{"id":"https://openalex.org/W4399039679","doi":"https://doi.org/10.1109/tmi.2024.3405794","title":"Distance Regression Enhanced With Temporal Information Fusion and Adversarial Training for Robot-Assisted Endomicroscopy","display_name":"Distance Regression Enhanced With Temporal Information Fusion and Adversarial Training for Robot-Assisted Endomicroscopy","publication_year":2024,"publication_date":"2024-05-27","ids":{"openalex":"https://openalex.org/W4399039679","doi":"https://doi.org/10.1109/tmi.2024.3405794","pmid":"https://pubmed.ncbi.nlm.nih.gov/38801689"},"language":"en","primary_location":{"id":"doi:10.1109/tmi.2024.3405794","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmi.2024.3405794","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":"https://openalex.org/A5076772092","display_name":"Chi Xu","orcid":"https://orcid.org/0000-0002-3530-2733"},"institutions":[{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Chi Xu","raw_affiliation_strings":["Department of Surgery and Cancer, The Hamlyn Centre for Robotic Surgery, Imperial College London, London, U.K"],"raw_orcid":"https://orcid.org/0000-0002-3530-2733","affiliations":[{"raw_affiliation_string":"Department of Surgery and Cancer, The Hamlyn Centre for Robotic Surgery, Imperial College London, London, U.K","institution_ids":["https://openalex.org/I47508984"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022005243","display_name":"Haozheng Xu","orcid":"https://orcid.org/0009-0004-0594-3945"},"institutions":[{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Haozheng Xu","raw_affiliation_strings":["Department of Surgery and Cancer, The Hamlyn Centre for Robotic Surgery, Imperial College London, London, U.K"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Surgery and Cancer, The Hamlyn Centre for Robotic Surgery, Imperial College London, London, U.K","institution_ids":["https://openalex.org/I47508984"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5054387003","display_name":"Stamatia Giannarou","orcid":"https://orcid.org/0000-0002-8745-1343"},"institutions":[{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Stamatia Giannarou","raw_affiliation_strings":["Department of Surgery and Cancer, The Hamlyn Centre for Robotic Surgery, Imperial College London, London, U.K"],"raw_orcid":"https://orcid.org/0000-0002-8745-1343","affiliations":[{"raw_affiliation_string":"Department of Surgery and Cancer, The Hamlyn Centre for Robotic Surgery, Imperial College London, London, U.K","institution_ids":["https://openalex.org/I47508984"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I47508984"],"apc_list":null,"apc_paid":null,"fwci":1.3551,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.80444589,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":98},"biblio":{"volume":"43","issue":"11","first_page":"3895","last_page":"3908"},"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":0.9431999921798706,"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":0.9431999921798706,"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/T11885","display_name":"MRI in cancer diagnosis","score":0.9221000075340271,"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/endomicroscopy","display_name":"Endomicroscopy","score":0.8352679014205933},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6999392509460449},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6181415319442749},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5653071403503418},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.49149906635284424},{"id":"https://openalex.org/keywords/image-fusion","display_name":"Image fusion","score":0.46796852350234985},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.4665517508983612},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.4459786117076874},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4425746202468872},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.4270707070827484},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3815942108631134},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.20787429809570312},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.18205571174621582},{"id":"https://openalex.org/keywords/confocal","display_name":"Confocal","score":0.08836692571640015},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.08811745047569275}],"concepts":[{"id":"https://openalex.org/C17480853","wikidata":"https://www.wikidata.org/wiki/Q5376368","display_name":"Endomicroscopy","level":3,"score":0.8352679014205933},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6999392509460449},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6181415319442749},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5653071403503418},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.49149906635284424},{"id":"https://openalex.org/C69744172","wikidata":"https://www.wikidata.org/wiki/Q860822","display_name":"Image fusion","level":3,"score":0.46796852350234985},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.4665517508983612},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.4459786117076874},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4425746202468872},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.4270707070827484},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3815942108631134},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.20787429809570312},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.18205571174621582},{"id":"https://openalex.org/C136009344","wikidata":"https://www.wikidata.org/wiki/Q336201","display_name":"Confocal","level":2,"score":0.08836692571640015},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.08811745047569275},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D004724","descriptor_name":"Endoscopy","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D004724","descriptor_name":"Endoscopy","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D004724","descriptor_name":"Endoscopy","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D004724","descriptor_name":"Endoscopy","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D018613","descriptor_name":"Microscopy, Confocal","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D018613","descriptor_name":"Microscopy, Confocal","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D018613","descriptor_name":"Microscopy, Confocal","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D018613","descriptor_name":"Microscopy, Confocal","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D065287","descriptor_name":"Robotic Surgical Procedures","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D065287","descriptor_name":"Robotic Surgical Procedures","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D065287","descriptor_name":"Robotic Surgical Procedures","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D065287","descriptor_name":"Robotic Surgical Procedures","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true}],"locations_count":2,"locations":[{"id":"doi:10.1109/tmi.2024.3405794","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmi.2024.3405794","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:38801689","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/38801689","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/G665417808","display_name":"Molecularly aware robotics for surgery (MARS)","funder_award_id":"EP/W004798/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"},{"id":"https://openalex.org/G6788765131","display_name":null,"funder_award_id":"URF\\R\\201014","funder_id":"https://openalex.org/F4320320006","funder_display_name":"Royal Society"},{"id":"https://openalex.org/G7661004567","display_name":null,"funder_award_id":"EP/W004798/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"}],"funders":[{"id":"https://openalex.org/F4320320006","display_name":"Royal Society","ror":"https://ror.org/03wnrjx87"},{"id":"https://openalex.org/F4320334627","display_name":"Engineering and Physical Sciences Research Council","ror":"https://ror.org/0439y7842"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":58,"referenced_works":["https://openalex.org/W1598866093","https://openalex.org/W1686810756","https://openalex.org/W1689711448","https://openalex.org/W1924770834","https://openalex.org/W2194775991","https://openalex.org/W2330485005","https://openalex.org/W2553156677","https://openalex.org/W2593414223","https://openalex.org/W2611395991","https://openalex.org/W2617064674","https://openalex.org/W2765811365","https://openalex.org/W2783303820","https://openalex.org/W2790594255","https://openalex.org/W2790695487","https://openalex.org/W2792179230","https://openalex.org/W2890451764","https://openalex.org/W2896457183","https://openalex.org/W2948499658","https://openalex.org/W2952267667","https://openalex.org/W2952716587","https://openalex.org/W2963163009","https://openalex.org/W2963446712","https://openalex.org/W2963574983","https://openalex.org/W2964137095","https://openalex.org/W2985775862","https://openalex.org/W2999435349","https://openalex.org/W3012582094","https://openalex.org/W3034582814","https://openalex.org/W3044812225","https://openalex.org/W3094118223","https://openalex.org/W3096678291","https://openalex.org/W3096831136","https://openalex.org/W3099186728","https://openalex.org/W3105616927","https://openalex.org/W3111322308","https://openalex.org/W3126071990","https://openalex.org/W3131796352","https://openalex.org/W3131855784","https://openalex.org/W3137540208","https://openalex.org/W3138516171","https://openalex.org/W3171615848","https://openalex.org/W3180355996","https://openalex.org/W4200173722","https://openalex.org/W4224442033","https://openalex.org/W4225476092","https://openalex.org/W4226265017","https://openalex.org/W4293243680","https://openalex.org/W4296193300","https://openalex.org/W4308443974","https://openalex.org/W4312443924","https://openalex.org/W4385245566","https://openalex.org/W6635810480","https://openalex.org/W6637373629","https://openalex.org/W6640212811","https://openalex.org/W6741832134","https://openalex.org/W6755207826","https://openalex.org/W6755312952","https://openalex.org/W6785302134"],"related_works":["https://openalex.org/W2502115930","https://openalex.org/W2482350142","https://openalex.org/W4246396837","https://openalex.org/W3126451824","https://openalex.org/W1561927205","https://openalex.org/W3191453585","https://openalex.org/W4297672492","https://openalex.org/W4310988119","https://openalex.org/W4285226279","https://openalex.org/W4288019534"],"abstract_inverted_index":{"Probe-based":[0],"confocal":[1],"laser":[2],"endomicroscopy":[3],"(pCLE)":[4],"has":[5],"a":[6,37,65,80,107,115,121,161,180],"role":[7],"in":[8,146,200,222,241],"characterising":[9],"tissue":[10],"intraoperatively":[11],"to":[12,33,90,173,191,204],"guide":[13],"tumour":[14],"resection":[15],"during":[16],"surgery.":[17],"To":[18,150],"capture":[19],"good":[20],"quality":[21,246],"pCLE":[22,148,224,237],"data":[23,193,225,245],"which":[24,51,127,159,195],"is":[25,89,160,189],"important":[26],"for":[27,110,129],"diagnosis,":[28],"the":[29,53,57,72,92,102,130,141,147,156,175,186,201,206,217,223,236],"probe-tissue":[30,58],"contact":[31],"needs":[32],"be":[34,45],"maintained":[35],"within":[36],"working":[38],"range":[39],"of":[40,56,71,87,114,144,219,243],"micrometre":[41],"scale.":[42],"This":[43,138],"can":[44],"achieved":[46],"through":[47],"micro-surgical":[48],"robotic":[49],"manipulation":[50],"requires":[52],"automatic":[54],"estimation":[55],"distance.":[59],"In":[60],"this":[61],"paper,":[62],"we":[63,178],"propose":[64],"novel":[66,122],"deep":[67],"regression":[68,176,207,228],"framework":[69],"composed":[70],"Deep":[73],"Regression":[74,238],"Generative":[75],"Adversarial":[76],"Network":[77],"(DR-GAN)":[78],"and":[79,134,226,247],"Sequence":[81],"Attention":[82],"(SA)":[83],"module.":[84],"The":[85],"aim":[86],"DR-GAN":[88,119],"train":[91,174],"network":[93,188,211],"using":[94,106],"an":[95],"enhanced":[96,164],"image-based":[97],"supervision":[98],"approach.":[99],"It":[100,230],"extents":[101],"standard":[103],"generator":[104],"by":[105,215],"well-defined":[108],"function":[109],"image":[111],"generation,":[112],"instead":[113],"learnable":[116,123],"decoder.":[117],"Also,":[118],"uses":[120],"neural":[124],"perceptual":[125],"loss":[126],"combines":[128],"first":[131],"time":[132,199],"spatial":[133],"frequency":[135],"domain":[136],"features.":[137],"effectively":[139],"suppresses":[140],"adverse":[142],"effects":[143],"noise":[145,221],"data.":[149],"incorporate":[151],"temporal":[152],"information,":[153],"we've":[154],"designed":[155,179],"SA":[157],"module":[158,203],"cross-attention":[162],"module,":[163],"with":[165],"Radial":[166],"Basis":[167],"Function":[168],"based":[169],"encoding":[170],"(SA-RBF).":[171],"Furthermore,":[172],"framework,":[177],"multi-step":[181],"training":[182],"mechanism.":[183],"During":[184],"inference,":[185],"trained":[187],"used":[190],"generate":[192],"representations":[194],"are":[196],"fused":[197],"along":[198],"SA-RBF":[202],"boost":[205],"stability.":[208,229,248],"Our":[209],"proposed":[210],"advances":[212],"SOTA":[213,232],"networks":[214,233],"addressing":[216],"challenge":[218],"excessive":[220],"enhancing":[227],"outperforms":[231],"applied":[234],"on":[235],"dataset":[239],"(PRD)":[240],"terms":[242],"accuracy,":[244]},"counts_by_year":[{"year":2025,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
