{"id":"https://openalex.org/W4221154441","doi":"https://doi.org/10.1109/isbi53787.2023.10230361","title":"MDT-Net: Multi-Domain Transfer by Perceptual Supervision for Unpaired Images in OCT Scan","display_name":"MDT-Net: Multi-Domain Transfer by Perceptual Supervision for Unpaired Images in OCT Scan","publication_year":2023,"publication_date":"2023-04-18","ids":{"openalex":"https://openalex.org/W4221154441","doi":"https://doi.org/10.1109/isbi53787.2023.10230361"},"language":"en","primary_location":{"id":"doi:10.1109/isbi53787.2023.10230361","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/isbi53787.2023.10230361","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE 20th International Symposium on Biomedical Imaging (ISBI)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2203.06363","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5019008241","display_name":"Weinan Song","orcid":"https://orcid.org/0000-0002-7464-1551"},"institutions":[{"id":"https://openalex.org/I161318765","display_name":"University of California, Los Angeles","ror":"https://ror.org/046rm7j60","country_code":"US","type":"education","lineage":["https://openalex.org/I161318765"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Weinan Song","raw_affiliation_strings":["University of California,Los Angeles"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of California,Los Angeles","institution_ids":["https://openalex.org/I161318765"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060539849","display_name":"Gaurav Fotedar","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gaurav Fotedar","raw_affiliation_strings":["VoxelCloud Inc"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"VoxelCloud Inc","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011019569","display_name":"Nima Tajbakhsh","orcid":"https://orcid.org/0000-0001-8614-4811"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nima Tajbakhsh","raw_affiliation_strings":["VoxelCloud Inc"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"VoxelCloud Inc","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010204267","display_name":"Ziheng Zhou","orcid":"https://orcid.org/0000-0002-5241-5326"},"institutions":[{"id":"https://openalex.org/I161318765","display_name":"University of California, Los Angeles","ror":"https://ror.org/046rm7j60","country_code":"US","type":"education","lineage":["https://openalex.org/I161318765"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ziheng Zhou","raw_affiliation_strings":["University of California,Los Angeles"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of California,Los Angeles","institution_ids":["https://openalex.org/I161318765"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Lei He","orcid":null},"institutions":[{"id":"https://openalex.org/I161318765","display_name":"University of California, Los Angeles","ror":"https://ror.org/046rm7j60","country_code":"US","type":"education","lineage":["https://openalex.org/I161318765"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Lei He","raw_affiliation_strings":["University of California,Los Angeles"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of California,Los Angeles","institution_ids":["https://openalex.org/I161318765"]}]},{"author_position":"last","author":{"id":null,"display_name":"Xiaowei Ding","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiaowei Ding","raw_affiliation_strings":["VoxelCloud Inc"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"VoxelCloud Inc","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"30","issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13497","display_name":"Hermeneutics and Narrative Identity","score":0.9879000186920166,"subfield":{"id":"https://openalex.org/subfields/1211","display_name":"Philosophy"},"field":{"id":"https://openalex.org/fields/12","display_name":"Arts and Humanities"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T13497","display_name":"Hermeneutics and Narrative Identity","score":0.9879000186920166,"subfield":{"id":"https://openalex.org/subfields/1211","display_name":"Philosophy"},"field":{"id":"https://openalex.org/fields/12","display_name":"Arts and Humanities"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T13695","display_name":"Aging, Elder Care, and Social Issues","score":0.9749000072479248,"subfield":{"id":"https://openalex.org/subfields/3600","display_name":"General Health Professions"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T13099","display_name":"Health, Medicine and Society","score":0.95660001039505,"subfield":{"id":"https://openalex.org/subfields/3600","display_name":"General Health Professions"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7673588991165161},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.70298171043396},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.6873349547386169},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.652296781539917},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6473962068557739},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5239296555519104},{"id":"https://openalex.org/keywords/domain-adaptation","display_name":"Domain adaptation","score":0.49244794249534607},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.489686518907547},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.472993940114975},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.46664121747016907},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.46520549058914185},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.43444231152534485},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.42718762159347534},{"id":"https://openalex.org/keywords/transfer","display_name":"Transfer (computing)","score":0.42502832412719727},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.40335315465927124},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10475406050682068}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7673588991165161},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.70298171043396},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.6873349547386169},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.652296781539917},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6473962068557739},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5239296555519104},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.49244794249534607},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.489686518907547},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.472993940114975},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.46664121747016907},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.46520549058914185},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.43444231152534485},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.42718762159347534},{"id":"https://openalex.org/C2776175482","wikidata":"https://www.wikidata.org/wiki/Q1195816","display_name":"Transfer (computing)","level":2,"score":0.42502832412719727},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.40335315465927124},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10475406050682068},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.0},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/isbi53787.2023.10230361","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/isbi53787.2023.10230361","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE 20th International Symposium on Biomedical Imaging (ISBI)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2203.06363","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2203.06363","pdf_url":"https://arxiv.org/pdf/2203.06363","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2203.06363","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2203.06363","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"},{"id":"doi:10.17023/vfgp-5g60","is_oa":true,"landing_page_url":"https://doi.org/10.17023/vfgp-5g60","pdf_url":null,"source":{"id":"https://openalex.org/S7407051697","display_name":"IEEE RESOURCE CENTERS","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Audiovisual"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2203.06363","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2203.06363","pdf_url":"https://arxiv.org/pdf/2203.06363","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4221154441.pdf","grobid_xml":"https://content.openalex.org/works/W4221154441.grobid-xml"},"referenced_works_count":20,"referenced_works":["https://openalex.org/W2475287302","https://openalex.org/W2594179300","https://openalex.org/W2603777577","https://openalex.org/W2604737827","https://openalex.org/W2919070891","https://openalex.org/W2962785568","https://openalex.org/W2962793481","https://openalex.org/W2979448937","https://openalex.org/W2980138121","https://openalex.org/W3027069075","https://openalex.org/W3034600949","https://openalex.org/W3093389376","https://openalex.org/W3130570865","https://openalex.org/W4295101063","https://openalex.org/W6637373629","https://openalex.org/W6639824700","https://openalex.org/W6702130928","https://openalex.org/W6748481559","https://openalex.org/W6765779288","https://openalex.org/W6767071366"],"related_works":["https://openalex.org/W674670","https://openalex.org/W10029978","https://openalex.org/W6473745","https://openalex.org/W2893967","https://openalex.org/W15123885","https://openalex.org/W15292189","https://openalex.org/W2758677","https://openalex.org/W6421880","https://openalex.org/W12718294","https://openalex.org/W2356256"],"abstract_inverted_index":{"Deep":[0],"learning":[1,70],"models":[2,45],"tend":[3],"to":[4,96,118,130,188],"underperform":[5],"in":[6,57,197,215,227],"the":[7,38,64,67,77,98,123,133,138,141,150,178,190,198,221],"presence":[8],"of":[9,40,60,69,79,108,122,152,192,200,225],"domain":[10,25,127],"shifts.":[11],"Domain":[12],"transfer":[13,72,92,116,179],"has":[14],"recently":[15],"emerged":[16],"as":[17,181],"a":[18,24,90,109],"promising":[19],"approach":[20],"wherein":[21],"images":[22],"exhibiting":[23],"shift":[26],"are":[27],"transformed":[28],"into":[29],"other":[30],"domains":[31,81],"for":[32,185],"augmentation":[33],"or":[34],"adaptation.":[35],"However,":[36],"with":[37,76],"absence":[39],"paired":[41],"and":[42,51,82,113,126,160,203,223],"annotated":[43],"images,":[44],"merely":[46],"learned":[47],"by":[48],"adversarial":[49],"loss":[50,54],"cycle":[52],"consistency":[53,59],"could":[55,73,135,211],"result":[56],"poor":[58],"anatomy":[61,124],"structures":[62],"during":[63],"translation.":[65],"Additionally,":[66],"complexity":[68,139],"multi-domain":[71,91,228],"significantly":[74,136],"increase":[75],"number":[78],"target":[80],"source":[83],"images.":[84],"In":[85],"this":[86,131],"paper,":[87],"we":[88,155,176],"propose":[89],"network,":[93],"named":[94],"MDT-Net,":[95],"address":[97],"limitations":[99],"above":[100],"through":[101],"perceptual":[102],"supervision.":[103],"Specifically,":[104],"our":[105,153,157,193,209],"model":[106,134,158,194],"consists":[107],"single":[110],"encoder-decoder":[111],"network":[112],"multiple":[114,146],"domain-specific":[115],"modules":[117],"disentangle":[119],"feature":[120],"representations":[121],"content":[125],"variance.":[128],"Owing":[129],"architecture,":[132],"reduce":[137],"when":[140],"translation":[142],"is":[143],"conducted":[144],"among":[145],"domains.":[147],"To":[148],"demonstrate":[149],"performance":[151],"method,":[154],"evaluate":[156],"qualitatively":[159],"quantitatively":[161],"on":[162],"RETOUCH,":[163],"an":[164],"OCT":[165],"dataset":[166],"comprising":[167],"scans":[168],"from":[169],"three":[170],"different":[171],"scanner":[172],"devices":[173],"(domains).":[174],"Furthermore,":[175],"take":[177],"results":[180,206],"additional":[182],"training":[183],"data":[184,201],"fluid":[186],"segmentation":[187,217],"prove":[189],"advantage":[191],"indirectly,":[195],"i.e.,":[196],"task":[199],"adaptation":[202],"augmentation.":[204],"Experimental":[205],"show":[207],"that":[208],"method":[210],"bring":[212],"universal":[213],"improvement":[214],"these":[216],"tasks,":[218],"which":[219],"demonstrates":[220],"effectiveness":[222],"efficiency":[224],"MDT-Net":[226],"transfer.":[229]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2022-04-03T00:00:00"}