{"id":"https://openalex.org/W3011614460","doi":"https://doi.org/10.1117/12.2547763","title":"Choroidal atrophy segmentation based on deep network with deep-supervision and EDT-auxiliary-loss","display_name":"Choroidal atrophy segmentation based on deep network with deep-supervision and EDT-auxiliary-loss","publication_year":2020,"publication_date":"2020-03-10","ids":{"openalex":"https://openalex.org/W3011614460","doi":"https://doi.org/10.1117/12.2547763","mag":"3011614460"},"language":"en","primary_location":{"id":"doi:10.1117/12.2547763","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2547763","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Medical Imaging 2020: Image Processing","raw_type":"proceedings-article"},"type":"article","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/A5041550104","display_name":"Ruyi Lu","orcid":null},"institutions":[{"id":"https://openalex.org/I3923682","display_name":"Soochow University","ror":"https://ror.org/05t8y2r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I3923682"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ruyi Lu","raw_affiliation_strings":["Soochow Univ. (China)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Soochow Univ. (China)","institution_ids":["https://openalex.org/I3923682"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058024483","display_name":"Weifang Zhu","orcid":"https://orcid.org/0000-0001-9540-4101"},"institutions":[{"id":"https://openalex.org/I354108","display_name":"Minjiang University","ror":"https://ror.org/00s7tkw17","country_code":"CN","type":"education","lineage":["https://openalex.org/I354108"]},{"id":"https://openalex.org/I3923682","display_name":"Soochow University","ror":"https://ror.org/05t8y2r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I3923682"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weifang Zhu","raw_affiliation_strings":["Minjiang Univ. (China)","Soochow Univ. (China)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Minjiang Univ. (China)","institution_ids":["https://openalex.org/I354108"]},{"raw_affiliation_string":"Soochow Univ. (China)","institution_ids":["https://openalex.org/I3923682"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079122160","display_name":"Xuena Cheng","orcid":null},"institutions":[{"id":"https://openalex.org/I3923682","display_name":"Soochow University","ror":"https://ror.org/05t8y2r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I3923682"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuena Cheng","raw_affiliation_strings":["Soochow Univ. (China)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Soochow Univ. (China)","institution_ids":["https://openalex.org/I3923682"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079807652","display_name":"Xinjian Chen","orcid":"https://orcid.org/0000-0002-0871-293X"},"institutions":[{"id":"https://openalex.org/I3923682","display_name":"Soochow University","ror":"https://ror.org/05t8y2r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I3923682"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinjian Chen","raw_affiliation_strings":["Soochow Univ. (China)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Soochow Univ. (China)","institution_ids":["https://openalex.org/I3923682"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5064824381","display_name":"Ivica Kopriva","orcid":"https://orcid.org/0000-0002-8610-8877"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ivica Kopriva","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.2349,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.57211799,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"68","last_page":"68"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11438","display_name":"Retinal Imaging and Analysis","score":0.9997000098228455,"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":0.9997000098228455,"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/T10250","display_name":"Glaucoma and retinal disorders","score":0.9934999942779541,"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/T10170","display_name":"Retinal Diseases and Treatments","score":0.989300012588501,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6569010019302368},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6052637100219727},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5639275312423706},{"id":"https://openalex.org/keywords/fundus","display_name":"Fundus (uterus)","score":0.49958372116088867},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4912497401237488},{"id":"https://openalex.org/keywords/merge","display_name":"Merge (version control)","score":0.45559006929397583},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.44208580255508423},{"id":"https://openalex.org/keywords/atrophy","display_name":"Atrophy","score":0.4323290288448334},{"id":"https://openalex.org/keywords/euclidean-distance","display_name":"Euclidean distance","score":0.4253779351711273},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3712085485458374},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3664551377296448},{"id":"https://openalex.org/keywords/ophthalmology","display_name":"Ophthalmology","score":0.20606309175491333},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.18928757309913635}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6569010019302368},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6052637100219727},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5639275312423706},{"id":"https://openalex.org/C2776391266","wikidata":"https://www.wikidata.org/wiki/Q9612","display_name":"Fundus (uterus)","level":2,"score":0.49958372116088867},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4912497401237488},{"id":"https://openalex.org/C197129107","wikidata":"https://www.wikidata.org/wiki/Q1921621","display_name":"Merge (version control)","level":2,"score":0.45559006929397583},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.44208580255508423},{"id":"https://openalex.org/C2781172350","wikidata":"https://www.wikidata.org/wiki/Q194520","display_name":"Atrophy","level":2,"score":0.4323290288448334},{"id":"https://openalex.org/C120174047","wikidata":"https://www.wikidata.org/wiki/Q847073","display_name":"Euclidean distance","level":2,"score":0.4253779351711273},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3712085485458374},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3664551377296448},{"id":"https://openalex.org/C118487528","wikidata":"https://www.wikidata.org/wiki/Q161437","display_name":"Ophthalmology","level":1,"score":0.20606309175491333},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.18928757309913635},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1117/12.2547763","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2547763","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Medical Imaging 2020: Image Processing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.46000000834465027,"display_name":"Partnerships for the goals","id":"https://metadata.un.org/sdg/17"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4234886518","https://openalex.org/W2389591058","https://openalex.org/W2382112581","https://openalex.org/W3124036233","https://openalex.org/W4229787472","https://openalex.org/W2486541857","https://openalex.org/W2108840191","https://openalex.org/W2759366996","https://openalex.org/W2110679372","https://openalex.org/W2354081742"],"abstract_inverted_index":{"The":[0,153,183,192],"prevalence":[1],"of":[2,12,20,99,119,143,167],"myopia":[3,176,181],"is":[4,37,68,109,139,148],"rapidly":[5],"increasing":[6],"worldwide.":[7],"Along":[8],"with":[9,188],"the":[10,51,62,86,97,141,197],"deepening":[11],"myopia,":[13],"there":[14],"will":[15],"be":[16],"various":[17],"pathological":[18],"changes":[19],"retina,":[21],"such":[22],"as":[23,50],"choroidal":[24,26,42,203],"atrophy,":[25],"neovascularization,":[27],"etc.":[28],"In":[29,61],"this":[30],"paper,":[31],"a":[32,104],"U-Net":[33,49],"based":[34],"deep":[35],"network":[36,185],"proposed":[38,154,184,198],"to":[39,73,90,151],"automatically":[40],"segment":[41,202],"atrophy":[43,204],"in":[44],"fundus":[45,169],"images.":[46],"We":[47,79],"use":[48],"main":[52],"structure,":[53],"which":[54,108,147,165],"can":[55,200],"learn":[56],"rich":[57],"hierarchical":[58],"feature":[59,77],"representations.":[60],"decoder":[63],"path,":[64],"Squeeze-and-Excitation":[65],"(SE)":[66],"block":[67],"employed":[69],"before":[70],"each":[71],"deconvolution":[72],"adaptively":[74],"recalibrate":[75],"channel":[76],"response.":[78],"introduce":[80],"deep-supervision":[81],"mechanism":[82],"and":[83,125,178,205],"merge":[84],"all":[85],"early":[87],"prediction":[88,93],"maps":[89],"obtain":[91],"final":[92],"map.":[94,133],"To":[95],"ensure":[96],"smoothness":[98],"segmentation":[100],"results,":[101],"we":[102],"propose":[103],"new":[105],"loss":[106,121,130],"function,":[107],"termed":[110],"EDT-auxiliary-loss":[111,117],"(Euclidean":[112],"distance":[113,132],"transformation":[114],"auxiliary":[115],"loss).":[116],"consists":[118,166],"Dice":[120],"for":[122,131,136],"ground":[123],"truth":[124],"mean":[126],"square":[127],"error":[128],"(MSE)":[129],"Another":[134],"strategy":[135],"performance":[137,208],"improvement":[138],"utilizing":[140],"information":[142],"optic":[144],"disc":[145],"(OD),":[146],"usually":[149],"adjacent":[150],"atrophy.":[152],"method":[155,199],"was":[156,186],"evaluated":[157],"on":[158],"ISBI":[159],"2019":[160],"Pathologic":[161],"Myopia":[162],"Challenge":[163],"dataset,":[164],"400":[168],"images":[170],"from161":[171],"normal":[172],"eyes,":[173],"26":[174],"high":[175],"eyes":[177],"213":[179],"pathologic":[180],"eyes.":[182],"validated":[187],"four-fold":[189],"cross":[190],"validation.":[191],"experiment":[193],"results":[194],"show":[195],"that":[196],"successfully":[201],"achieve":[206],"better":[207],"than":[209],"traditional":[210],"U-Net.":[211]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
