{"id":"https://openalex.org/W4386362640","doi":"https://doi.org/10.1109/isbi53787.2023.10230419","title":"Fusion Contours as a Source of Segmentation Training Data: A Simulation Study","display_name":"Fusion Contours as a Source of Segmentation Training Data: A Simulation Study","publication_year":2023,"publication_date":"2023-04-18","ids":{"openalex":"https://openalex.org/W4386362640","doi":"https://doi.org/10.1109/isbi53787.2023.10230419"},"language":"en","primary_location":{"id":"doi:10.1109/isbi53787.2023.10230419","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi53787.2023.10230419","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE 20th 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/A5031873173","display_name":"D\u00f3nal M. McSweeney","orcid":null},"institutions":[{"id":"https://openalex.org/I28407311","display_name":"University of Manchester","ror":"https://ror.org/027m9bs27","country_code":"GB","type":"education","lineage":["https://openalex.org/I28407311"]},{"id":"https://openalex.org/I4210129527","display_name":"Cancer Research UK Manchester Institute","ror":"https://ror.org/037405c78","country_code":"GB","type":"facility","lineage":["https://openalex.org/I2801316944","https://openalex.org/I4210129527"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"D\u00f3nal M. McSweeney","raw_affiliation_strings":["University of Manchester,Division of Cancer Science,Manchester,UK","Division of Cancer Science, University of Manchester, Manchester, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Manchester,Division of Cancer Science,Manchester,UK","institution_ids":["https://openalex.org/I4210129527"]},{"raw_affiliation_string":"Division of Cancer Science, University of Manchester, Manchester, UK","institution_ids":["https://openalex.org/I4210129527","https://openalex.org/I28407311"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049929595","display_name":"Paul A. Bromiley","orcid":"https://orcid.org/0000-0003-4901-107X"},"institutions":[{"id":"https://openalex.org/I28407311","display_name":"University of Manchester","ror":"https://ror.org/027m9bs27","country_code":"GB","type":"education","lineage":["https://openalex.org/I28407311"]},{"id":"https://openalex.org/I4210142469","display_name":"Health Data Research UK","ror":"https://ror.org/04rtjaj74","country_code":"GB","type":"nonprofit","lineage":["https://openalex.org/I4210142469"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Paul A. Bromiley","raw_affiliation_strings":["University of Manchester,Division of Informatics, Imaging and Data Sciences,UK","Division of Informatics, Imaging and Data Sciences, University of Manchester, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Manchester,Division of Informatics, Imaging and Data Sciences,UK","institution_ids":["https://openalex.org/I4210142469"]},{"raw_affiliation_string":"Division of Informatics, Imaging and Data Sciences, University of Manchester, UK","institution_ids":["https://openalex.org/I28407311"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100317500","display_name":"Andrew Green","orcid":"https://orcid.org/0000-0002-8297-0953"},"institutions":[{"id":"https://openalex.org/I1303153112","display_name":"European Bioinformatics Institute","ror":"https://ror.org/02catss52","country_code":"GB","type":"facility","lineage":["https://openalex.org/I1303153112","https://openalex.org/I4210138560"]},{"id":"https://openalex.org/I4210137637","display_name":"Bioinformatics Institute","ror":"https://ror.org/04btxg914","country_code":"RU","type":"nonprofit","lineage":["https://openalex.org/I4210137637"]}],"countries":["GB","RU"],"is_corresponding":false,"raw_author_name":"Andrew Green","raw_affiliation_strings":["EMBL European Bioinformatics Institute,Cambridge,UK","EMBL European Bioinformatics Institute, Cambridge, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"EMBL European Bioinformatics Institute,Cambridge,UK","institution_ids":["https://openalex.org/I4210137637","https://openalex.org/I1303153112"]},{"raw_affiliation_string":"EMBL European Bioinformatics Institute, Cambridge, UK","institution_ids":["https://openalex.org/I1303153112"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009101796","display_name":"Marcel van Herk","orcid":"https://orcid.org/0000-0001-6448-898X"},"institutions":[{"id":"https://openalex.org/I28407311","display_name":"University of Manchester","ror":"https://ror.org/027m9bs27","country_code":"GB","type":"education","lineage":["https://openalex.org/I28407311"]},{"id":"https://openalex.org/I4210129527","display_name":"Cancer Research UK Manchester Institute","ror":"https://ror.org/037405c78","country_code":"GB","type":"facility","lineage":["https://openalex.org/I2801316944","https://openalex.org/I4210129527"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Marcel van Herk","raw_affiliation_strings":["University of Manchester,Division of Cancer Science,Manchester,UK","Division of Cancer Science, University of Manchester, Manchester, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Manchester,Division of Cancer Science,Manchester,UK","institution_ids":["https://openalex.org/I4210129527"]},{"raw_affiliation_string":"Division of Cancer Science, University of Manchester, Manchester, UK","institution_ids":["https://openalex.org/I4210129527","https://openalex.org/I28407311"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5010870209","display_name":"Alan McWilliam","orcid":"https://orcid.org/0000-0002-7344-2868"},"institutions":[{"id":"https://openalex.org/I28407311","display_name":"University of Manchester","ror":"https://ror.org/027m9bs27","country_code":"GB","type":"education","lineage":["https://openalex.org/I28407311"]},{"id":"https://openalex.org/I4210129527","display_name":"Cancer Research UK Manchester Institute","ror":"https://ror.org/037405c78","country_code":"GB","type":"facility","lineage":["https://openalex.org/I2801316944","https://openalex.org/I4210129527"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Alan McWilliam","raw_affiliation_strings":["University of Manchester,Division of Cancer Science,Manchester,UK","Division of Cancer Science, University of Manchester, Manchester, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Manchester,Division of Cancer Science,Manchester,UK","institution_ids":["https://openalex.org/I4210129527"]},{"raw_affiliation_string":"Division of Cancer Science, University of Manchester, Manchester, UK","institution_ids":["https://openalex.org/I4210129527","https://openalex.org/I28407311"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.1632,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.55679024,"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":"6"},"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":0.9871000051498413,"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":0.9871000051498413,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9871000051498413,"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":0.9772999882698059,"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":0.8340609669685364},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.7613004446029663},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.698551595211029},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6803553700447083},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.6288337707519531},{"id":"https://openalex.org/keywords/majority-rule","display_name":"Majority rule","score":0.6284447908401489},{"id":"https://openalex.org/keywords/observer","display_name":"Observer (physics)","score":0.5743045210838318},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5558121800422668},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.5423802137374878},{"id":"https://openalex.org/keywords/annotation","display_name":"Annotation","score":0.5243551731109619},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5044862031936646},{"id":"https://openalex.org/keywords/noisy-data","display_name":"Noisy data","score":0.47345370054244995},{"id":"https://openalex.org/keywords/voting","display_name":"Voting","score":0.45899513363838196},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.421755313873291},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.09011039137840271}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8340609669685364},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7613004446029663},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.698551595211029},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6803553700447083},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.6288337707519531},{"id":"https://openalex.org/C153668964","wikidata":"https://www.wikidata.org/wiki/Q27636","display_name":"Majority rule","level":2,"score":0.6284447908401489},{"id":"https://openalex.org/C2780704645","wikidata":"https://www.wikidata.org/wiki/Q9251458","display_name":"Observer (physics)","level":2,"score":0.5743045210838318},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5558121800422668},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.5423802137374878},{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.5243551731109619},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5044862031936646},{"id":"https://openalex.org/C2781170535","wikidata":"https://www.wikidata.org/wiki/Q30587856","display_name":"Noisy data","level":2,"score":0.47345370054244995},{"id":"https://openalex.org/C520049643","wikidata":"https://www.wikidata.org/wiki/Q189760","display_name":"Voting","level":3,"score":0.45899513363838196},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.421755313873291},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.09011039137840271},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isbi53787.2023.10230419","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi53787.2023.10230419","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE 20th International Symposium on Biomedical Imaging (ISBI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W335813838","https://openalex.org/W1522301498","https://openalex.org/W1861492603","https://openalex.org/W2018662705","https://openalex.org/W2127424726","https://openalex.org/W2148347694","https://openalex.org/W2163595993","https://openalex.org/W2164971516","https://openalex.org/W2309693750","https://openalex.org/W2345010043","https://openalex.org/W2889615630","https://openalex.org/W2896134910","https://openalex.org/W2913768941","https://openalex.org/W2945682148","https://openalex.org/W2945683845","https://openalex.org/W2963012093","https://openalex.org/W2963772355","https://openalex.org/W2964156854","https://openalex.org/W2979302305","https://openalex.org/W3034976991","https://openalex.org/W3046830682","https://openalex.org/W3085136579","https://openalex.org/W3119379033","https://openalex.org/W3130354799","https://openalex.org/W3176913189","https://openalex.org/W4213021241","https://openalex.org/W4297791576","https://openalex.org/W6631190155","https://openalex.org/W6639102338","https://openalex.org/W6752558437","https://openalex.org/W6779384589","https://openalex.org/W6782070623","https://openalex.org/W6788328075"],"related_works":["https://openalex.org/W4401571341","https://openalex.org/W2295086410","https://openalex.org/W160673860","https://openalex.org/W4289766121","https://openalex.org/W2963642612","https://openalex.org/W4289548080","https://openalex.org/W1585680390","https://openalex.org/W3173587717","https://openalex.org/W3165456129","https://openalex.org/W2113005879"],"abstract_inverted_index":{"Consensus":[0],"contours":[1,81],"are":[2,82],"often":[3],"used":[4],"to":[5,101],"reduce":[6],"annotator":[7],"error":[8],"in":[9,20,107],"segmentation":[10],"data.":[11],"Here,":[12],"we":[13,66],"investigate":[14,67],"the":[15,58,68,96,108],"use":[16],"of":[17,60,70],"multi-annotator":[18],"labels,":[19],"simulated":[21],"data,":[22],"for":[23,104],"training":[24,109],"auto-segmentation":[25],"models.":[26],"We":[27,43],"compare":[28],"convolutional":[29],"neural":[30],"networks":[31],"(CNNs)":[32],"trained":[33,78,91],"on":[34,72,79,92],"all":[35,93],"observer":[36,49],"annotations,":[37],"STAPLE":[38,80],"and":[39,54,62,98],"majority":[40],"voting":[41],"estimates.":[42],"generate":[44],"annotation":[45],"sets":[46],"by":[47],"simulating":[48],"delineations":[50],"with":[51,87],"varying":[52],"noise":[53],"bias.":[55],"By":[56],"altering":[57],"quantity":[59],"observers":[61],"their":[63],"relative":[64],"biases,":[65],"impact":[69],"bias":[71],"CNN":[73],"performance.We":[74],"find":[75],"that":[76],"models":[77],"significantly":[83],"worse":[84],"when":[85],"presented":[86],"biased":[88,105],"annotations.":[89],"CNNs":[90],"annotations":[94,106],"performed":[95],"best":[97],"were":[99],"able":[100],"implicitly":[102],"account":[103],"set.":[110]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}