{"id":"https://openalex.org/W4410296740","doi":"https://doi.org/10.1109/isbi60581.2025.10980667","title":"Adaptive Cross-Attention for Robust Lung Segmentation with Noisy Labels","display_name":"Adaptive Cross-Attention for Robust Lung Segmentation with Noisy Labels","publication_year":2025,"publication_date":"2025-04-14","ids":{"openalex":"https://openalex.org/W4410296740","doi":"https://doi.org/10.1109/isbi60581.2025.10980667"},"language":"en","primary_location":{"id":"doi:10.1109/isbi60581.2025.10980667","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi60581.2025.10980667","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 22nd International Symposium on Biomedical Imaging (ISBI)","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/A5100738705","display_name":"Junyi Liu","orcid":"https://orcid.org/0000-0002-4277-1802"},"institutions":[{"id":"https://openalex.org/I52357470","display_name":"The Ohio State University","ror":"https://ror.org/00rs6vg23","country_code":"US","type":"education","lineage":["https://openalex.org/I52357470"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Junyi Liu","raw_affiliation_strings":["The Ohio State University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Ohio State University","institution_ids":["https://openalex.org/I52357470"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101946640","display_name":"Ahmed H. Aly","orcid":"https://orcid.org/0000-0001-7626-8124"},"institutions":[{"id":"https://openalex.org/I52357470","display_name":"The Ohio State University","ror":"https://ror.org/00rs6vg23","country_code":"US","type":"education","lineage":["https://openalex.org/I52357470"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ahmed Aly","raw_affiliation_strings":["The Ohio State University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Ohio State University","institution_ids":["https://openalex.org/I52357470"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112973300","display_name":"Peter J. Kneuertz","orcid":null},"institutions":[{"id":"https://openalex.org/I52357470","display_name":"The Ohio State University","ror":"https://ror.org/00rs6vg23","country_code":"US","type":"education","lineage":["https://openalex.org/I52357470"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Peter Kneuertz","raw_affiliation_strings":["The Ohio State University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Ohio State University","institution_ids":["https://openalex.org/I52357470"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5028544932","display_name":"Yuan Xue","orcid":"https://orcid.org/0000-0002-5390-9037"},"institutions":[{"id":"https://openalex.org/I52357470","display_name":"The Ohio State University","ror":"https://ror.org/00rs6vg23","country_code":"US","type":"education","lineage":["https://openalex.org/I52357470"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yuan Xue","raw_affiliation_strings":["The Ohio State University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Ohio State University","institution_ids":["https://openalex.org/I52357470"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I52357470"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.1877494,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"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/T10202","display_name":"Lung Cancer Diagnosis and Treatment","score":0.9847999811172485,"subfield":{"id":"https://openalex.org/subfields/2740","display_name":"Pulmonary and Respiratory Medicine"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T10202","display_name":"Lung Cancer Diagnosis and Treatment","score":0.9847999811172485,"subfield":{"id":"https://openalex.org/subfields/2740","display_name":"Pulmonary and Respiratory Medicine"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9628000259399414,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T11667","display_name":"Advanced Chemical Sensor Technologies","score":0.920199990272522,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical 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":0.7131683230400085},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6355122923851013},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6243024468421936},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.47054749727249146},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4627404808998108},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.43313151597976685}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7131683230400085},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6355122923851013},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6243024468421936},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.47054749727249146},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4627404808998108},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.43313151597976685}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isbi60581.2025.10980667","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi60581.2025.10980667","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 22nd International Symposium on Biomedical Imaging (ISBI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5099999904632568,"display_name":"Zero hunger","id":"https://metadata.un.org/sdg/2"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W2122692815","https://openalex.org/W2803684675","https://openalex.org/W2804047627","https://openalex.org/W2915725179","https://openalex.org/W3014974815","https://openalex.org/W3035294798","https://openalex.org/W3036586801","https://openalex.org/W3138516171","https://openalex.org/W3157259822","https://openalex.org/W4206151668","https://openalex.org/W4384159609"],"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":{"Accurate":[0],"lung":[1,41,143],"segmentation":[2,19,42,104,144],"in":[3,68],"computed":[4],"tomography":[5],"(CT)":[6],"images":[7],"is":[8,20],"essential":[9],"for":[10,40,142],"diagnosing":[11],"and":[12,26,81,117,139],"managing":[13],"respiratory":[14],"diseases.":[15],"However,":[16],"achieving":[17,106],"reliable":[18],"challenging":[21],"due":[22],"to":[23,65,127],"the":[24,88,128],"scarcity":[25],"noise":[27,147],"of":[28,90,112],"labeled":[29],"medical":[30],"data.":[31],"In":[32],"this":[33],"paper,":[34],"we":[35,71],"present":[36],"a":[37,118,137],"novel":[38],"approach":[39,102],"under":[43,122,145],"noisy":[44,124],"labeling":[45],"conditions":[46],"via":[47],"attention-guided":[48],"transfer":[49],"learning.":[50],"Our":[51],"method":[52],"integrates":[53],"an":[54,73,107],"Adaptive":[55],"Cross-Attention":[56],"block,":[57],"which":[58],"selectively":[59],"incorporates":[60],"features":[61],"from":[62],"pretrained":[63,80],"models":[64],"improve":[66],"robustness":[67],"segmentation.":[69],"Furthermore,":[70],"introduce":[72],"adaptive":[74],"loss":[75],"function":[76],"that":[77,100],"dynamically":[78],"weighs":[79],"ground-truth":[82],"outputs":[83],"during":[84],"training,":[85],"effectively":[86],"mitigating":[87],"impact":[89],"possible":[91],"label":[92,146],"noise.":[93],"Extensive":[94],"evaluations":[95],"on":[96,114],"public":[97],"datasets":[98],"demonstrate":[99],"our":[101,134],"improves":[103],"accuracy,":[105],"average":[108],"Dice":[109],"coefficient":[110],"increase":[111],"3.7%":[113],"clean":[115],"data":[116],"significant":[119],"29.4%":[120],"improvement":[121],"simulated":[123],"annotations":[125],"compared":[126],"standard":[129],"nnU-Net.":[130],"These":[131],"results":[132],"establish":[133],"model":[135],"as":[136],"simple":[138],"effective":[140],"solution":[141],"constraints.":[148]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
