{"id":"https://openalex.org/W3091585082","doi":"https://doi.org/10.1109/ijcnn48605.2020.9207288","title":"Retinopathy of Prematurity Stage Diagnosis Using Object Segmentation and Convolutional Neural Networks","display_name":"Retinopathy of Prematurity Stage Diagnosis Using Object Segmentation and Convolutional Neural Networks","publication_year":2020,"publication_date":"2020-07-01","ids":{"openalex":"https://openalex.org/W3091585082","doi":"https://doi.org/10.1109/ijcnn48605.2020.9207288","mag":"3091585082"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn48605.2020.9207288","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn48605.2020.9207288","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 International Joint Conference on Neural Networks (IJCNN)","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/A5103043353","display_name":"Alexander Ding","orcid":"https://orcid.org/0000-0001-6490-3573"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Alexander Ding","raw_affiliation_strings":["Commonwealth School, Boston, MA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Commonwealth School, Boston, MA, USA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055939635","display_name":"Qilei Chen","orcid":"https://orcid.org/0000-0002-4127-5524"},"institutions":[{"id":"https://openalex.org/I133738476","display_name":"University of Massachusetts Lowell","ror":"https://ror.org/03hamhx47","country_code":"US","type":"education","lineage":["https://openalex.org/I133738476"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Qilei Chen","raw_affiliation_strings":["Department Of Computer Science, University of Massachusetts Lowell, Lowell, MA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department Of Computer Science, University of Massachusetts Lowell, Lowell, MA, USA","institution_ids":["https://openalex.org/I133738476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100780032","display_name":"Yu Cao","orcid":"https://orcid.org/0000-0001-8624-1099"},"institutions":[{"id":"https://openalex.org/I133738476","display_name":"University of Massachusetts Lowell","ror":"https://ror.org/03hamhx47","country_code":"US","type":"education","lineage":["https://openalex.org/I133738476"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yu Cao","raw_affiliation_strings":["Department Of Computer Science, University of Massachusetts Lowell, Lowell, MA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department Of Computer Science, University of Massachusetts Lowell, Lowell, MA, USA","institution_ids":["https://openalex.org/I133738476"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5077348938","display_name":"Benyuan Liu","orcid":"https://orcid.org/0000-0002-7543-1054"},"institutions":[{"id":"https://openalex.org/I133738476","display_name":"University of Massachusetts Lowell","ror":"https://ror.org/03hamhx47","country_code":"US","type":"education","lineage":["https://openalex.org/I133738476"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Benyuan Liu","raw_affiliation_strings":["Department Of Computer Science, University of Massachusetts Lowell, Lowell, MA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department Of Computer Science, University of Massachusetts Lowell, Lowell, MA, USA","institution_ids":["https://openalex.org/I133738476"]}]}],"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":29,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12484","display_name":"Retinopathy of Prematurity Studies","score":1.0,"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/T12484","display_name":"Retinopathy of Prematurity Studies","score":1.0,"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/T11184","display_name":"Neonatal and fetal brain pathology","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/2735","display_name":"Pediatrics, Perinatology and Child Health"},"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":0.9909999966621399,"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":0.7870736122131348},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7818135023117065},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7747575044631958},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6404946446418762},{"id":"https://openalex.org/keywords/retinopathy-of-prematurity","display_name":"Retinopathy of prematurity","score":0.594562292098999},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5055849552154541},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4878394901752472},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.47839653491973877},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4670851230621338},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.462103009223938}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7870736122131348},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7818135023117065},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7747575044631958},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6404946446418762},{"id":"https://openalex.org/C2779918416","wikidata":"https://www.wikidata.org/wiki/Q1423087","display_name":"Retinopathy of prematurity","level":4,"score":0.594562292098999},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5055849552154541},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4878394901752472},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.47839653491973877},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4670851230621338},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.462103009223938},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0},{"id":"https://openalex.org/C2778376644","wikidata":"https://www.wikidata.org/wiki/Q2253111","display_name":"Gestational age","level":3,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C2779234561","wikidata":"https://www.wikidata.org/wiki/Q11995","display_name":"Pregnancy","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn48605.2020.9207288","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn48605.2020.9207288","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6499999761581421,"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W1536680647","https://openalex.org/W1561051169","https://openalex.org/W2005772228","https://openalex.org/W2108598243","https://openalex.org/W2118437936","https://openalex.org/W2183341477","https://openalex.org/W2255081042","https://openalex.org/W2599765304","https://openalex.org/W2800012666","https://openalex.org/W2907759749","https://openalex.org/W2920795557","https://openalex.org/W2923106228","https://openalex.org/W2942265585","https://openalex.org/W2963150697","https://openalex.org/W2977442267","https://openalex.org/W2979688847","https://openalex.org/W2980030301","https://openalex.org/W2990460508","https://openalex.org/W6761981288","https://openalex.org/W6768981810"],"related_works":["https://openalex.org/W415308517","https://openalex.org/W4255079005","https://openalex.org/W3112525243","https://openalex.org/W3129370351","https://openalex.org/W2092834228","https://openalex.org/W4386645458","https://openalex.org/W4226493464","https://openalex.org/W3133861977","https://openalex.org/W2951211570","https://openalex.org/W3103566983"],"abstract_inverted_index":{"Retinopathy":[0],"of":[1,18,44,48,69,94,116,134,217,247],"Prematurity":[2],"(ROP)":[3],"is":[4,141],"an":[5,113,154,173],"eye":[6],"disorder":[7],"primarily":[8],"affecting":[9],"premature":[10],"infants":[11],"with":[12],"lower":[13],"weights.":[14],"It":[15],"causes":[16],"proliferation":[17],"vessels":[19],"in":[20,26,66,138,177,242],"the":[21,46,53,83,92,127,130,139,142,160,169,178,182,190,198,202,207,211,245],"retina":[22,140],"and":[23,97,106,132,167,201,228],"could":[24],"result":[25],"vision":[27],"loss":[28],"and,":[29],"eventually,":[30],"retinal":[31,123],"detachment,":[32],"leading":[33],"to":[34,56,81,111,158,193,210,223],"blindness.":[35],"While":[36],"human":[37,70],"experts":[38],"can":[39],"easily":[40],"identify":[41,159],"severe":[42],"stages":[43,118],"ROP,":[45],"diagnosis":[47,84],"earlier":[49,146],"stages,":[50,148],"which":[51,102,204],"are":[52,60],"most":[54],"relevant":[55],"determining":[57],"treatment":[58],"choice,":[59],"much":[61],"more":[62],"affected":[63],"by":[64,126],"variability":[65],"subjective":[67],"interpretations":[68],"experts.":[71],"In":[72,214],"recent":[73],"years,":[74],"there":[75],"has":[76],"been":[77],"a":[78,99,135,164,185,215],"significant":[79],"effort":[80],"automate":[82],"using":[85],"deep":[86],"learning.":[87],"This":[88],"paper":[89],"builds":[90],"upon":[91],"success":[93],"previous":[95,224,240],"models":[96],"develops":[98],"novel":[100,236],"architecture,":[101],"combines":[103],"object":[104,155,225],"segmentation":[105,156,226],"convolutional":[107],"neural":[108],"networks":[109],"(CNN)":[110],"construct":[112],"effective":[114],"classifier":[115,187],"ROP":[117,147],"1-3":[119],"based":[120,188],"on":[121,189,232],"neonatal":[122],"images.":[124],"Motivated":[125],"fact":[128],"that":[129],"formation":[131],"shape":[133],"demarcation":[136,161,212],"line":[137,162],"distinguishing":[143],"feature":[144],"between":[145],"our":[149,233,235,248],"proposed":[150,249],"system":[151,183],"first":[152],"trains":[153,184],"model":[157],"at":[163],"pixel":[165],"level":[166],"adds":[168],"resulting":[170],"mask":[171],"as":[172],"additional":[174],"\"color\"":[175],"channel":[176],"original":[179,199],"image.":[180],"Then,":[181],"CNN":[186],"processed":[191],"images":[192],"leverage":[194],"information":[195],"from":[196],"both":[197],"image":[200],"mask,":[203],"helps":[205],"direct":[206],"model's":[208],"attention":[209],"line.":[213],"number":[216],"careful":[218],"experiments":[219],"comparing":[220],"its":[221],"performance":[222],"systems":[227,230,241],"CNN-only":[229],"trained":[231],"dataset,":[234],"architecture":[237],"significantly":[238],"outperforms":[239],"accuracy,":[243],"demonstrating":[244],"effectiveness":[246],"pipeline.":[250]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":9},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}