{"id":"https://openalex.org/W7126044582","doi":"https://doi.org/10.1109/bibm66473.2025.11356622","title":"CyclicAligner: Knowledge-Enhanced Cyclical Alignment for Chest X-Ray Report Generation","display_name":"CyclicAligner: Knowledge-Enhanced Cyclical Alignment for Chest X-Ray Report Generation","publication_year":2025,"publication_date":"2025-12-15","ids":{"openalex":"https://openalex.org/W7126044582","doi":"https://doi.org/10.1109/bibm66473.2025.11356622"},"language":null,"primary_location":{"id":"doi:10.1109/bibm66473.2025.11356622","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm66473.2025.11356622","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 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/A5025713948","display_name":"Jiamei Sun","orcid":"https://orcid.org/0000-0001-6957-0608"},"institutions":[{"id":"https://openalex.org/I50760025","display_name":"Hangzhou Dianzi University","ror":"https://ror.org/0576gt767","country_code":"CN","type":"education","lineage":["https://openalex.org/I50760025"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiamei Sun","raw_affiliation_strings":["School of Computer Science, Hangzhou Dianzi University,Hangzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, Hangzhou Dianzi University,Hangzhou,China","institution_ids":["https://openalex.org/I50760025"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Pengbo Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I50760025","display_name":"Hangzhou Dianzi University","ror":"https://ror.org/0576gt767","country_code":"CN","type":"education","lineage":["https://openalex.org/I50760025"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Pengbo Wang","raw_affiliation_strings":["School of Computer Science, Hangzhou Dianzi University,Hangzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, Hangzhou Dianzi University,Hangzhou,China","institution_ids":["https://openalex.org/I50760025"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124251232","display_name":"Ke Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I50760025","display_name":"Hangzhou Dianzi University","ror":"https://ror.org/0576gt767","country_code":"CN","type":"education","lineage":["https://openalex.org/I50760025"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ke Zhang","raw_affiliation_strings":["School of Computer Science, Hangzhou Dianzi University,Hangzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, Hangzhou Dianzi University,Hangzhou,China","institution_ids":["https://openalex.org/I50760025"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124260977","display_name":"Xiangyu Tan","orcid":null},"institutions":[{"id":"https://openalex.org/I50760025","display_name":"Hangzhou Dianzi University","ror":"https://ror.org/0576gt767","country_code":"CN","type":"education","lineage":["https://openalex.org/I50760025"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiangyu Tan","raw_affiliation_strings":["School of Computer Science, Hangzhou Dianzi University,Hangzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, Hangzhou Dianzi University,Hangzhou,China","institution_ids":["https://openalex.org/I50760025"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002531550","display_name":"Zhenqi Fu","orcid":"https://orcid.org/0000-0003-2950-7190"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenqi Fu","raw_affiliation_strings":["Tsinghua University,Department of Automation,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University,Department of Automation,Beijing,China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101847695","display_name":"Yuting Yang","orcid":"https://orcid.org/0000-0001-6859-6195"},"institutions":[{"id":"https://openalex.org/I50760025","display_name":"Hangzhou Dianzi University","ror":"https://ror.org/0576gt767","country_code":"CN","type":"education","lineage":["https://openalex.org/I50760025"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yan Yang","raw_affiliation_strings":["School of Computer Science, Hangzhou Dianzi University,Hangzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, Hangzhou Dianzi University,Hangzhou,China","institution_ids":["https://openalex.org/I50760025"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"5704","last_page":"5711"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.791100025177002,"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"}},"topics":[{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.791100025177002,"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/T11775","display_name":"COVID-19 diagnosis using AI","score":0.06350000202655792,"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/T10028","display_name":"Topic Modeling","score":0.06300000101327896,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.7412999868392944},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.5803999900817871},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.5737000107765198},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.3986000120639801},{"id":"https://openalex.org/keywords/task-analysis","display_name":"Task analysis","score":0.37040001153945923},{"id":"https://openalex.org/keywords/language-understanding","display_name":"Language understanding","score":0.3580999970436096},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.3336000144481659},{"id":"https://openalex.org/keywords/unified-medical-language-system","display_name":"Unified Medical Language System","score":0.32420000433921814}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7628999948501587},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.7412999868392944},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.6301000118255615},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5929999947547913},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.5803999900817871},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.5737000107765198},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.3986000120639801},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.37040001153945923},{"id":"https://openalex.org/C2983448237","wikidata":"https://www.wikidata.org/wiki/Q1078276","display_name":"Language understanding","level":2,"score":0.3580999970436096},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.33889999985694885},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.3336000144481659},{"id":"https://openalex.org/C69505689","wikidata":"https://www.wikidata.org/wiki/Q455338","display_name":"Unified Medical Language System","level":2,"score":0.32420000433921814},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.31290000677108765},{"id":"https://openalex.org/C2985684807","wikidata":"https://www.wikidata.org/wiki/Q1513879","display_name":"Text generation","level":2,"score":0.304500013589859},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.2994000017642975},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.28029999136924744},{"id":"https://openalex.org/C133162039","wikidata":"https://www.wikidata.org/wiki/Q1061077","display_name":"Code generation","level":3,"score":0.2791999876499176},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.27219998836517334},{"id":"https://openalex.org/C146499914","wikidata":"https://www.wikidata.org/wiki/Q5469969","display_name":"Formal semantics (linguistics)","level":2,"score":0.27149999141693115},{"id":"https://openalex.org/C2985722590","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medical knowledge","level":2,"score":0.26840001344680786},{"id":"https://openalex.org/C199033989","wikidata":"https://www.wikidata.org/wiki/Q1318295","display_name":"Narrative","level":2,"score":0.2667999863624573},{"id":"https://openalex.org/C2776187449","wikidata":"https://www.wikidata.org/wiki/Q1513879","display_name":"Natural language generation","level":3,"score":0.266400009393692},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.2500999867916107}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bibm66473.2025.11356622","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm66473.2025.11356622","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","score":0.6011715531349182,"id":"https://metadata.un.org/sdg/4"}],"awards":[{"id":"https://openalex.org/G4742642327","display_name":null,"funder_award_id":"62176230,62406093,62501357","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W1895577753","https://openalex.org/W1956340063","https://openalex.org/W2101105183","https://openalex.org/W2133512280","https://openalex.org/W2152772232","https://openalex.org/W2770165365","https://openalex.org/W2962858109","https://openalex.org/W2995225687","https://openalex.org/W3034655362","https://openalex.org/W3091588028","https://openalex.org/W3104609094","https://openalex.org/W3173688449","https://openalex.org/W3174714208","https://openalex.org/W3177048142","https://openalex.org/W3213610319","https://openalex.org/W4281729070","https://openalex.org/W4283821415","https://openalex.org/W4285108627","https://openalex.org/W4375802394","https://openalex.org/W4385245566","https://openalex.org/W4385573131","https://openalex.org/W4387789891","https://openalex.org/W4390970476","https://openalex.org/W4392909927","https://openalex.org/W4393159239","https://openalex.org/W4399527328","https://openalex.org/W4405754135","https://openalex.org/W4406261030","https://openalex.org/W4408858700","https://openalex.org/W4411208761"],"related_works":[],"abstract_inverted_index":{"To":[0,127],"reduce":[1],"the":[2,113,121,125,165,174,183],"diagnostic":[3],"burden":[4],"on":[5,179],"radiologists,":[6],"recent":[7],"studies":[8],"have":[9],"explored":[10],"automatic":[11],"chest":[12],"X-ray":[13],"(CXR)":[14],"report":[15,48,175,191],"generation":[16,71],"via":[17],"artificial":[18],"intelligence.":[19],"Yet,":[20],"achieving":[21],"robust":[22],"cross-modal":[23,65,130],"alignment":[24,44],"between":[25],"medical":[26,135,154],"images":[27],"and":[28,97,103,119,147,156],"textual":[29],"reports":[30,158],"remains":[31],"a":[32,41,52,81,90,105,140,160],"major":[33],"challenge.":[34],"In":[35],"this":[36],"paper,":[37],"we":[38,132],"propose":[39],"CyclicAligner,":[40],"knowledge-enhanced":[42],"cyclical":[43,54],"framework":[45],"for":[46,100,116,188],"CXR":[47,190],"generation.":[49,176,192],"CyclicAligner":[50,151],"adopts":[51],"novel":[53],"training":[55],"paradigm":[56],"with":[57,77,124],"four":[58],"tightly":[59],"coupled":[60],"tasks":[61],"to":[62,143],"effectively":[63],"learn":[64],"semantic":[66,170],"alignment:":[67],"(1)":[68],"an":[69],"image-to-text":[70,114],"task":[72,84,93,107],"that":[73,85,94,108,172],"aligns":[74,120],"visual":[75],"semantics":[76],"clinical":[78],"findings,":[79],"(2)":[80],"text-to-text":[82],"reconstruction":[83,92,118],"strengthens":[86],"language":[87,98,148],"modeling,":[88],"(3)":[89],"hybrid-to-text":[91],"mixes":[95],"vision":[96,146],"tokens":[99],"text":[101,117,123],"reconstruction,":[102],"(4)":[104],"traceback-alignment":[106],"re-encodes":[109],"texts":[110],"generated":[111],"by":[112],"branch":[115],"reconstructed":[122],"reference.":[126],"further":[128],"enhance":[129],"understanding,":[131],"integrate":[133],"domain-specific":[134],"entity":[136],"knowledge":[137],"extracted":[138],"from":[139],"pre-trained":[141],"encoder":[142],"enrich":[144],"both":[145],"tokens.":[149],"Moreover,":[150],"jointly":[152],"predicts":[153],"tags":[155,166],"narrative":[157],"within":[159],"unified":[161],"auto-regressive":[162],"pipeline,":[163],"where":[164],"serve":[167],"as":[168],"auxiliary":[169],"anchors":[171],"guide":[173],"Extensive":[177],"experiments":[178],"public":[180],"datasets":[181],"demonstrate":[182],"effectiveness":[184],"of":[185],"our":[186],"method":[187],"clinical-coherent":[189],"The":[193],"related":[194],"code":[195],"is":[196],"available":[197],"at":[198],"https://github.com/yangyan22/CyclicAligner.":[199]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2026-01-30T00:00:00"}