{"id":"https://openalex.org/W4402352065","doi":"https://doi.org/10.1109/ijcnn60899.2024.10650546","title":"Class-aware Patch Based Contrastive Learning for Medical Image Segmentation","display_name":"Class-aware Patch Based Contrastive Learning for Medical Image Segmentation","publication_year":2024,"publication_date":"2024-06-30","ids":{"openalex":"https://openalex.org/W4402352065","doi":"https://doi.org/10.1109/ijcnn60899.2024.10650546"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn60899.2024.10650546","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn60899.2024.10650546","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-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/A5100518821","display_name":"Shaozhi Wu","orcid":"https://orcid.org/0000-0001-5466-8119"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shaozhi Wu","raw_affiliation_strings":["University of Electronic Science and Technology of China,Yangtze Delta Region Institute (Quzhou),Quzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China,Yangtze Delta Region Institute (Quzhou),Quzhou,China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100452614","display_name":"Han Li","orcid":"https://orcid.org/0000-0003-0276-9756"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Han Li","raw_affiliation_strings":["University of Electronic Science and Technology of China,Yangtze Delta Region Institute (Quzhou),Quzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China,Yangtze Delta Region Institute (Quzhou),Quzhou,China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114009038","display_name":"Xingang Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xingang Liu","raw_affiliation_strings":["University of Electronic Science and Technology of China,School of Information and Communication Engineering,Chengdu,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China,School of Information and Communication Engineering,Chengdu,China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103082122","display_name":"Dan Tian","orcid":"https://orcid.org/0000-0002-0104-8976"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dan Tian","raw_affiliation_strings":["University of Electronic Science and Technology of China,School of Information and Communication Engineering,Chengdu,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China,School of Information and Communication Engineering,Chengdu,China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103029832","display_name":"Han Su","orcid":"https://orcid.org/0000-0001-5579-0378"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Han Su","raw_affiliation_strings":["University of Electronic Science and Technology of China,Yangtze Delta Region Institute (Quzhou),Chengdu,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China,Yangtze Delta Region Institute (Quzhou),Chengdu,China","institution_ids":["https://openalex.org/I150229711"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.3055,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.64403159,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"9"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9995999932289124,"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"}},"topics":[{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9995999932289124,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9984999895095825,"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9972000122070312,"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/computer-science","display_name":"Computer science","score":0.7501223683357239},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6519616842269897},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.6030470728874207},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.5542603135108948},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5361122488975525},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.49970531463623047},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.45008179545402527},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3930491805076599},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.33498215675354004}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7501223683357239},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6519616842269897},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.6030470728874207},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.5542603135108948},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5361122488975525},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.49970531463623047},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.45008179545402527},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3930491805076599},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.33498215675354004}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn60899.2024.10650546","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn60899.2024.10650546","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":46,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W2431080869","https://openalex.org/W2887997457","https://openalex.org/W2917551568","https://openalex.org/W2953070460","https://openalex.org/W2962804657","https://openalex.org/W2962914239","https://openalex.org/W2963073217","https://openalex.org/W2979888373","https://openalex.org/W2979907638","https://openalex.org/W2982043723","https://openalex.org/W3024821730","https://openalex.org/W3035524453","https://openalex.org/W3035680157","https://openalex.org/W3044738063","https://openalex.org/W3083779147","https://openalex.org/W3090844657","https://openalex.org/W3097499499","https://openalex.org/W3102363610","https://openalex.org/W3108938817","https://openalex.org/W3113328489","https://openalex.org/W3157653192","https://openalex.org/W3168822201","https://openalex.org/W3171007011","https://openalex.org/W3171581326","https://openalex.org/W3194662286","https://openalex.org/W3216275916","https://openalex.org/W4214481550","https://openalex.org/W4221143093","https://openalex.org/W4287755086","https://openalex.org/W4297808394","https://openalex.org/W4323924189","https://openalex.org/W4378640398","https://openalex.org/W4386624959","https://openalex.org/W4387422830","https://openalex.org/W4389910970","https://openalex.org/W4399512996","https://openalex.org/W4400525960","https://openalex.org/W6682948231","https://openalex.org/W6717772578","https://openalex.org/W6733814495","https://openalex.org/W6762573206","https://openalex.org/W6774314701","https://openalex.org/W6778102432","https://openalex.org/W6779992872","https://openalex.org/W6780191644"],"related_works":["https://openalex.org/W4379231730","https://openalex.org/W4389858081","https://openalex.org/W2501551404","https://openalex.org/W4385583601","https://openalex.org/W4298131179","https://openalex.org/W2113201962","https://openalex.org/W4395685956","https://openalex.org/W2799953226","https://openalex.org/W4398146871","https://openalex.org/W1522196789"],"abstract_inverted_index":{"For":[0],"medical":[1,136],"image":[2,76,137,159],"segmentation,":[3],"contrastive":[4,41,97,133,145,226,251],"learning":[5,42,98,125,134,252],"recently":[6],"becomes":[7],"the":[8,13,22,47,58,66,74,90,104,154,162,174,188,204,220,238,247],"dominant":[9],"method":[10,243],"to":[11,65,112,117,186,197,212,246],"get":[12],"class-separated":[14],"visual":[15],"representations":[16],"by":[17,152,191],"pulling":[18],"augmented":[19,33],"views":[20,34],"of":[21,35,49,73,195,200,210,222,240],"same":[23,59,75,105],"samples":[24],"closer":[25],"in":[26,95,99,132,173,225],"a":[27,122,143,180,207,213],"representation":[28],"space,":[29],"and":[30,80,157,170,218,250],"pushing":[31],"apart":[32],"different":[36,193,198],"samples.":[37,88],"However,":[38],"most":[39],"current":[40],"methods":[43],"may":[44],"suffer":[45],"from":[46,57,103,234],"issue":[48,221],"class":[50,60,106,215,223],"collision":[51,224],"because":[52],"those":[53],"images":[54,83],"(pixels)":[55],"that":[56,100],"are":[61,84,107],"forcefully":[62],"contrasted":[63],"due":[64],"pretext":[67],"task":[68],"simply":[69],"takes":[70],"another":[71],"augmentation":[72,131,184],"as":[77,86,109,244],"positive":[78],"pairs":[79,111],"all":[81],"other":[82],"view":[85],"negative":[87,110],"Moreover,":[89],"problem":[91],"looks":[92],"more":[93,216],"serious":[94],"pixel-level":[96],"massive":[101],"pixels":[102],"viewed":[108],"differ":[113],"is":[114],"intolerable.":[115],"Therefore,":[116],"alleviate":[118],"this,":[119],"we":[120,165],"propose":[121,142],"novel":[123,144,163],"semi-supervised":[124,249],"framework":[126],"based":[127,148],"on":[128,149,229],"hierarchical":[129,182,189],"data":[130,183],"for":[135],"segmentation.":[138],"Specifically,":[139],"We":[140,177],"first":[141],"loss":[146],"function":[147],"class-aware":[150],"patch":[151],"using":[153],"pseudo":[155],"labels":[156],"source":[158],"effectively.":[160],"With":[161],"loss,":[164],"learn":[166,187],"better":[167],"intra-class":[168],"compactness":[169],"inter-class":[171],"separability":[172],"feature":[175],"space.":[176],"then":[178],"introduce":[179],"patch-based":[181],"module":[185],"invariance":[190],"applying":[192],"strength":[194],"augment":[196],"probability":[199,209],"patches,":[201],"thus":[202],"making":[203],"patches":[205],"with":[206],"high":[208],"belong":[211],"certain":[214],"alike":[217],"avoiding":[219],"learning.":[227],"Experiments":[228],"several":[230],"public":[231],"accessible":[232],"datasets":[233],"multiple":[235],"domains":[236],"reveals":[237],"superiority":[239],"our":[241],"proposed":[242],"compared":[245],"state-of-the-art":[248],"methods.":[253]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}