{"id":"https://openalex.org/W7126108372","doi":"https://doi.org/10.1109/bibm66473.2025.11356330","title":"Frequency\u2014Semantic Dual\u2014Driven Segmentation of Peripapillary Atrophy in Retinal Fundus Images","display_name":"Frequency\u2014Semantic Dual\u2014Driven Segmentation of Peripapillary Atrophy in Retinal Fundus Images","publication_year":2025,"publication_date":"2025-12-15","ids":{"openalex":"https://openalex.org/W7126108372","doi":"https://doi.org/10.1109/bibm66473.2025.11356330"},"language":null,"primary_location":{"id":"doi:10.1109/bibm66473.2025.11356330","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm66473.2025.11356330","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/A5124191212","display_name":"Wanbo Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wanbo Wang","raw_affiliation_strings":["Harbin Institute of Technology,Department of Computer Science and Technology,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Harbin Institute of Technology,Department of Computer Science and Technology,China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5107973137","display_name":"Hongshuo Li","orcid":"https://orcid.org/0009-0009-3554-0510"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210165339","display_name":"Ningbo Institute of Industrial Technology","ror":"https://ror.org/05nqg3g04","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165339"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongshuo Li","raw_affiliation_strings":["Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences,Ningbo,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences,Ningbo,China","institution_ids":["https://openalex.org/I4210165339","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073108691","display_name":"Lei Yuan","orcid":"https://orcid.org/0000-0002-0532-7745"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210165339","display_name":"Ningbo Institute of Industrial Technology","ror":"https://ror.org/05nqg3g04","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165339"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Leilei Yuan","raw_affiliation_strings":["Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences,Ningbo,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences,Ningbo,China","institution_ids":["https://openalex.org/I4210165339","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101320798","display_name":"Yaxuan Zhao","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"]},{"id":"https://openalex.org/I4210165339","display_name":"Ningbo Institute of Industrial Technology","ror":"https://ror.org/05nqg3g04","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165339"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yaxuan Zhao","raw_affiliation_strings":["Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences,Laboratory of Advanced Theranostic Materials and Technology,China","University of Chinese Academy of Sciences,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences,Laboratory of Advanced Theranostic Materials and Technology,China","institution_ids":["https://openalex.org/I4210165339"]},{"raw_affiliation_string":"University of Chinese Academy of Sciences,Beijing,China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Shaodong Ma","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":"Shaodong Ma","raw_affiliation_strings":["University of Chinese Academy of Sciences,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Chinese Academy of Sciences,Beijing,China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124277705","display_name":"Ling Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ling Wang","raw_affiliation_strings":["Harbin Institute of Technology,Department of Computer Science and Technology,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Harbin Institute of Technology,Department of Computer Science and Technology,China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5124181077","display_name":"Yitian Zhao","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"]},{"id":"https://openalex.org/I4210165339","display_name":"Ningbo Institute of Industrial Technology","ror":"https://ror.org/05nqg3g04","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165339"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yitian Zhao","raw_affiliation_strings":["Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences,Laboratory of Advanced Theranostic Materials and Technology,China","University of Chinese Academy of Sciences,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences,Laboratory of Advanced Theranostic Materials and Technology,China","institution_ids":["https://openalex.org/I4210165339"]},{"raw_affiliation_string":"University of Chinese Academy of Sciences,Beijing,China","institution_ids":["https://openalex.org/I4210165038"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"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":"2892","last_page":"2898"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11438","display_name":"Retinal Imaging and Analysis","score":0.9186000227928162,"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"}},"topics":[{"id":"https://openalex.org/T11438","display_name":"Retinal Imaging and Analysis","score":0.9186000227928162,"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/T10170","display_name":"Retinal Diseases and Treatments","score":0.03440000116825104,"subfield":{"id":"https://openalex.org/subfields/2731","display_name":"Ophthalmology"},"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/T10381","display_name":"Ophthalmology and Visual Impairment Studies","score":0.020500000566244125,"subfield":{"id":"https://openalex.org/subfields/2713","display_name":"Epidemiology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.8061000108718872},{"id":"https://openalex.org/keywords/fundus","display_name":"Fundus (uterus)","score":0.6363999843597412},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.48089998960494995},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.45239999890327454},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.362199991941452},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.34310001134872437},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.3301999866962433},{"id":"https://openalex.org/keywords/medical-imaging","display_name":"Medical imaging","score":0.33009999990463257}],"concepts":[{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.8061000108718872},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7857000231742859},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6445000171661377},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6419000029563904},{"id":"https://openalex.org/C2776391266","wikidata":"https://www.wikidata.org/wiki/Q9612","display_name":"Fundus (uterus)","level":2,"score":0.6363999843597412},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.48089998960494995},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.45239999890327454},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.362199991941452},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.34310001134872437},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3301999866962433},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.33009999990463257},{"id":"https://openalex.org/C2779549770","wikidata":"https://www.wikidata.org/wiki/Q1122413","display_name":"Computer-aided diagnosis","level":2,"score":0.3199999928474426},{"id":"https://openalex.org/C2777286243","wikidata":"https://www.wikidata.org/wiki/Q5591926","display_name":"Grading (engineering)","level":2,"score":0.3172000050544739},{"id":"https://openalex.org/C193536780","wikidata":"https://www.wikidata.org/wiki/Q1513153","display_name":"Edge detection","level":4,"score":0.3140000104904175},{"id":"https://openalex.org/C2778527774","wikidata":"https://www.wikidata.org/wiki/Q159701","display_name":"Glaucoma","level":2,"score":0.31139999628067017},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.30219998955726624},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.2985000014305115},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.28679999709129333},{"id":"https://openalex.org/C206824153","wikidata":"https://www.wikidata.org/wiki/Q1169834","display_name":"Region growing","level":5,"score":0.28299999237060547},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2800999879837036},{"id":"https://openalex.org/C163892561","wikidata":"https://www.wikidata.org/wiki/Q2613728","display_name":"S\u00f8rensen\u2013Dice coefficient","level":4,"score":0.25699999928474426},{"id":"https://openalex.org/C2778818243","wikidata":"https://www.wikidata.org/wiki/Q899552","display_name":"Optical coherence tomography","level":2,"score":0.251800000667572},{"id":"https://openalex.org/C2779093074","wikidata":"https://www.wikidata.org/wiki/Q1140528","display_name":"Drusen","level":3,"score":0.2508000135421753}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bibm66473.2025.11356330","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm66473.2025.11356330","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":[],"awards":[{"id":"https://openalex.org/G1226869867","display_name":null,"funder_award_id":"62422122,62272444","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5571727189","display_name":null,"funder_award_id":"2024C03204,2023C04017,2024C03101","funder_id":"https://openalex.org/F8142712028","funder_display_name":"Key Research and Development Program of Zhejiang Province"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F8142712028","display_name":"Key Research and Development Program of Zhejiang Province","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1975630810","https://openalex.org/W2194775991","https://openalex.org/W2263495255","https://openalex.org/W2601564443","https://openalex.org/W2804179870","https://openalex.org/W2811207365","https://openalex.org/W2884436604","https://openalex.org/W2914483840","https://openalex.org/W2921406441","https://openalex.org/W2964309882","https://openalex.org/W2979448322","https://openalex.org/W2980185997","https://openalex.org/W3211490618","https://openalex.org/W4367184133","https://openalex.org/W4377233005","https://openalex.org/W4409330653","https://openalex.org/W4409367393","https://openalex.org/W4413145101"],"related_works":[],"abstract_inverted_index":{"Peripapillary":[0],"atrophy":[1],"(PPA)":[2],"is":[3],"a":[4,65,83,93,103,175],"critical":[5],"imaging":[6,200],"biomarker":[7],"for":[8,180,192,202,220],"the":[9,55,121],"diagnosis":[10,213,218],"and":[11,17,28,44,50,102,120,135,161,177,196,205],"grading":[12],"of":[13,57,132,148,157,207,214],"pathological":[14],"myopia":[15],"(PM),":[16],"its":[18],"accurate":[19],"segmentation":[20,34,67,152],"plays":[21],"an":[22,116,189,198],"essential":[23],"role":[24],"in":[25],"clinical":[26],"evaluation":[27],"longitudinal":[29],"monitoring.":[30],"However,":[31],"automatic":[32,181],"PPA":[33,118,159,182],"from":[35],"color":[36],"fundus":[37,216,222],"images":[38],"remains":[39],"challenging":[40],"due":[41],"to":[42,75,88,97,108],"blurred":[43],"discontinuous":[45],"boundaries,":[46],"low":[47],"tissue":[48,99],"contrast,":[49],"noise":[51],"interference,":[52],"which":[53],"limit":[54],"performance":[56,168],"existing":[58,140],"methods.":[59],"In":[60],"this":[61],"study,":[62],"we":[63],"propose":[64],"novel":[66],"framework,":[68],"termed":[69],"FSD-PPA":[70,81],"(Frequency-Semantic":[71],"Dual-Driven":[72],"Segmentation":[73],"Network),":[74],"address":[76],"these":[77],"limitations.":[78],"The":[79],"proposed":[80],"integrates":[82],"high-frequency":[84],"edge":[85],"extraction":[86],"module":[87,96,107],"enhance":[89],"anatomical":[90],"boundary":[91],"perception,":[92],"low-frequency":[94],"compensation":[95],"restore":[98],"structural":[100],"integrity,":[101],"multi-scale":[104],"semantic":[105],"enhancement":[106],"improve":[109],"cross-level":[110],"contextual":[111],"understanding.":[112],"Experimental":[113],"results":[114,143],"on":[115],"expert-annotated":[117],"dataset":[119,124],"public":[122],"PALM":[123],"demonstrate":[125],"that":[126],"our":[127],"method":[128],"achieves":[129],"Dice":[130],"scores":[131],"83.48":[133],"%":[134],"84.30":[136],"%,":[137],"respectively,":[138],"outperforming":[139],"approaches.":[141],"These":[142],"confirm":[144],"two":[145],"major":[146],"advantages":[147],"FSD-PPA:":[149],"(1)":[150],"high":[151],"accuracy,":[153],"enabling":[154],"precise":[155],"identification":[156],"complex":[158],"morphology;":[160],"(2)":[162],"strong":[163],"generalization":[164],"ability,":[165],"with":[166],"stable":[167],"across":[169],"different":[170],"datasets.":[171],"This":[172],"study":[173],"provides":[174],"robust":[176],"reliable":[178],"solution":[179],"segmentation.":[183],"Clinically,":[184],"it":[185],"holds":[186],"potential":[187],"as":[188],"assistive":[190],"tool":[191],"early":[193],"PM":[194],"screening":[195],"offers":[197],"objective":[199],"basis":[201],"quantitative":[203],"assessment":[204],"monitoring":[206],"myopic":[208],"progression,":[209],"thereby":[210],"facilitating":[211],"intelligent":[212],"myopia-associated":[215],"lesions.lligent":[217],"systems":[219],"myopia-related":[221],"lesions.":[223]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2026-01-30T00:00:00"}