{"id":"https://openalex.org/W2922255001","doi":"https://doi.org/10.1117/12.2510446","title":"Computerized assessment of glaucoma severity based on color fundus images","display_name":"Computerized assessment of glaucoma severity based on color fundus images","publication_year":2019,"publication_date":"2019-03-15","ids":{"openalex":"https://openalex.org/W2922255001","doi":"https://doi.org/10.1117/12.2510446","mag":"2922255001"},"language":"en","primary_location":{"id":"doi:10.1117/12.2510446","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2510446","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Medical Imaging 2019: Biomedical Applications in Molecular, Structural, and Functional Imaging","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/A5100409994","display_name":"Jian Zhang","orcid":"https://orcid.org/0000-0002-7240-3541"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jian Zhang","raw_affiliation_strings":["Shaanxi Provincial People\u2019s Hospital (China)","Shaanxi Provincial People's Hospital (China)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shaanxi Provincial People\u2019s Hospital (China)","institution_ids":[]},{"raw_affiliation_string":"Shaanxi Provincial People's Hospital (China)","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100442532","display_name":"Hang Chen","orcid":"https://orcid.org/0000-0003-1410-4284"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hang Chen","raw_affiliation_strings":["Shaanxi Provincial People\u2019s Hospital (China)","Shaanxi Provincial People's Hospital (China)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shaanxi Provincial People\u2019s Hospital (China)","institution_ids":[]},{"raw_affiliation_string":"Shaanxi Provincial People's Hospital (China)","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100435890","display_name":"Lei Wang","orcid":"https://orcid.org/0000-0002-3024-8627"},"institutions":[{"id":"https://openalex.org/I170201317","display_name":"University of Pittsburgh","ror":"https://ror.org/01an3r305","country_code":"US","type":"education","lineage":["https://openalex.org/I170201317"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Lei Wang","raw_affiliation_strings":["Univ. of Pittsburgh (United States)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Univ. of Pittsburgh (United States)","institution_ids":["https://openalex.org/I170201317"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041650010","display_name":"Jiantao Pu","orcid":"https://orcid.org/0000-0003-2127-5313"},"institutions":[{"id":"https://openalex.org/I170201317","display_name":"University of Pittsburgh","ror":"https://ror.org/01an3r305","country_code":"US","type":"education","lineage":["https://openalex.org/I170201317"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jiantao Pu","raw_affiliation_strings":["Univ. of Pittsburgh (United States)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Univ. of Pittsburgh (United States)","institution_ids":["https://openalex.org/I170201317"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100448105","display_name":"Han Liu","orcid":"https://orcid.org/0000-0002-6618-1380"},"institutions":[{"id":"https://openalex.org/I170201317","display_name":"University of Pittsburgh","ror":"https://ror.org/01an3r305","country_code":"US","type":"education","lineage":["https://openalex.org/I170201317"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Han Liu","raw_affiliation_strings":["Univ. of Pittsburgh (United States)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Univ. of Pittsburgh (United States)","institution_ids":["https://openalex.org/I170201317"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"2015","issue":null,"first_page":"72","last_page":"72"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11438","display_name":"Retinal Imaging and Analysis","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9979000091552734,"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/T12874","display_name":"Digital Imaging for Blood Diseases","score":0.9767000079154968,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.7967536449432373},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6377484798431396},{"id":"https://openalex.org/keywords/fundus","display_name":"Fundus (uterus)","score":0.5941433906555176},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5469468235969543},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.545331597328186},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4767526090145111},{"id":"https://openalex.org/keywords/glaucoma","display_name":"Glaucoma","score":0.4504941999912262},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.4149250090122223},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3993144631385803},{"id":"https://openalex.org/keywords/ophthalmology","display_name":"Ophthalmology","score":0.22327730059623718},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.20794197916984558},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.18973636627197266}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7967536449432373},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6377484798431396},{"id":"https://openalex.org/C2776391266","wikidata":"https://www.wikidata.org/wiki/Q9612","display_name":"Fundus (uterus)","level":2,"score":0.5941433906555176},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5469468235969543},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.545331597328186},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4767526090145111},{"id":"https://openalex.org/C2778527774","wikidata":"https://www.wikidata.org/wiki/Q159701","display_name":"Glaucoma","level":2,"score":0.4504941999912262},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.4149250090122223},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3993144631385803},{"id":"https://openalex.org/C118487528","wikidata":"https://www.wikidata.org/wiki/Q161437","display_name":"Ophthalmology","level":1,"score":0.22327730059623718},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.20794197916984558},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.18973636627197266}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1117/12.2510446","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2510446","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Medical Imaging 2019: Biomedical Applications in Molecular, Structural, and Functional Imaging","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":48,"referenced_works":["https://openalex.org/W7444089","https://openalex.org/W1677182931","https://openalex.org/W1686810756","https://openalex.org/W1836465849","https://openalex.org/W1969241653","https://openalex.org/W1977941417","https://openalex.org/W2025049031","https://openalex.org/W2077275296","https://openalex.org/W2081178133","https://openalex.org/W2089479074","https://openalex.org/W2097117768","https://openalex.org/W2117539524","https://openalex.org/W2183341477","https://openalex.org/W2187731819","https://openalex.org/W2194775991","https://openalex.org/W2253535767","https://openalex.org/W2266451716","https://openalex.org/W2330025265","https://openalex.org/W2512450393","https://openalex.org/W2531409750","https://openalex.org/W2557738935","https://openalex.org/W2592929672","https://openalex.org/W2618530766","https://openalex.org/W2741033153","https://openalex.org/W2750580920","https://openalex.org/W2769913741","https://openalex.org/W2788633781","https://openalex.org/W2789717942","https://openalex.org/W2791412124","https://openalex.org/W2963446712","https://openalex.org/W2964081807","https://openalex.org/W2964350391","https://openalex.org/W4251782597","https://openalex.org/W4285051141","https://openalex.org/W6637373629","https://openalex.org/W6638667902","https://openalex.org/W6642698431","https://openalex.org/W6674914833","https://openalex.org/W6683566454","https://openalex.org/W6684191040","https://openalex.org/W6686164453","https://openalex.org/W6687483927","https://openalex.org/W6691419123","https://openalex.org/W6693552096","https://openalex.org/W6694260854","https://openalex.org/W6725739302","https://openalex.org/W6728184133","https://openalex.org/W6741414320"],"related_works":["https://openalex.org/W4205257730","https://openalex.org/W3047257194","https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3193565141","https://openalex.org/W3133861977","https://openalex.org/W2951211570","https://openalex.org/W3167935049","https://openalex.org/W3103566983","https://openalex.org/W3029198973"],"abstract_inverted_index":{"In":[0],"this":[1],"study,":[2],"the":[3,11,47,67,72,106,138,170],"deep":[4],"learning":[5],"technology":[6],"was":[7],"used":[8],"to":[9,57,186],"grade":[10],"severity":[12],"of":[13,25,49,63,118],"glaucoma":[14,35],"depicted":[15],"on":[16,30,126,177],"color":[17],"fundus":[18,27],"images.":[19,76,193],"We":[20],"retrospectively":[21],"collected":[22],"a":[23],"dataset":[24],"5,978":[26],"images":[28,54,70],"acquired":[29],"different":[31],"subjects":[32],"and":[33,60,71,97,111,120,128,131,133,143,162],"their":[34],"severities":[36],"were":[37,55,79],"annotated":[38],"as":[39,184],"none,":[40],"mild,":[41],"moderate,":[42],"or":[43],"severe,":[44],"respectively,":[45],"by":[46],"consensus":[48],"two":[50],"experienced":[51],"ophthalmologists.":[52],"These":[53,77],"preprocessed":[56],"generate":[58],"global":[59,68,127,161,182],"local":[61,73,129,163,190],"regions":[62],"interest":[64],"(ROIs),":[65],"namely":[66],"field-of-view":[69],"disc":[74,192],"region":[75],"ROIs":[78],"separately":[80],"fed":[81],"into":[82],"eight":[83],"classical":[84],"convolutional":[85],"neural":[86],"networks":[87],"(CNNs)":[88],"(i.e.,":[89,174],"VGG16,":[90],"VGG19,":[91,112],"ResNet,":[92],"DenseNet,":[93],"InceptionV3,":[94],"InceptionResNet,":[95],"Xception,":[96],"NASNetMobile)":[98],"for":[99,159],"classification":[100,172],"purposes.":[101],"Experimental":[102],"results":[103],"demonstrated":[104],"that":[105],"available":[107],"CNNs,":[108,167],"except":[109],"VGG16":[110,142],"achieved":[113,145],"average":[114],"quadratic":[115],"kappa":[116],"scores":[117],"80.36%":[119],"78.22%":[121],"when":[122,135,148,155,180,188],"trained":[123,149],"from":[124,150],"scratch":[125],"ROIs,":[130],"85.29%":[132],"82.72%":[134],"fine-tuned":[136],"using":[137,156,181,189],"imagenet":[139,157],"weights,":[140],"respectively.":[141],"VGG19":[144],"reasonable":[146],"accuracy":[147,173],"scratch,":[151],"but":[152],"they":[153],"failed":[154],"weights":[158,179],"both":[160],"ROIs.":[164],"Among":[165],"these":[166],"DenseNet":[168],"had":[169],"highest":[171],"75.50%)":[175],"based":[176],"pre-trained":[178],"images,":[183],"compared":[185],"65.50%":[187],"optic":[191]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":3},{"year":2019,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
