{"id":"https://openalex.org/W4403447271","doi":"https://doi.org/10.1109/tim.2024.3481581","title":"Pseudosupervision With Contrast\u2013Separation Awareness in Endoscopy Image Segmentation","display_name":"Pseudosupervision With Contrast\u2013Separation Awareness in Endoscopy Image Segmentation","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4403447271","doi":"https://doi.org/10.1109/tim.2024.3481581"},"language":"en","primary_location":{"id":"doi:10.1109/tim.2024.3481581","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2024.3481581","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"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 Instrumentation and Measurement","raw_type":"journal-article"},"type":"article","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/A5026540573","display_name":"Huisi Wu","orcid":"https://orcid.org/0000-0002-0399-9089"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huisi Wu","raw_affiliation_strings":["College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0002-0399-9089","affiliations":[{"raw_affiliation_string":"College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Jiahao Li","orcid":"https://orcid.org/0000-0003-3612-1667"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiahao Li","raw_affiliation_strings":["College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0003-3612-1667","affiliations":[{"raw_affiliation_string":"College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5005393674","display_name":"Jing Qin","orcid":"https://orcid.org/0000-0002-2961-0860"},"institutions":[{"id":"https://openalex.org/I14243506","display_name":"Hong Kong Polytechnic University","ror":"https://ror.org/0030zas98","country_code":"HK","type":"education","lineage":["https://openalex.org/I14243506"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Jing Qin","raw_affiliation_strings":["Centre for Smart Health, School of Nursing, The Hong Kong Polytechnic University, Kowloon, Hong Kong","School of Nursing, Centre for Smart Health, The Hong Kong Polytechnic University, Kowloon, Hong Kong, China"],"raw_orcid":"https://orcid.org/0000-0002-2961-0860","affiliations":[{"raw_affiliation_string":"Centre for Smart Health, School of Nursing, The Hong Kong Polytechnic University, Kowloon, Hong Kong","institution_ids":["https://openalex.org/I14243506"]},{"raw_affiliation_string":"School of Nursing, Centre for Smart Health, The Hong Kong Polytechnic University, Kowloon, Hong Kong, China","institution_ids":["https://openalex.org/I14243506"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.16560526,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"73","issue":null,"first_page":"1","last_page":"12"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9571999907493591,"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9571999907493591,"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/contrast","display_name":"Contrast (vision)","score":0.6835269927978516},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6451585292816162},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6190858483314514},{"id":"https://openalex.org/keywords/separation","display_name":"Separation (statistics)","score":0.556517481803894},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.5334480404853821},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.49686339497566223},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.4905702471733093},{"id":"https://openalex.org/keywords/endoscopy","display_name":"Endoscopy","score":0.42763060331344604},{"id":"https://openalex.org/keywords/radiology","display_name":"Radiology","score":0.15143418312072754},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.13037648797035217}],"concepts":[{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.6835269927978516},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6451585292816162},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6190858483314514},{"id":"https://openalex.org/C2776061190","wikidata":"https://www.wikidata.org/wiki/Q7451805","display_name":"Separation (statistics)","level":2,"score":0.556517481803894},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5334480404853821},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.49686339497566223},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.4905702471733093},{"id":"https://openalex.org/C2778451229","wikidata":"https://www.wikidata.org/wiki/Q212809","display_name":"Endoscopy","level":2,"score":0.42763060331344604},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.15143418312072754},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.13037648797035217},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tim.2024.3481581","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2024.3481581","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"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 Instrumentation and Measurement","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4206905956","display_name":null,"funder_award_id":"2024A1515011946","funder_id":"https://openalex.org/F4320321921","funder_display_name":"Natural Science Foundation of Guangdong Province"},{"id":"https://openalex.org/G6694410858","display_name":null,"funder_award_id":"62273241","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321921","display_name":"Natural Science Foundation of Guangdong Province","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":61,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W2008359794","https://openalex.org/W2021088830","https://openalex.org/W2034269173","https://openalex.org/W2096733369","https://openalex.org/W2117539524","https://openalex.org/W2138621090","https://openalex.org/W2153125812","https://openalex.org/W2157364932","https://openalex.org/W2194775991","https://openalex.org/W2466942361","https://openalex.org/W2560023338","https://openalex.org/W2703741708","https://openalex.org/W2842511635","https://openalex.org/W2884436604","https://openalex.org/W2997286550","https://openalex.org/W3012248522","https://openalex.org/W3033428961","https://openalex.org/W3034930876","https://openalex.org/W3035524453","https://openalex.org/W3035680157","https://openalex.org/W3082604781","https://openalex.org/W3090492687","https://openalex.org/W3102628144","https://openalex.org/W3107695429","https://openalex.org/W3110002552","https://openalex.org/W3120562181","https://openalex.org/W3162410350","https://openalex.org/W3164631742","https://openalex.org/W3177634011","https://openalex.org/W3181871665","https://openalex.org/W3202263958","https://openalex.org/W3203434372","https://openalex.org/W3204025806","https://openalex.org/W3206203595","https://openalex.org/W3216275916","https://openalex.org/W4221144896","https://openalex.org/W4221161877","https://openalex.org/W4226502176","https://openalex.org/W4280521332","https://openalex.org/W4295916856","https://openalex.org/W4295934810","https://openalex.org/W4296119467","https://openalex.org/W4297094919","https://openalex.org/W4299652825","https://openalex.org/W4312692325","https://openalex.org/W4360981268","https://openalex.org/W4386075748","https://openalex.org/W4390307178","https://openalex.org/W6730323794","https://openalex.org/W6739696289","https://openalex.org/W6743428213","https://openalex.org/W6750469568","https://openalex.org/W6772553744","https://openalex.org/W6774224378","https://openalex.org/W6776411772","https://openalex.org/W6776782944","https://openalex.org/W6779101013","https://openalex.org/W6779992872","https://openalex.org/W6784265214","https://openalex.org/W6794152581"],"related_works":["https://openalex.org/W2071676784","https://openalex.org/W2069592018","https://openalex.org/W4292513318","https://openalex.org/W2075740387","https://openalex.org/W2358990940","https://openalex.org/W4308092240","https://openalex.org/W2287611352","https://openalex.org/W2093931120","https://openalex.org/W320684304","https://openalex.org/W1522196789"],"abstract_inverted_index":{"Endoscopy":[0],"is":[1,20],"a":[2,115,149,174],"noninvasive":[3],"and":[4,26,54,69,102,140,163,184],"effective":[5,181],"diagnostic":[6],"technique":[7],"for":[8,45,105,156],"detecting":[9],"intestinal":[10],"lesions,":[11],"but":[12],"accurately":[13,52],"segmenting":[14],"these":[15,37],"lesions":[16,109],"from":[17],"endoscopy":[18,47,111,201],"images":[19],"challenging":[21],"due":[22],"to":[23,96,153,179],"low":[24],"contrast":[25],"blurred":[27],"boundaries,":[28],"as":[29,31],"well":[30],"limited":[32],"annotated":[33],"data.":[34],"To":[35],"address":[36],"challenges,":[38],"this":[39],"article":[40],"proposes":[41],"an":[42],"innovative":[43],"approach":[44],"semisupervised":[46],"image":[48],"segmentation":[49,187,191,218],"that":[50,135,207],"can":[51],"identify":[53],"segment":[55],"lesions.":[56],"The":[57,193,203],"core":[58],"idea":[59],"revolves":[60],"around":[61],"the":[62,86,91,108,125,133,144,168,186,208],"distinction":[63],"in":[64,110,215],"semantic":[65],"information":[66],"between":[67],"foreground":[68,101,162],"background":[70,103,164],"regions.":[71],"Lesion":[72],"areas":[73,137],"sharing":[74],"similar":[75,136],"colors":[76],"or":[77],"backgrounds":[78],"with":[79],"comparable":[80],"appearances":[81],"exhibit":[82],"analogous":[83],"representations":[84,104,183],"within":[85],"feature":[87,98,121,165,182],"space.":[88],"We":[89,113],"propose":[90],"adaptive":[92],"separative":[93],"module":[94],"(ASM)":[95],"separate":[97],"maps":[99],"into":[100],"better":[106],"distinguishing":[107],"images.":[112],"introduce":[114],"rank":[116],"weighting":[117],"method":[118,195,210],"based":[119,131],"on":[120,132,198],"similarity,":[122],"which":[123],"mitigates":[124],"impact":[126],"of":[127,138,170,217],"dissimilar":[128],"representations.":[129,166],"Additionally,":[130],"fact":[134],"labeled":[139,161],"unlabeled":[141,157],"data":[142,158],"contain":[143],"same":[145],"semantics,":[146],"we":[147,172],"develop":[148],"pseudosupervision":[150],"mechanism":[151],"(PSM)":[152],"generate":[154],"pseudolabels":[155],"by":[159],"utilizing":[160],"Considering":[167],"consistency":[169],"pseudolabel,":[171],"design":[173],"density-based":[175],"class":[176],"entropy":[177],"scheme":[178],"mine":[180],"boost":[185],"performance":[188],"further":[189],"enhancing":[190],"results.":[192],"proposed":[194,209],"was":[196],"evaluated":[197],"four":[199],"benchmark":[200],"datasets.":[202],"experimental":[204],"results":[205],"show":[206],"outperforms":[211],"other":[212],"state-of-the-art":[213],"methods":[214],"terms":[216],"accuracy.":[219]},"counts_by_year":[],"updated_date":"2025-12-27T23:08:20.325037","created_date":"2025-10-10T00:00:00"}
