{"id":"https://openalex.org/W4417304481","doi":"https://doi.org/10.1109/tmi.2025.3643631","title":"Co-Seg++: Mutual Prompt-Guided Collaborative Learning for Versatile Medical Segmentation","display_name":"Co-Seg++: Mutual Prompt-Guided Collaborative Learning for Versatile Medical Segmentation","publication_year":2025,"publication_date":"2025-12-12","ids":{"openalex":"https://openalex.org/W4417304481","doi":"https://doi.org/10.1109/tmi.2025.3643631","pmid":"https://pubmed.ncbi.nlm.nih.gov/41385415"},"language":"en","primary_location":{"id":"doi:10.1109/tmi.2025.3643631","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmi.2025.3643631","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":true,"oa_status":"green","oa_url":"https://figshare.com/articles/journal_contribution/Co-Seg_Mutual_Prompt-Guided_Collaborative_Learning_for_Versatile_Medical_Segmentation/30861551","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102087196","display_name":"Qing Xu","orcid":null},"institutions":[{"id":"https://openalex.org/I13591777","display_name":"University of Nottingham Ningbo China","ror":"https://ror.org/03y4dt428","country_code":"CN","type":"education","lineage":["https://openalex.org/I13591777","https://openalex.org/I142263535"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qing Xu","raw_affiliation_strings":["School of Computer Science, University of Nottingham Ningbo China, Ningbo, Zhejiang, China"],"raw_orcid":"https://orcid.org/0000-0001-6898-0269","affiliations":[{"raw_affiliation_string":"School of Computer Science, University of Nottingham Ningbo China, Ningbo, Zhejiang, China","institution_ids":["https://openalex.org/I13591777"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100569167","display_name":"Yuxiang Luo","orcid":null},"institutions":[{"id":"https://openalex.org/I150744194","display_name":"Waseda University","ror":"https://ror.org/00ntfnx83","country_code":"JP","type":"education","lineage":["https://openalex.org/I150744194"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yuxiang Luo","raw_affiliation_strings":["Graduate School of Information, Production and Systems, Waseda University, Tokyo, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate School of Information, Production and Systems, Waseda University, Tokyo, Japan","institution_ids":["https://openalex.org/I150744194"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034115794","display_name":"Wenting Duan","orcid":"https://orcid.org/0000-0001-9665-4890"},"institutions":[{"id":"https://openalex.org/I33821262","display_name":"Lincoln University - Pennsylvania","ror":"https://ror.org/0521rfb23","country_code":"US","type":"education","lineage":["https://openalex.org/I33821262"]},{"id":"https://openalex.org/I51532219","display_name":"University of Lincoln","ror":"https://ror.org/03yeq9x20","country_code":"GB","type":"education","lineage":["https://openalex.org/I51532219"]}],"countries":["GB","US"],"is_corresponding":false,"raw_author_name":"Wenting Duan","raw_affiliation_strings":["School of Engineering and Physical Science, University of Lincoln, Lincoln, U.K"],"raw_orcid":"https://orcid.org/0000-0001-9665-4890","affiliations":[{"raw_affiliation_string":"School of Engineering and Physical Science, University of Lincoln, Lincoln, U.K","institution_ids":["https://openalex.org/I51532219","https://openalex.org/I33821262"]}]},{"author_position":"last","author":{"id":null,"display_name":"Zhen Chen","orcid":"https://orcid.org/0000-0003-0255-6435"},"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":"Zhen Chen","raw_affiliation_strings":["Department of Data Science and Artificial Intelligence, The Hong Kong Polytechnic University, Hung Hom, SAR, Hong Kong"],"raw_orcid":"https://orcid.org/0000-0003-0255-6435","affiliations":[{"raw_affiliation_string":"Department of Data Science and Artificial Intelligence, The Hong Kong Polytechnic University, Hung Hom, SAR, Hong Kong","institution_ids":["https://openalex.org/I14243506"]}]}],"institutions":[],"countries_distinct_count":5,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":7.1203,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.96890124,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":"45","issue":"5","first_page":"1947","last_page":"1959"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.5687999725341797,"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/T10862","display_name":"AI in cancer detection","score":0.5687999725341797,"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":0.11289999634027481,"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/T11363","display_name":"Dental Radiography and Imaging","score":0.094200000166893,"subfield":{"id":"https://openalex.org/subfields/3504","display_name":"Oral Surgery"},"field":{"id":"https://openalex.org/fields/35","display_name":"Dentistry"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.7870000004768372},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.6126000285148621},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.5931000113487244},{"id":"https://openalex.org/keywords/scale-space-segmentation","display_name":"Scale-space segmentation","score":0.5593000054359436},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.5185999870300293},{"id":"https://openalex.org/keywords/segmentation-based-object-categorization","display_name":"Segmentation-based object categorization","score":0.4968999922275543},{"id":"https://openalex.org/keywords/market-segmentation","display_name":"Market segmentation","score":0.4348999857902527},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.40369999408721924}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8567000031471252},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7870000004768372},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.6126000285148621},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5968000292778015},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.5931000113487244},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.5593000054359436},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.5185999870300293},{"id":"https://openalex.org/C25694479","wikidata":"https://www.wikidata.org/wiki/Q7446278","display_name":"Segmentation-based object categorization","level":5,"score":0.4968999922275543},{"id":"https://openalex.org/C125308379","wikidata":"https://www.wikidata.org/wiki/Q363057","display_name":"Market segmentation","level":2,"score":0.4348999857902527},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.40950000286102295},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.40369999408721924},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.3952000141143799},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.3718999922275543},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.3384000062942505},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.33719998598098755},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.3181000053882599},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.3001999855041504},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.29789999127388},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.29170000553131104},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.29159998893737793},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.2800000011920929},{"id":"https://openalex.org/C185874996","wikidata":"https://www.wikidata.org/wiki/Q269699","display_name":"Interdependence","level":2,"score":0.27219998836517334},{"id":"https://openalex.org/C2779097318","wikidata":"https://www.wikidata.org/wiki/Q2993446","display_name":"Connectomics","level":4,"score":0.26170000433921814},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2565999925136566}],"mesh":[{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"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":"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":"D014057","descriptor_name":"Tomography, X-Ray Computed","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D014057","descriptor_name":"Tomography, X-Ray Computed","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D014070","descriptor_name":"Tooth","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":false},{"descriptor_ui":"D014070","descriptor_name":"Tooth","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":false},{"descriptor_ui":"D016208","descriptor_name":"Databases, Factual","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016208","descriptor_name":"Databases, Factual","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":3,"locations":[{"id":"doi:10.1109/tmi.2025.3643631","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmi.2025.3643631","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:41385415","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/41385415","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},{"id":"pmh:oai:figshare.com:article/30861551","is_oa":true,"landing_page_url":"https://figshare.com/articles/journal_contribution/Co-Seg_Mutual_Prompt-Guided_Collaborative_Learning_for_Versatile_Medical_Segmentation/30861551","pdf_url":null,"source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"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"}],"best_oa_location":{"id":"pmh:oai:figshare.com:article/30861551","is_oa":true,"landing_page_url":"https://figshare.com/articles/journal_contribution/Co-Seg_Mutual_Prompt-Guided_Collaborative_Learning_for_Versatile_Medical_Segmentation/30861551","pdf_url":null,"source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"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":[{"id":"https://openalex.org/G6350940726","display_name":null,"funder_award_id":"202508330191","funder_id":"https://openalex.org/F4320322725","funder_display_name":"China Scholarship Council"}],"funders":[{"id":"https://openalex.org/F4320322725","display_name":"China Scholarship Council","ror":"https://ror.org/04atp4p48"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Medical":[0],"image":[1,51,103],"analysis":[2],"is":[3,169],"critical":[4],"yet":[5],"challenged":[6],"by":[7],"the":[8,37,122,145,151],"need":[9],"of":[10,125,157],"jointly":[11,128],"segmenting":[12],"organs":[13],"or":[14],"tissues,":[15,162],"and":[16,22,48,75,96,102,131,140,154,163],"numerous":[17],"instances":[18],"for":[19,62],"anatomical":[20,159],"structures":[21],"tumor":[23],"microenvironment":[24],"analysis.":[25],"Existing":[26],"studies":[27],"typically":[28],"formulated":[29],"different":[30],"segmentation":[31,46,77,100,133,156],"tasks":[32,78],"in":[33,150],"isolation,":[34],"which":[35],"overlooks":[36],"fundamental":[38],"interdependencies":[39],"between":[40,99],"these":[41],"tasks,":[42,127],"leading":[43],"to":[44,79,92,120],"suboptimal":[45],"performance":[47],"insufficient":[49],"medical":[50,64],"understanding.":[52],"To":[53],"address":[54],"this":[55],"issue,":[56],"we":[57,67,110],"propose":[58],"a":[59,69,87,112],"Co-Seg++":[60,147],"framework":[61],"versatile":[63],"segmentation.":[65],"Specifically,":[66],"introduce":[68],"novel":[70],"co-segmentation":[71],"paradigm,":[72],"allowing":[73],"semantic":[74,130],"instance":[76,132],"mutually":[80],"enhance":[81],"each":[82],"other.":[83],"We":[84],"first":[85],"devise":[86,111],"spatio-sequential":[88],"prompt":[89],"encoder":[90],"(SSP-Encoder)":[91],"capture":[93],"long-range":[94],"spatial":[95,107],"sequential":[97],"relationships":[98],"regions":[101],"embeddings":[104],"as":[105],"prior":[106],"constraints.":[108],"Moreover,":[109],"multi-task":[113],"collaborative":[114],"decoder":[115],"(MTC-Decoder)":[116],"that":[117,144],"leverages":[118],"cross-guidance":[119],"strengthen":[121],"contextual":[123],"consistency":[124],"both":[126],"computing":[129],"masks.":[134],"Extensive":[135],"experiments":[136],"on":[137],"diverse":[138],"CT":[139],"histopathology":[141,161],"datasets":[142],"demonstrate":[143],"proposed":[146],"outperforms":[148],"state-of-the-arts":[149],"semantic,":[152],"instance,":[153],"panoptic":[155],"dental":[158],"structures,":[160],"nuclei":[164],"instances.":[165],"The":[166],"source":[167],"code":[168],"available":[170],"at":[171],"https://github.com/xq141839/Co-Seg-Plus.":[172]},"counts_by_year":[{"year":2026,"cited_by_count":5}],"updated_date":"2026-07-08T08:33:18.762332","created_date":"2025-10-10T00:00:00"}
