{"id":"https://openalex.org/W7127059694","doi":"https://doi.org/10.1080/03772063.2026.2616248","title":"MSFCS-Net: A Dual-Decoder Architecture for an Efficient Segmentation of Optic Disc and Optic Cup","display_name":"MSFCS-Net: A Dual-Decoder Architecture for an Efficient Segmentation of Optic Disc and Optic Cup","publication_year":2026,"publication_date":"2026-02-01","ids":{"openalex":"https://openalex.org/W7127059694","doi":"https://doi.org/10.1080/03772063.2026.2616248"},"language":"en","primary_location":{"id":"doi:10.1080/03772063.2026.2616248","doi":"https://doi.org/10.1080/03772063.2026.2616248","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03772063.2026.2616248","pdf_url":null,"source":{"id":"https://openalex.org/S158263287","display_name":"IETE Journal of Research","issn_l":"0377-2063","issn":["0377-2063","0974-780X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","dongbi-d","jufo-1","norway-1","poland-40","russia-white-list-2"],"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547","https://openalex.org/P4310320449"],"host_organization_lineage_names":["Taylor & Francis","Informa"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IETE Journal of Research","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"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/A5103958319","display_name":"Kowju Gayatri","orcid":"https://orcid.org/0000-0001-5813-0084","observed_orcids":["https://orcid.org/0000-0001-5813-0084"]},"institutions":[{"id":"https://openalex.org/I100887729","display_name":"Andhra University","ror":"https://ror.org/049skhf47","country_code":"IN","type":"education","lineage":["https://openalex.org/I100887729"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Kowju Gayatri","raw_affiliation_strings":["AU College of Engineering, Andhra University"],"raw_orcid":"https://orcid.org/0000-0001-5813-0084","affiliations":[{"raw_affiliation_string":"AU College of Engineering, Andhra University","institution_ids":["https://openalex.org/I100887729"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036773016","display_name":"Birendra Biswal","orcid":"https://orcid.org/0000-0002-6848-3729","observed_orcids":["https://orcid.org/0000-0002-6848-3729"]},"institutions":[{"id":"https://openalex.org/I4405263749","display_name":"Gayatri Vidya Parishad College of Engineering for Women","ror":"https://ror.org/05pw0an27","country_code":"IN","type":"education","lineage":["https://openalex.org/I4405263749"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Birendra Biswal","raw_affiliation_strings":["GVP College of Engineering"],"raw_orcid":"https://orcid.org/0000-0002-6848-3729","affiliations":[{"raw_affiliation_string":"GVP College of Engineering","institution_ids":["https://openalex.org/I4405263749"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5084841781","display_name":"Singam Aruna","orcid":"https://orcid.org/0000-0002-5411-9221","observed_orcids":["https://orcid.org/0000-0002-5411-9221"]},"institutions":[{"id":"https://openalex.org/I100887729","display_name":"Andhra University","ror":"https://ror.org/049skhf47","country_code":"IN","type":"education","lineage":["https://openalex.org/I100887729"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Singam Aruna","raw_affiliation_strings":["AU College of Engineering, Andhra University"],"raw_orcid":"https://orcid.org/0000-0002-5411-9221","affiliations":[{"raw_affiliation_string":"AU College of Engineering, Andhra University","institution_ids":["https://openalex.org/I100887729"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.8925,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.82452039,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"72","issue":"5-6","first_page":"1461","last_page":"1479"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11438","display_name":"Retinal Imaging and Analysis","score":0.9994999766349792,"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":0.9994999766349792,"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.00019999999494757503,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.0,"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/optic-disc-segmentation","display_name":"optic disc segmentation","score":0.9909999966621399},{"id":"https://openalex.org/keywords/optic-cup-segmentation","display_name":"optic cup segmentation","score":0.9990000128746033},{"id":"https://openalex.org/keywords/glaucoma-diagnosis","display_name":"glaucoma diagnosis","score":0.8220000267028809},{"id":"https://openalex.org/keywords/fundus-images","display_name":"fundus images","score":0.871999979019165},{"id":"https://openalex.org/keywords/multi-scale-encoder","display_name":"multi-scale encoder","score":0.7599999904632568},{"id":"https://openalex.org/keywords/triple-attention-mechanism","display_name":"triple attention mechanism","score":0.9129999876022339},{"id":"https://openalex.org/keywords/dual-decoder","display_name":"dual decoder","score":0.8830000162124634}],"concepts":[{"id":"https://openalex.org/C96021297","wikidata":"https://www.wikidata.org/wiki/Q7098791","display_name":"Optic cup (embryology)","level":5,"score":0.7103999853134155},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6161999702453613},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6110000014305115},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6105999946594238},{"id":"https://openalex.org/C2779735895","wikidata":"https://www.wikidata.org/wiki/Q16873995","display_name":"Optic disc","level":3,"score":0.5809999704360962},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5802000164985657},{"id":"https://openalex.org/C194232370","wikidata":"https://www.wikidata.org/wiki/Q162","display_name":"Optical fiber","level":2,"score":0.429500013589859},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.41029998660087585},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4004000127315521},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.3010999858379364},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.296099990606308},{"id":"https://openalex.org/C199639397","wikidata":"https://www.wikidata.org/wiki/Q1788588","display_name":"Engineering drawing","level":1,"score":0.2639000117778778},{"id":"https://openalex.org/C98025372","wikidata":"https://www.wikidata.org/wiki/Q477538","display_name":"Systems architecture","level":3,"score":0.2533999979496002}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1080/03772063.2026.2616248","doi":"https://doi.org/10.1080/03772063.2026.2616248","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03772063.2026.2616248","pdf_url":null,"source":{"id":"https://openalex.org/S158263287","display_name":"IETE Journal of Research","issn_l":"0377-2063","issn":["0377-2063","0974-780X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","dongbi-d","jufo-1","norway-1","poland-40","russia-white-list-2"],"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547","https://openalex.org/P4310320449"],"host_organization_lineage_names":["Taylor & Francis","Informa"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IETE Journal of Research","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8048999905586243,"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3"}],"study_designs":[],"awards":[{"id":"https://openalex.org/G5868146129","display_name":null,"funder_award_id":"CRG\u00a0/2023/005474","funder_id":"https://openalex.org/F4320334771","funder_display_name":"Science and Engineering Research Board"}],"funders":[{"id":"https://openalex.org/F4320334771","display_name":"Science and Engineering Research Board","ror":"https://ror.org/03ffdsr55"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":45,"referenced_works":["https://openalex.org/W1974969377","https://openalex.org/W2006476492","https://openalex.org/W2034786340","https://openalex.org/W2782364420","https://openalex.org/W2901615768","https://openalex.org/W2953659608","https://openalex.org/W2979448322","https://openalex.org/W2979865275","https://openalex.org/W2991498793","https://openalex.org/W3026291462","https://openalex.org/W3042346321","https://openalex.org/W3046021838","https://openalex.org/W3131680944","https://openalex.org/W3132918437","https://openalex.org/W3184038019","https://openalex.org/W3207054482","https://openalex.org/W4200316488","https://openalex.org/W4206539142","https://openalex.org/W4224023954","https://openalex.org/W4225302259","https://openalex.org/W4283656559","https://openalex.org/W4294989946","https://openalex.org/W4308322215","https://openalex.org/W4317748844","https://openalex.org/W4378571844","https://openalex.org/W4386826466","https://openalex.org/W4387740466","https://openalex.org/W4388889410","https://openalex.org/W4390848623","https://openalex.org/W4391341367","https://openalex.org/W4394910795","https://openalex.org/W4395694368","https://openalex.org/W4396622532","https://openalex.org/W4397010041","https://openalex.org/W4399039900","https://openalex.org/W4399788298","https://openalex.org/W4401359875","https://openalex.org/W4403647195","https://openalex.org/W4404341967","https://openalex.org/W4405253539","https://openalex.org/W4405760333","https://openalex.org/W4406564097","https://openalex.org/W4407622894","https://openalex.org/W4409879924","https://openalex.org/W4410352061"],"related_works":["https://openalex.org/W4294031599","https://openalex.org/W4406709427","https://openalex.org/W3091209960","https://openalex.org/W4406028182","https://openalex.org/W4416033301","https://openalex.org/W3202710872","https://openalex.org/W7213442486","https://openalex.org/W2912663195","https://openalex.org/W7153298377","https://openalex.org/W3112806607"],"abstract_inverted_index":{"Fundus":[0],"photography":[1],"significantly":[2],"enhances":[3,56],"the":[4,12,15,27,45,57,87,104,118,123,138,143,151,167,170,173,177,184,194,241,244,248],"detection":[5],"mechanism":[6,162],"of":[7,14,18,30,44,60,94,125,154,169,176,183,196,217,226,232,238],"ophthalmic":[8],"conditions":[9],"that":[10,85],"affect":[11],"vision":[13,40],"eye.":[16],"One":[17],"these":[19],"conditions,":[20],"Glaucoma,":[21],"which":[22],"is":[23,32,111,134,163],"widely":[24],"known":[25],"as":[26,209],"silent":[28],"thief":[29],"vision,":[31],"due":[33],"to":[34,63,113,121,136,145,165],"its":[35],"subtle":[36],"signs":[37],"in":[38,193],"causing":[39],"loss.":[41],"Precise":[42],"localisation":[43],"Optic":[46,50],"Cup":[47],"(OC)":[48],"&":[49],"Disc":[51],"(OD)":[52],"from":[53],"retinal":[54],"images":[55],"diagnostic":[58],"accuracy":[59,225],"Glaucoma.":[61,218],"Thus,":[62],"develop":[64],"an":[65,78,223,228],"automated":[66],"model,":[67],"this":[68,102],"research":[69],"proposes":[70],"a":[71,98,129,158,180,190,235],"Multi-Scale":[72],"Feature-driven":[73],"Condition-based":[74],"Segmentation":[75],"Network":[76,83],"(MSFCS-Net),":[77],"improved":[79],"Deep":[80],"Convolutional":[81],"Neural":[82],"(DCNN)":[84],"elevates":[86],"segmentation":[88,161,168,195],"efficiency":[89],"by":[90],"learning":[91],"feature":[92,140],"maps":[93,175],"several":[95],"sizes":[96],"using":[97,172],"multi-scale":[99],"encoder.":[100],"In":[101],"paper,":[103],"Residual":[105],"Depth-wise":[106],"Separable":[107],"Convolution":[108],"Module":[109],"(RDSCM)":[110],"employed":[112],"preserve":[114],"spatial":[115],"information,":[116],"reducing":[117],"hyperparameter":[119],"size":[120],"mitigate":[122],"burden":[124],"computational":[126],"complexity.":[127],"Furthermore,":[128],"Triple":[130],"Attention":[131],"Mechanism":[132],"(TAM)":[133],"integrated":[135],"elevate":[137],"pertinent":[139],"maps,":[141],"enabling":[142],"network":[144],"achieve":[146],"high":[147],"intra-class":[148],"variance":[149],"between":[150],"pixel":[152],"values":[153],"different":[155,204],"classes.":[156],"Additionally,":[157],"novel":[159],"condition-based":[160],"proposed":[164,249],"control":[166],"OC":[171,199],"predicted":[174],"OD":[178,197],"via":[179],"dual":[181],"decoder":[182],"MSFCS-Net.":[185],"This":[186],"model":[187,221],"has":[188],"shown":[189],"remarkable":[191],"improvement":[192],"and":[198,212,234],"regions":[200],"when":[201],"validated":[202],"with":[203,247],"publicly":[205],"available":[206],"datasets":[207],"such":[208],"REFUGE,":[210],"Rim-One,":[211],"ORIGA,":[213,242],"for":[214],"accurate":[215],"diagnosis":[216],"The":[219],"MSFCS-Net":[220],"achieved":[222],"average":[224],"99.67,":[227],"intersection":[229],"over":[230],"union":[231],"99.34":[233],"Dice":[236],"coefficient":[237],"99.66":[239],"on":[240],"outperforming":[243],"existing":[245],"models":[246],"model.":[250]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-11-10T11:39:43.021295","created_date":"2026-02-03T00:00:00"}
