{"id":"https://openalex.org/W4416251492","doi":"https://doi.org/10.1109/ijcnn64981.2025.11229102","title":"A Dental Periapical X-ray Images Segmentation Network Based on Pixel-Wise Contrastive Learning with Dual Attention Mechanisms","display_name":"A Dental Periapical X-ray Images Segmentation Network Based on Pixel-Wise Contrastive Learning with Dual Attention Mechanisms","publication_year":2025,"publication_date":"2025-06-30","ids":{"openalex":"https://openalex.org/W4416251492","doi":"https://doi.org/10.1109/ijcnn64981.2025.11229102"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn64981.2025.11229102","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11229102","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://ink.library.smu.edu.sg/sis_research/10826","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5026875205","display_name":"Yanan Du","orcid":"https://orcid.org/0000-0002-4438-139X"},"institutions":[{"id":"https://openalex.org/I126924076","display_name":"Chongqing Normal University","ror":"https://ror.org/01dcw5w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I126924076"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanan Du","raw_affiliation_strings":["Chongqing Normal University,School of Computer and Information Science,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chongqing Normal University,School of Computer and Information Science,China","institution_ids":["https://openalex.org/I126924076"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047461613","display_name":"Zhi Zeng","orcid":"https://orcid.org/0000-0002-7002-736X"},"institutions":[{"id":"https://openalex.org/I126924076","display_name":"Chongqing Normal University","ror":"https://ror.org/01dcw5w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I126924076"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhi Zeng","raw_affiliation_strings":["Chongqing Normal University,School of Computer and Information Science,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chongqing Normal University,School of Computer and Information Science,China","institution_ids":["https://openalex.org/I126924076"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102632157","display_name":"Yibin Tian","orcid":"https://orcid.org/0009-0008-4590-8318"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yibin Tian","raw_affiliation_strings":["Shenzhen University,College of Mechatronics and Control Engineering,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shenzhen University,College of Mechatronics and Control Engineering,China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002674092","display_name":"Zhiyuan Zhang","orcid":"https://orcid.org/0000-0002-2605-1549"},"institutions":[{"id":"https://openalex.org/I79891267","display_name":"Singapore Management University","ror":"https://ror.org/050qmg959","country_code":"SG","type":"education","lineage":["https://openalex.org/I79891267"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Zhiyuan Zhang","raw_affiliation_strings":["Singapore Management University,School of Computing and Information System,Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Singapore Management University,School of Computing and Information System,Singapore","institution_ids":["https://openalex.org/I79891267"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004662248","display_name":"Xueyang Zhang","orcid":"https://orcid.org/0000-0003-3625-219X"},"institutions":[{"id":"https://openalex.org/I4210098425","display_name":"The First People's Hospital of Shunde","ror":"https://ror.org/00wwb2b69","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210098425"]},{"id":"https://openalex.org/I58200834","display_name":"Southern Medical University","ror":"https://ror.org/01vjw4z39","country_code":"CN","type":"education","lineage":["https://openalex.org/I58200834"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xueyang Zhang","raw_affiliation_strings":["Southern Medical University,Shunde Hospital,Department of Stomatology,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Southern Medical University,Shunde Hospital,Department of Stomatology,China","institution_ids":["https://openalex.org/I4210098425","https://openalex.org/I58200834"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5119789343","display_name":"Shan Lianlei","orcid":null},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shan Lianlei","raw_affiliation_strings":["University of Chinese Academy of Sciences,School of Computer Science and Technology,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Chinese Academy of Sciences,School of Computer Science and Technology,China","institution_ids":["https://openalex.org/I4210165038"]}]}],"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":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11363","display_name":"Dental Radiography and Imaging","score":0.9725000262260437,"subfield":{"id":"https://openalex.org/subfields/3504","display_name":"Oral Surgery"},"field":{"id":"https://openalex.org/fields/35","display_name":"Dentistry"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T11363","display_name":"Dental Radiography and Imaging","score":0.9725000262260437,"subfield":{"id":"https://openalex.org/subfields/3504","display_name":"Oral Surgery"},"field":{"id":"https://openalex.org/fields/35","display_name":"Dentistry"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T11775","display_name":"COVID-19 diagnosis using AI","score":0.003700000001117587,"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/T10862","display_name":"AI in cancer detection","score":0.0019000000320374966,"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/segmentation","display_name":"Segmentation","score":0.7940000295639038},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.6672000288963318},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5467000007629395},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5142999887466431},{"id":"https://openalex.org/keywords/dual","display_name":"Dual (grammatical number)","score":0.43799999356269836},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.40049999952316284},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.3587000072002411},{"id":"https://openalex.org/keywords/contrast","display_name":"Contrast (vision)","score":0.35589998960494995}],"concepts":[{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7940000295639038},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.713100016117096},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6952999830245972},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.6672000288963318},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5467000007629395},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5142999887466431},{"id":"https://openalex.org/C2780980858","wikidata":"https://www.wikidata.org/wiki/Q110022","display_name":"Dual (grammatical number)","level":2,"score":0.43799999356269836},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.40049999952316284},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.3587000072002411},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.35589998960494995},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.34619998931884766},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3296000063419342},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.3140000104904175},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.3109999895095825},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3059999942779541},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.302700012922287},{"id":"https://openalex.org/C125308379","wikidata":"https://www.wikidata.org/wiki/Q363057","display_name":"Market segmentation","level":2,"score":0.296999990940094},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.29420000314712524},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.2831999957561493},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.27709999680519104},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.27250000834465027},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.2689000070095062}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/ijcnn64981.2025.11229102","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11229102","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},{"id":"pmh:oai:ink.library.smu.edu.sg:sis_research-11828","is_oa":true,"landing_page_url":"https://ink.library.smu.edu.sg/sis_research/10826","pdf_url":null,"source":{"id":"https://openalex.org/S4306401925","display_name":"Singapore Management University Institutional Knowledge (InK) (Singapore Management University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I79891267","host_organization_name":"Singapore Management University","host_organization_lineage":["https://openalex.org/I79891267"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Conference Proceeding Article"}],"best_oa_location":{"id":"pmh:oai:ink.library.smu.edu.sg:sis_research-11828","is_oa":true,"landing_page_url":"https://ink.library.smu.edu.sg/sis_research/10826","pdf_url":null,"source":{"id":"https://openalex.org/S4306401925","display_name":"Singapore Management University Institutional Knowledge (InK) (Singapore Management University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I79891267","host_organization_name":"Singapore Management University","host_organization_lineage":["https://openalex.org/I79891267"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Conference Proceeding Article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320311649","display_name":"Ministry of Education","ror":"https://ror.org/036nq5137"},{"id":"https://openalex.org/F4320325571","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70"},{"id":"https://openalex.org/F4320326279","display_name":"Department of Education of Guangdong Province","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W789961223","https://openalex.org/W1901129140","https://openalex.org/W2097117768","https://openalex.org/W2115892176","https://openalex.org/W2118386984","https://openalex.org/W2138621090","https://openalex.org/W2194775991","https://openalex.org/W2395611524","https://openalex.org/W2412782625","https://openalex.org/W2884436604","https://openalex.org/W2897953830","https://openalex.org/W2912654919","https://openalex.org/W2934073222","https://openalex.org/W2955058313","https://openalex.org/W2963150697","https://openalex.org/W3035524453","https://openalex.org/W3035951809","https://openalex.org/W3096947210","https://openalex.org/W3108776516","https://openalex.org/W3202623927","https://openalex.org/W4213019189","https://openalex.org/W4294904564","https://openalex.org/W4317690705","https://openalex.org/W4362672205","https://openalex.org/W4387046219","https://openalex.org/W4387472455","https://openalex.org/W4390350005","https://openalex.org/W4390926704","https://openalex.org/W4392024636","https://openalex.org/W4396973073","https://openalex.org/W4399419713","https://openalex.org/W4402716203","https://openalex.org/W4403456736","https://openalex.org/W4403905612","https://openalex.org/W4404922950"],"related_works":[],"abstract_inverted_index":{"Periapical":[0],"radiographs":[1,144],"tend":[2],"to":[3,8,21,46,84,133],"have":[4],"poor":[5],"quality":[6],"due":[7],"factors":[9,19],"like":[10],"acquisition":[11],"techniques,":[12],"equipment":[13],"limitations,":[14],"and":[15,50,80,105,117],"patient":[16],"differences.":[17],"These":[18],"lead":[20],"discrepancies":[22],"in":[23,34,142,207],"images,":[24],"making":[25],"precise":[26],"segmentation":[27,31,48,88,115,190,210],"challenging.":[28],"However,":[29],"accurate":[30],"is":[32],"crucial":[33],"dental":[35],"practices.":[36],"To":[37],"address":[38,85],"this":[39,61],"issue,":[40],"deep":[41,66],"learning":[42,67,83,172],"can":[43],"be":[44],"employed":[45],"improve":[47],"accuracy":[49],"efficiency,":[51],"thereby":[52],"providing":[53],"more":[54],"reliable":[55],"support":[56],"for":[57,113],"clinical":[58],"diagnosis.":[59],"In":[60],"study,":[62],"we":[63],"propose":[64],"a":[65,76,125,147],"network":[68],"based":[69],"on":[70,189],"an":[71],"encoder-decoder":[72],"architecture,":[73],"which":[74,98],"integrates":[75],"dual":[77,155],"attention":[78,107,156],"mechanism":[79,157],"pixel-wise":[81,118,170],"contrastive":[82,119,171],"the":[86,92,130,138,159,175,179,184,196],"tooth":[87],"problem.":[89],"We":[90],"design":[91],"Dual":[93],"Attention":[94],"Contrast":[95],"(DAC)":[96],"module,":[97,122],"enhances":[99],"feature":[100,150,180],"maps":[101],"through":[102,165],"joint":[103],"spatial":[104],"channel":[106],"before":[108],"utilizing":[109],"optimized":[110],"multi-scale":[111,139],"features":[112,136,164],"both":[114],"prediction":[116],"learning.":[120],"This":[121],"implemented":[123],"with":[124],"multi-level":[126],"deployment":[127],"strategy,":[128],"strengthens":[129],"network's":[131],"ability":[132],"extract":[134],"discriminative":[135],"from":[137],"anatomical":[140],"structures":[141],"periapical":[143,208],"while":[145,169],"constructing":[146],"globally":[148],"structured":[149],"space":[151],"across":[152,203],"datasets.":[153],"The":[154],"improves":[158],"recognition":[160],"of":[161,178,186],"key":[162],"local":[163],"spatial-channel":[166],"collaborative":[167],"calibration,":[168],"explicitly":[173],"constrains":[174],"topological":[176],"structure":[177],"space,":[181],"effectively":[182],"mitigating":[183],"impact":[185],"inter-image":[187],"variations":[188],"accuracy.":[191],"Experimental":[192],"results":[193],"show":[194],"that":[195],"proposed":[197],"model":[198],"outperforms":[199],"current":[200],"mainstream":[201],"models":[202],"various":[204],"evaluation":[205],"metrics":[206],"radiograph":[209],"tasks.":[211]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-11-14T00:00:00"}