{"id":"https://openalex.org/W4406260028","doi":"https://doi.org/10.1109/bibm62325.2024.10822080","title":"Multi-rater Prompting for Ambiguous Medical Image Segmentation","display_name":"Multi-rater Prompting for Ambiguous Medical Image Segmentation","publication_year":2024,"publication_date":"2024-12-03","ids":{"openalex":"https://openalex.org/W4406260028","doi":"https://doi.org/10.1109/bibm62325.2024.10822080"},"language":"en","primary_location":{"id":"doi:10.1109/bibm62325.2024.10822080","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm62325.2024.10822080","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":"conference-paper","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/A5100775332","display_name":"Jinhong Wang","orcid":"https://orcid.org/0000-0002-0012-7218"},"institutions":[{"id":"https://openalex.org/I168879160","display_name":"Zhejiang University of Science and Technology","ror":"https://ror.org/05mx0wr29","country_code":"CN","type":"education","lineage":["https://openalex.org/I168879160"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinhong Wang","raw_affiliation_strings":["Zhejiang University,College of Computer Science and Technology,Hangzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang University,College of Computer Science and Technology,Hangzhou,China","institution_ids":["https://openalex.org/I168879160"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110459459","display_name":"Yi Cheng","orcid":null},"institutions":[{"id":"https://openalex.org/I45928872","display_name":"Alibaba Group (China)","ror":"https://ror.org/00k642b80","country_code":"CN","type":"company","lineage":["https://openalex.org/I45928872"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yi Cheng","raw_affiliation_strings":["Alibaba Group,Hangzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Alibaba Group,Hangzhou,China","institution_ids":["https://openalex.org/I45928872"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023258354","display_name":"Jintai Chen","orcid":"https://orcid.org/0000-0002-3199-2597"},"institutions":[{"id":"https://openalex.org/I157725225","display_name":"University of Illinois Urbana-Champaign","ror":"https://ror.org/047426m28","country_code":"US","type":"education","lineage":["https://openalex.org/I157725225"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jintai Chen","raw_affiliation_strings":["University of Illinois at Urbana-Champaign,Urbana-Champaign,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Illinois at Urbana-Champaign,Urbana-Champaign,USA","institution_ids":["https://openalex.org/I157725225"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101880727","display_name":"Hongxia Xu","orcid":"https://orcid.org/0000-0001-5384-4627"},"institutions":[{"id":"https://openalex.org/I4210123185","display_name":"Zhejiang Lab","ror":"https://ror.org/02m2h7991","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210123185"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongxia Xu","raw_affiliation_strings":["Liangzhu Laboratory and WeDoctor Cloud and Zhejiang Key Laboratory of Medical Imaging Artificial Intelligence,Hangzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Liangzhu Laboratory and WeDoctor Cloud and Zhejiang Key Laboratory of Medical Imaging Artificial Intelligence,Hangzhou,China","institution_ids":["https://openalex.org/I4210123185"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112888350","display_name":"Danny Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I107639228","display_name":"University of Notre Dame","ror":"https://ror.org/00mkhxb43","country_code":"US","type":"education","lineage":["https://openalex.org/I107639228"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Danny Chen","raw_affiliation_strings":["University of Notre Dame,South Bend,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Notre Dame,South Bend,USA","institution_ids":["https://openalex.org/I107639228"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5071068569","display_name":"Jian Wu","orcid":"https://orcid.org/0000-0002-3230-6392"},"institutions":[{"id":"https://openalex.org/I4210158318","display_name":"Second Affiliated Hospital of Zhejiang University","ror":"https://ror.org/059cjpv64","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210158318"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jian Wu","raw_affiliation_strings":["Zhejiang University,State Key Laboratory of Transvascular Implantation Devices of The Second Affiliated Hospital School of Medicine and School of Public Health,Hangzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang University,State Key Laboratory of Transvascular Implantation Devices of The Second Affiliated Hospital School of Medicine and School of Public Health,Hangzhou,China","institution_ids":["https://openalex.org/I4210158318"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"2519","last_page":"2525"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.8978999853134155,"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/T10320","display_name":"Neural Networks and Applications","score":0.8978999853134155,"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/T10057","display_name":"Face and Expression Recognition","score":0.7928000092506409,"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/T10876","display_name":"Fault Detection and Control Systems","score":0.754800021648407,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.662555992603302},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.6219592094421387},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6204385757446289},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6059662103652954},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.512579619884491}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.662555992603302},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.6219592094421387},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6204385757446289},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6059662103652954},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.512579619884491}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bibm62325.2024.10822080","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm62325.2024.10822080","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/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":37,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W2079853375","https://openalex.org/W2194775991","https://openalex.org/W2510083763","https://openalex.org/W2889615630","https://openalex.org/W2900936384","https://openalex.org/W2963012093","https://openalex.org/W2963772355","https://openalex.org/W2964184998","https://openalex.org/W2979410457","https://openalex.org/W2979448322","https://openalex.org/W2979960726","https://openalex.org/W2988571156","https://openalex.org/W3004531689","https://openalex.org/W3034629650","https://openalex.org/W3037115995","https://openalex.org/W3097460321","https://openalex.org/W3130794141","https://openalex.org/W3173777717","https://openalex.org/W3182906273","https://openalex.org/W4285300583","https://openalex.org/W4312238419","https://openalex.org/W4312351187","https://openalex.org/W4312651322","https://openalex.org/W4312980231","https://openalex.org/W4382239347","https://openalex.org/W4385574005","https://openalex.org/W4386057714","https://openalex.org/W4386075949","https://openalex.org/W4388543952","https://openalex.org/W6631190155","https://openalex.org/W6752558437","https://openalex.org/W6778883912","https://openalex.org/W6782070623","https://openalex.org/W6791353385","https://openalex.org/W6843477136","https://openalex.org/W6850625674"],"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":{"Multi-rater":[0],"annotations":[1,24],"commonly":[2],"occur":[3],"when":[4,42,63],"medical":[5,26,31,170],"images":[6],"are":[7,66,124],"independently":[8],"annotated":[9],"by":[10],"multiple":[11],"experts":[12],"(raters).":[13],"In":[14],"this":[15],"paper,":[16],"we":[17,92,144],"tackle":[18],"two":[19,88,174],"challenges":[20,89],"arisen":[21],"in":[22,136],"multi-rater":[23,82,147],"for":[25,69,107,155,168],"image":[27,32,171],"segmentation":[28,172],"(called":[29],"ambiguous":[30,169],"segmentation):":[33],"(1)":[34],"How":[35],"to":[36,58,85,110,126,130,138],"train":[37],"a":[38,43,48,75,81,94,152],"deep":[39],"learning":[40],"model":[41,61,73,106,183],"group":[44],"of":[45,50,96,121,164,182],"raters":[46],"produces":[47],"set":[49],"diverse":[51],"but":[52],"plausible":[53],"annotations,":[54],"and":[55,142,150],"(2)":[56],"how":[57],"fine-tune":[59],"the":[60,71,104,115,132,162,179],"efficiently":[62],"computation":[64],"resources":[65],"not":[67],"available":[68],"retraining":[70],"entire":[72,133],"on":[74,173],"different":[76,146],"dataset":[77],"domain.":[78],"We":[79],"propose":[80],"prompt-based":[83,116],"approach":[84,167],"address":[86],"these":[87],"altogether.":[90],"Specifically,":[91],"introduce":[93],"series":[95],"rater-aware":[97],"prompts":[98],"that":[99],"can":[100],"be":[101,127,187],"plugged":[102],"into":[103],"U-Net":[105],"uncertainty":[108],"estimation":[109],"handle":[111],"multi-annotation":[112],"cases.":[113],"During":[114],"fine-tuning":[117],"process,":[118],"only":[119],"0.3%":[120],"learnable":[122],"parameters":[123],"required":[125],"updated":[128],"comparing":[129],"training":[131],"model.":[134],"Further,":[135],"order":[137],"integrate":[139],"expert":[140],"consensus":[141],"disagreement,":[143],"explore":[145],"incorporation":[148],"strategies":[149],"design":[151],"mix-training":[153],"strategy":[154],"comprehensive":[156],"insight":[157],"learning.":[158],"Extensive":[159],"experiments":[160],"verify":[161],"effectiveness":[163],"our":[165],"new":[166],"public":[175],"datasets":[176],"while":[177],"alleviating":[178],"heavy":[180],"burden":[181],"re-training.":[184],"Code":[185],"will":[186],"made":[188],"available.":[189]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
