{"id":"https://openalex.org/W4406259815","doi":"https://doi.org/10.1109/bibm62325.2024.10822668","title":"MMPL-Seg: Prompt Learning with Missing Modalities for Medical Segmentation","display_name":"MMPL-Seg: Prompt Learning with Missing Modalities for Medical Segmentation","publication_year":2024,"publication_date":"2024-12-03","ids":{"openalex":"https://openalex.org/W4406259815","doi":"https://doi.org/10.1109/bibm62325.2024.10822668"},"language":"en","primary_location":{"id":"doi:10.1109/bibm62325.2024.10822668","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm62325.2024.10822668","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","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/A5069410522","display_name":"Ruowen Qu","orcid":null},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Ruowen Qu","raw_affiliation_strings":["South China University of Technology,School of Electronic and Information Engineering,Guangzhou,China"],"affiliations":[{"raw_affiliation_string":"South China University of Technology,School of Electronic and Information Engineering,Guangzhou,China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052774438","display_name":"Wenxuan Wu","orcid":"https://orcid.org/0000-0001-5459-8990"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenxuan Wu","raw_affiliation_strings":["South China University of Technology,School of Electronic and Information Engineering,Guangzhou,China"],"affiliations":[{"raw_affiliation_string":"South China University of Technology,School of Electronic and Information Engineering,Guangzhou,China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108894742","display_name":"Yeyi Guan","orcid":null},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yeyi Guan","raw_affiliation_strings":["South China University of Technology,School of Electronic and Information Engineering,Guangzhou,China"],"affiliations":[{"raw_affiliation_string":"South China University of Technology,School of Electronic and Information Engineering,Guangzhou,China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5113985606","display_name":"Lin Shu","orcid":null},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lin Shu","raw_affiliation_strings":["South China University of Technology Pazhou Lab,School of Future Technology,Guangzhou,China"],"affiliations":[{"raw_affiliation_string":"South China University of Technology Pazhou Lab,School of Future Technology,Guangzhou,China","institution_ids":["https://openalex.org/I90610280"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5069410522"],"corresponding_institution_ids":["https://openalex.org/I90610280"],"apc_list":null,"apc_paid":null,"fwci":0.3616,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.7072286,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"5053","last_page":"5058"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.9898999929428101,"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":0.9898999929428101,"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/T13702","display_name":"Machine Learning in Healthcare","score":0.9769999980926514,"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/T11396","display_name":"Artificial Intelligence in Healthcare","score":0.9739999771118164,"subfield":{"id":"https://openalex.org/subfields/3605","display_name":"Health Information Management"},"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":0.70389324426651},{"id":"https://openalex.org/keywords/modalities","display_name":"Modalities","score":0.6671283841133118},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5925875902175903},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.569003164768219},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4406081736087799},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.35003358125686646}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.70389324426651},{"id":"https://openalex.org/C2779903281","wikidata":"https://www.wikidata.org/wiki/Q6888026","display_name":"Modalities","level":2,"score":0.6671283841133118},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5925875902175903},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.569003164768219},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4406081736087799},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.35003358125686646},{"id":"https://openalex.org/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bibm62325.2024.10822668","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm62325.2024.10822668","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W3164581645","https://openalex.org/W3176031707","https://openalex.org/W3176404283","https://openalex.org/W3186033197","https://openalex.org/W3216551675","https://openalex.org/W4200631575","https://openalex.org/W4205512907","https://openalex.org/W4308235625","https://openalex.org/W4312533035","https://openalex.org/W4312980231","https://openalex.org/W4321232185","https://openalex.org/W4372260366","https://openalex.org/W4382998948","https://openalex.org/W4385700958","https://openalex.org/W4386057714","https://openalex.org/W4387211388","https://openalex.org/W4387211904","https://openalex.org/W4390017704","https://openalex.org/W4392903022","https://openalex.org/W4394625631","https://openalex.org/W6750469568","https://openalex.org/W6755207826","https://openalex.org/W6789753369","https://openalex.org/W6791353385"],"related_works":["https://openalex.org/W2772917594","https://openalex.org/W2036807459","https://openalex.org/W2058170566","https://openalex.org/W2755342338","https://openalex.org/W2166024367","https://openalex.org/W3116076068","https://openalex.org/W2229312674","https://openalex.org/W2951359407","https://openalex.org/W2079911747","https://openalex.org/W1969923398"],"abstract_inverted_index":{"Using":[0],"text":[1],"prompts":[2,44],"has":[3],"been":[4],"proven":[5],"helpful":[6],"in":[7,37,127],"improving":[8],"medical":[9,43,54],"segmentation":[10,14],"performance.":[11],"However,":[12],"text-prompted":[13],"of":[15,108,111,144,160],"the":[16,29,81,128,135,163,169],"pulmonary":[17],"infectious":[18],"areas":[19],"is":[20,32,96],"a":[21,65,88,158],"challenging":[22],"task,":[23],"for":[24,68,74,98],"two":[25,109],"major":[26],"reasons:":[27],"(i)":[28],"infected":[30],"area":[31],"prone":[33],"to":[34,121,140],"misjudgment,":[35],"resulting":[36],"under-segmentation":[38],"or":[39],"over-segmentation,":[40],"(ii)":[41],"full":[42],"are":[45],"expensive,":[46],"especially":[47],"during":[48,50],"real-world":[49],"testing,":[51],"so":[52],"missing":[53,182],"note":[55],"modality":[56,183],"often":[57],"occurs.":[58],"To":[59,152],"address":[60],"these":[61],"issues,":[62],"we":[63,85,133,156],"propose":[64],"new":[66],"method":[67],"Prompt":[69],"Learning":[70],"with":[71],"Missing":[72],"Modalities":[73],"Medical":[75],"Segmentation":[76],"(MMPL-Seg).":[77],"Specifically,":[78],"based":[79],"on":[80,105,162,168],"UNet-like":[82],"encoder-decoder":[83],"framework,":[84],"first":[86],"introduce":[87],"Modality":[89],"Reconstruction":[90],"and":[91,101,113,181,189],"Fusion":[92],"module":[93,117],"(MRF),":[94],"which":[95],"suitable":[97],"both":[99],"complete":[100,180],"incomplete":[102],"modalities.":[103],"Based":[104],"joint":[106],"training":[107],"branches":[110],"image-only":[112,119],"image-text":[114,146],"pairs,":[115],"this":[116],"enables":[118],"samples":[120],"also":[122],"have":[123],"latent":[124],"semantic":[125],"information":[126],"test":[129],"phase.":[130],"In":[131],"addition,":[132],"use":[134],"Dynamic":[136],"Convolution":[137],"Layer":[138],"(DyConv)":[139],"achieve":[141],"dynamic":[142],"fusion":[143],"deep":[145],"features":[147],"into":[148],"shallow":[149],"edge":[150],"layers.":[151],"validate":[153],"our":[154,174],"idea,":[155],"conduct":[157],"series":[159],"experiments":[161],"QaTa-COV19":[164,170],"multi-modality":[165],"dataset.":[166],"Experiments":[167],"dataset":[171],"demonstrated":[172],"that":[173],"model":[175],"outperforms":[176],"state-of-the-art":[177],"approaches":[178],"under":[179],"scenarios,":[184],"proving":[185],"its":[186],"high":[187],"performance":[188],"robustness.":[190]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-03-12T08:34:05.389933","created_date":"2025-10-10T00:00:00"}