{"id":"https://openalex.org/W4401795648","doi":"https://doi.org/10.1109/isbi56570.2024.10635274","title":"SEMI-CONTRANS: Semi-Supervised Medical Image Segmentation via Multi-Scale Feature Fusion and Cross Teaching of CNN and Transformer","display_name":"SEMI-CONTRANS: Semi-Supervised Medical Image Segmentation via Multi-Scale Feature Fusion and Cross Teaching of CNN and Transformer","publication_year":2024,"publication_date":"2024-05-27","ids":{"openalex":"https://openalex.org/W4401795648","doi":"https://doi.org/10.1109/isbi56570.2024.10635274"},"language":"en","primary_location":{"id":"doi:10.1109/isbi56570.2024.10635274","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi56570.2024.10635274","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Symposium on Biomedical Imaging (ISBI)","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/A5102020832","display_name":"Weiren Zhao","orcid":"https://orcid.org/0000-0003-2275-5714"},"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":"Weiren Zhao","raw_affiliation_strings":["University of Electronic Science and Technology of China,School of Computer Science and Engineering,Chengdu,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China,School of Computer Science and Engineering,Chengdu,China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042832520","display_name":"Lanfeng Zhong","orcid":"https://orcid.org/0009-0004-3570-382X"},"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":"Lanfeng Zhong","raw_affiliation_strings":["University of Electronic Science and Technology of China,School of Mechanical and Electrical Engineering,Chengdu,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China,School of Mechanical and Electrical Engineering,Chengdu,China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5029722566","display_name":"Guotai Wang","orcid":"https://orcid.org/0000-0002-8632-158X"},"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":"Guotai Wang","raw_affiliation_strings":["University of Electronic Science and Technology of China,School of Mechanical and Electrical Engineering,Chengdu,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China,School of Mechanical and Electrical Engineering,Chengdu,China","institution_ids":["https://openalex.org/I150229711"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I150229711"],"apc_list":null,"apc_paid":null,"fwci":0.6281,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.69315414,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12702","display_name":"Brain Tumor Detection and Classification","score":0.9225000143051147,"subfield":{"id":"https://openalex.org/subfields/2808","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T12702","display_name":"Brain Tumor Detection and Classification","score":0.9225000143051147,"subfield":{"id":"https://openalex.org/subfields/2808","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7157109975814819},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6723707318305969},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.5846121311187744},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5719214081764221},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.5210922956466675},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5175535082817078},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5030967593193054},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.4606940448284149},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.42956772446632385},{"id":"https://openalex.org/keywords/scale-space-segmentation","display_name":"Scale-space segmentation","score":0.41269195079803467},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.08382683992385864}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7157109975814819},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6723707318305969},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5846121311187744},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5719214081764221},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.5210922956466675},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5175535082817078},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5030967593193054},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.4606940448284149},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.42956772446632385},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.41269195079803467},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08382683992385864},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"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/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isbi56570.2024.10635274","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi56570.2024.10635274","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Symposium on Biomedical Imaging (ISBI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W2804047627","https://openalex.org/W2953070460","https://openalex.org/W2962804657","https://openalex.org/W2979907638","https://openalex.org/W2996290406","https://openalex.org/W3035680157","https://openalex.org/W3171581326","https://openalex.org/W3174864715","https://openalex.org/W3209458476","https://openalex.org/W4282935002","https://openalex.org/W4319444096","https://openalex.org/W4387211627","https://openalex.org/W6733814495","https://openalex.org/W6754852571","https://openalex.org/W6784333009","https://openalex.org/W6795435739","https://openalex.org/W6810755270"],"related_works":["https://openalex.org/W1986655823","https://openalex.org/W2185902295","https://openalex.org/W2103507220","https://openalex.org/W3144569342","https://openalex.org/W3011384228","https://openalex.org/W2945274617","https://openalex.org/W3199300986","https://openalex.org/W4313052709","https://openalex.org/W4298131179","https://openalex.org/W2375430703"],"abstract_inverted_index":{"Convolutional":[0],"Neural":[1],"Networks":[2],"(CNNs)":[3],"and":[4,41,62,68,81,109],"Transformers":[5,63,88],"have":[6],"achieved":[7],"promising":[8,30],"results":[9],"in":[10,87,89,100],"fully":[11],"supervised":[12],"medical":[13,21],"image":[14],"segmentation.":[15,73],"However,":[16],"acquiring":[17],"high-quality":[18],"annotations":[19],"for":[20,44,71,117,125],"images":[22,43,137,152],"is":[23],"prohibitively":[24],"expensive,":[25],"making":[26],"semi-supervised":[27,72,160],"learning":[28],"a":[29,51,90,106,110],"way":[31],"to":[32,75],"reduce":[33],"the":[34,58,101,132,144],"annotation":[35],"cost":[36],"by":[37,153],"leveraging":[38],"both":[39],"labeled":[40,151],"unlabeled":[42,128,155],"training.":[45],"In":[46],"this":[47],"work,":[48],"we":[49,93,104],"propose":[50],"novel":[52],"model":[53],"named":[54],"Semi-ConTrans":[55],"that":[56,139],"unifies":[57],"advantages":[59],"of":[60,85,135],"CNNs":[61,80],"through":[64],"multi-scale":[65],"feature":[66],"fusion":[67],"cross":[69,118],"teaching":[70],"Specifically,":[74],"leverage":[76],"localization":[77],"capability":[78],"from":[79],"global":[82],"context":[83],"modeling":[84],"self-attention":[86],"unified":[91],"framework,":[92],"adaptively":[94],"fuse":[95],"them":[96],"at":[97],"multiple":[98],"scales":[99],"encoder.":[102],"Furthermore,":[103],"use":[105],"CNN":[107],"decoder":[108,112],"Transformer":[111],"with":[113,127,146],"different":[114],"decision":[115],"boundaries":[116],"teaching,":[119],"obtaining":[120],"more":[121],"holistic":[122],"pseudo":[123],"labels":[124],"dealing":[126],"images.":[129],"Experiments":[130],"on":[131],"ACDC":[133],"dataset":[134],"cardiac":[136],"demonstrate":[138],"our":[140],"approach":[141],"greatly":[142],"improves":[143],"performance":[145],"only":[147],"10%":[148],"or":[149],"20%":[150],"exploiting":[154],"images,":[156],"outperforming":[157],"eight":[158],"state-of-the-art":[159],"segmentation":[161],"methods.":[162]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}
