{"id":"https://openalex.org/W3011381138","doi":"https://doi.org/10.1117/12.2551643","title":"Deep learning convolutional networks for image quality assessment in ultra-widefield fluorescein angiography","display_name":"Deep learning convolutional networks for image quality assessment in ultra-widefield fluorescein angiography","publication_year":2020,"publication_date":"2020-03-16","ids":{"openalex":"https://openalex.org/W3011381138","doi":"https://doi.org/10.1117/12.2551643","mag":"3011381138"},"language":"en","primary_location":{"id":"doi:10.1117/12.2551643","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2551643","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Medical Imaging 2020: Digital Pathology","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/A5023927257","display_name":"Jon Whitney","orcid":"https://orcid.org/0000-0003-2637-752X"},"institutions":[{"id":"https://openalex.org/I4210092411","display_name":"Earth Resources Technology (United States)","ror":"https://ror.org/00fhn5p96","country_code":"US","type":"company","lineage":["https://openalex.org/I4210092411"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Jon Whitney","raw_affiliation_strings":["ERT (United States)"],"affiliations":[{"raw_affiliation_string":"ERT (United States)","institution_ids":["https://openalex.org/I4210092411"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005031691","display_name":"Henry Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Henry Li","raw_affiliation_strings":["Cole Eye Institute (United States)"],"affiliations":[{"raw_affiliation_string":"Cole Eye Institute (United States)","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072863451","display_name":"Sunil K. Srivastava","orcid":"https://orcid.org/0000-0002-0398-8806"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sunil Srivastava","raw_affiliation_strings":["Cole Eye Institute (United States)"],"affiliations":[{"raw_affiliation_string":"Cole Eye Institute (United States)","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017527346","display_name":"Jenna Hach","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jenna Hach","raw_affiliation_strings":["Cole Eye Institute (United States)"],"affiliations":[{"raw_affiliation_string":"Cole Eye Institute (United States)","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108567512","display_name":"Jamie Reese","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jamie Reese","raw_affiliation_strings":["Cole Eye Institute (United States)"],"affiliations":[{"raw_affiliation_string":"Cole Eye Institute (United States)","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042719722","display_name":"Amit Vasanji","orcid":"https://orcid.org/0000-0002-6937-1921"},"institutions":[{"id":"https://openalex.org/I4210092411","display_name":"Earth Resources Technology (United States)","ror":"https://ror.org/00fhn5p96","country_code":"US","type":"company","lineage":["https://openalex.org/I4210092411"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Amit Vasanji","raw_affiliation_strings":["ERT (United States)"],"affiliations":[{"raw_affiliation_string":"ERT (United States)","institution_ids":["https://openalex.org/I4210092411"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5073193063","display_name":"Justis P. Ehlers","orcid":"https://orcid.org/0000-0001-6763-7768"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Justis Ehlers","raw_affiliation_strings":["Cole Eye Institute (United States)"],"affiliations":[{"raw_affiliation_string":"Cole Eye Institute (United States)","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5023927257"],"corresponding_institution_ids":["https://openalex.org/I4210092411"],"apc_list":null,"apc_paid":null,"fwci":0.3148,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.55234117,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":93,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"48","last_page":"48"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10170","display_name":"Retinal Diseases and Treatments","score":0.998199999332428,"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"}},"topics":[{"id":"https://openalex.org/T10170","display_name":"Retinal Diseases and Treatments","score":0.998199999332428,"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/T12599","display_name":"Retinal and Optic Conditions","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/T11438","display_name":"Retinal Imaging and Analysis","score":0.9959999918937683,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.758940577507019},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.667120099067688},{"id":"https://openalex.org/keywords/image-quality","display_name":"Image quality","score":0.6544499397277832},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.5489039421081543},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.532502293586731},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4859291613101959},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.46560174226760864},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.45155584812164307},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4305707514286041},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.42891162633895874},{"id":"https://openalex.org/keywords/receiver-operating-characteristic","display_name":"Receiver operating characteristic","score":0.42708680033683777},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.16564607620239258}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.758940577507019},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.667120099067688},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.6544499397277832},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.5489039421081543},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.532502293586731},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4859291613101959},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.46560174226760864},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.45155584812164307},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4305707514286041},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.42891162633895874},{"id":"https://openalex.org/C58471807","wikidata":"https://www.wikidata.org/wiki/Q327120","display_name":"Receiver operating characteristic","level":2,"score":0.42708680033683777},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.16564607620239258},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1117/12.2551643","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2551643","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Medical Imaging 2020: Digital Pathology","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.75,"display_name":"No poverty","id":"https://metadata.un.org/sdg/1"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4385649027","https://openalex.org/W4400094315","https://openalex.org/W4295532600","https://openalex.org/W2063823869","https://openalex.org/W2047973478","https://openalex.org/W2067569035","https://openalex.org/W4375867731","https://openalex.org/W2970784617","https://openalex.org/W2090985514","https://openalex.org/W2795259429"],"abstract_inverted_index":{"<strong>Purpose":[0],"-</strong>":[1,80,142],"Ultra-widefield":[2],"fluorescein":[3],"angiography":[4],"(UWFA)":[5],"images":[6,22,82,91,121,134,229,252],"are":[7,23],"used":[8,123,136,245],"to":[9,54,65,124,137,246,271],"assess":[10,138],"retinal,":[11],"vascular,":[12],"and":[13,49,74,108,163,188,191,209,253,273],"choroidal":[14],"abnormalities":[15],"in":[16,25,45,56,261],"retinal":[17],"disease.":[18],"During":[19],"image":[20,57,71,96,100,106,264,269,278,281],"acquisition,":[21],"taken":[24],"sequential":[26],"time":[27],"points,":[28],"which":[29],"allows":[30],"for":[31,83,184,194,283],"interrogation":[32],"of":[33,61,69,88,112,132,146,182,205,214,236,250],"vascular":[34],"features,":[35],"as":[36,38,42,153,157,161],"well":[37],"other":[39],"pathologies,":[40],"such":[41],"leakage.":[43],"Variations":[44],"eye":[46],"positioning,":[47],"injection,":[48],"camera":[50],"positioning":[51],"all":[52],"contribute":[53],"variability":[55],"quality.":[58],"The":[59,81,197,233],"purpose":[60],"this":[62,84,241],"study":[63],"was":[64,102,135],"evaluate":[66],"the":[67,126,169,172,248],"feasibility":[68],"automated":[70,173],"quality":[72,101,231,279],"classification":[73,207,223],"selection":[75],"using":[76],"deep":[77,221],"learning.":[78],"<strong>Methods":[79],"analysis":[85],"were":[86,122,151,166],"composed":[87,131],"3543":[89,120],"UWFA":[90,95,228],"obtained":[92],"during":[93,280],"standard":[94],"acquisition.":[97],"Ground":[98],"truth":[99],"assessed":[103],"by":[104,230],"expert":[105,144],"review,":[107],"classified":[109,227],"into":[110],"one":[111],"four":[113],"categories":[114],"(ungradable,":[115],"poor,":[116],"good,":[117,158],"or":[118],"best.":[119],"train":[125],"model.":[127],"A":[128],"testing":[129,170],"set":[130],"392":[133],"model":[139,224],"performance.":[140],"<strong>Results":[141],"By":[143],"review":[145],"3935":[147],"images,":[148,190],"110":[149],"(2.8%)":[150],"graded":[152],"best,":[154],"1042":[155],"(26.5%)":[156],"1156":[159],"(29.4%)":[160],"poor":[162],"1627":[164],"(41.3%)":[165],"ungradable.":[167],"In":[168],"set,":[171],"qualit":[174],"y":[175],"assessment":[176],"system":[177],"showed":[178],"an":[179,212],"overall":[180],"accuracy":[181,193,237],"88%":[183],"recognizing":[185],"between":[186],"gradable":[187],"ungradable":[189],"77%":[192],"four-category":[195],"classification.":[196],"receiver":[198],"operating":[199],"characteristic":[200],"(ROC)":[201],"curve":[202],"measuring":[203],"performance":[204],"two-class":[206],"(ungradable":[208],"gradable)":[210],"had":[211],"AUC":[213],"0.945.":[215],"<strong>Conclusions":[216],"\u2013</strong>":[217],"We":[218],"created":[219],"a":[220],"learning":[222],"that":[225,240],"automatic":[226],"category.":[232],"high":[234],"degree":[235],"provides":[238],"evidence":[239],"method":[242],"could":[243,259],"be":[244],"enhance":[247],"acquisition":[249,282],"angiogram":[251],"speed":[254],"up":[255],"clinic":[256],"workflow.":[257],"This":[258],"result":[260],"reduced":[262],"manual":[263],"grading":[265],"workload,":[266],"allow":[267],"quality-based":[268],"presentation":[270],"clinicians,":[272],"provide":[274],"near-instantaneous":[275],"feedback":[276],"on":[277],"photographers.":[284]},"counts_by_year":[{"year":2021,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
