese University of Hong Kong,Department of Electronic Engineering,Hong Kong SAR,China","institution_ids":["https://openalex.org/I177725633"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100764061","display_name":"Hongliang Ren","orcid":"https://orcid.org/0000-0002-2760-5224"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"HK","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Hongliang Ren","raw_affiliation_strings":["The Chinese University of Hong Kong,Department of Electronic Engineering,Hong Kong SAR,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Chinese University of Hong Kong,Department of Electronic Engineering,Hong Kong SAR,China","institution_ids":["https://openalex.org/I177725633"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9689000248908997,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9689000248908997,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9261999726295471,"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/T12290","display_name":"Human Motion and Animation","score":0.9190000295639038,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/smoke","display_name":"Smoke","score":0.72862309217453},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.6683534979820251},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.6009469628334045},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5688632726669312},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.5601746439933777},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.47586339712142944},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.4492711126804352},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.20693501830101013},{"id":"https://openalex.org/keywords/waste-management","display_name":"Waste management","score":0.10876888036727905}],"concepts":[{"id":"https://openalex.org/C58874564","wikidata":"https://www.wikidata.org/wiki/Q130768","display_name":"Smoke","level":2,"score":0.72862309217453},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.6683534979820251},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.6009469628334045},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5688632726669312},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.5601746439933777},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47586339712142944},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.4492711126804352},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.20693501830101013},{"id":"https://openalex.org/C548081761","wikidata":"https://www.wikidata.org/wiki/Q180388","display_name":"Waste management","level":1,"score":0.10876888036727905}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bhi62660.2024.10913669","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bhi62660.2024.10913669","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE EMBS International Conference on Biomedical and Health Informatics (BHI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Good health and well-being","score":0.6200000047683716,"id":"https://metadata.un.org/sdg/3"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1552073401","https://openalex.org/W2138088051","https://openalex.org/W2546190447","https://openalex.org/W2584009249","https://openalex.org/W2593414223","https://openalex.org/W2788686466","https://openalex.org/W2962793481","https://openalex.org/W2962891897","https://openalex.org/W2963074253","https://openalex.org/W2963306157","https://openalex.org/W2963564844","https://openalex.org/W2963709863","https://openalex.org/W2984306354","https://openalex.org/W3005969576","https://openalex.org/W3015519144","https://openalex.org/W3094074252","https://openalex.org/W3142024233","https://openalex.org/W3212516020","https://openalex.org/W4220997012","https://openalex.org/W4226301153","https://openalex.org/W4240805545","https://openalex.org/W4246193833","https://openalex.org/W4361287323","https://openalex.org/W4385245566"],"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":{"The":[0,198,239],"occurrence":[1],"of":[2,10,61,150,200,229],"smoke":[3,28,146,223],"during":[4],"endoscopic":[5,237],"surgery":[6],"hampers":[7],"the":[8,58,62,78,86,96,119,136,165,194,208,219,227],"ease":[9],"navigation":[11],"and":[12,19,50,157,225],"obstructs":[13],"clear":[14],"visibility,":[15],"thereby":[16],"presenting":[17],"challenges":[18,44],"amplifying":[20],"risks":[21],"within":[22],"surgical":[23,91,212],"procedures.":[24],"Current":[25],"image":[26,196],"processing-based":[27],"removal":[29],"methods":[30],"predominantly":[31],"utilize":[32],"machine":[33],"learning":[34],"approaches,":[35],"specifically":[36],"Generative":[37,80],"Adversarial":[38,81],"Networks":[39],"(GAN).":[40],"However,":[41],"they":[42,206],"encounter":[43],"in":[45,90,115,125,144,235],"effectively":[46,111],"preserving":[47],"fine":[48],"details":[49],"generating":[51],"realistic":[52],"images,":[53],"a":[54,126,148],"critical":[55],"reason":[56],"being":[57],"i.i.d":[59],"assumption":[60],"inputs.":[63],"To":[64],"tackle":[65],"these":[66],"issues,":[67],"we":[68],"present":[69],"SR-TGAN:":[70],"an":[71],"innovative":[72],"approach":[73],"for":[74,193],"Smoke":[75],"Removal":[76],"with":[77,135],"Temporal":[79],"Network.":[82],"Our":[83],"model":[84],"leverages":[85],"temporal":[87],"dynamics":[88],"inherent":[89],"videos":[92],"to":[93,110,174,179,189,191,210,221],"significantly":[94],"enhance":[95,226],"reconstructed":[97],"images'":[98],"quality.":[99],"Specifically,":[100],"SR-TGAN":[101],"integrates":[102],"sequential":[103],"contextual":[104],"information":[105],"from":[106,147,170,187],"closely":[107],"preceding":[108],"frames":[109],"eliminate":[112],"smoke,":[113],"especially":[114],"regions":[116],"where":[117],"inferring":[118],"background":[120],"is":[121,241],"challenging":[122],"such":[123],"as":[124,205],"highly":[127],"occluded":[128],"region.":[129],"By":[130],"comparing":[131],"our":[132,139],"SR-":[133],"TGAN":[134],"state-of-the-art":[137],"DeSmoke-LAP,":[138],"method":[140],"exhibits":[141,168],"enhanced":[142],"effectiveness":[143],"eliminating":[145],"dataset":[149],"500":[151],"test":[152],"images.":[153],"Both":[154],"visual":[155],"inspection":[156],"quantitative":[158],"metrics":[159],"support":[160],"this":[161,201],"conclusion.":[162],"In":[163],"particular,":[164],"JNBM":[166],"metric":[167],"improvement":[169],"1.37":[171],"(input":[172],"images)":[173,178],"1.49":[175],"(DeSmoke-LAP":[176],"generated":[177,182],"1.51":[180],"(SR-TGAN":[181],"images),":[183],"while":[184],"FADE":[185],"decreases":[186],"0.737":[188],"0.360":[190],"0.346":[192],"corresponding":[195],"sets.":[197],"implications":[199],"study":[202],"are":[203],"significant":[204],"have":[207],"potential":[209],"reduce":[211],"risks,":[213],"alleviate":[214],"surgeons'":[215],"workload":[216],"by":[217],"reducing":[218],"need":[220],"remove":[222],"physically,":[224],"precision":[228],"other":[230],"computer":[231],"vision":[232],"algorithms":[233],"utilized":[234],"live":[236],"surgeries.":[238],"code":[240],"available":[242],"at":[243],"https://github.com/XuMengyaAmy/SR-TGAN.":[244]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}