{"id":"https://openalex.org/W4400908843","doi":"https://doi.org/10.1109/siu61531.2024.10600987","title":"A Study on the Segmentation and Classification of Diabetic Retinopathy Images Using the K-Means Clustering Method","display_name":"A Study on the Segmentation and Classification of Diabetic Retinopathy Images Using the K-Means Clustering Method","publication_year":2024,"publication_date":"2024-05-15","ids":{"openalex":"https://openalex.org/W4400908843","doi":"https://doi.org/10.1109/siu61531.2024.10600987"},"language":"en","primary_location":{"id":"doi:10.1109/siu61531.2024.10600987","is_oa":false,"landing_page_url":"https://doi.org/10.1109/siu61531.2024.10600987","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 32nd Signal Processing and Communications Applications Conference (SIU)","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/A5092234227","display_name":"Ramazan \u0130ncir","orcid":"https://orcid.org/0000-0002-7869-9945"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Ramazan \u0130ncir","raw_affiliation_strings":["Bilgisayar Teknolojileri Bölümü, Bilgisayar Mühendisliği Bölümü,Gümüşhane Üniversitesi, Atatürk Üniversitesi Gümüşhane, Türkiye,Erzurum,Türkiye"],"affiliations":[{"raw_affiliation_string":"Bilgisayar Teknolojileri Bölümü, Bilgisayar Mühendisliği Bölümü,Gümüşhane Üniversitesi, Atatürk Üniversitesi Gümüşhane, Türkiye,Erzurum,Türkiye","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5009491457","display_name":"Ferhat Bozkurt","orcid":"https://orcid.org/0000-0003-0088-5825"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ferhat Bozkurt","raw_affiliation_strings":["Bilgisayar Teknolojileri Bölümü, Bilgisayar Mühendisliği Bölümü,Gümüşhane Üniversitesi, Atatürk Üniversitesi Gümüşhane, Türkiye,Erzurum,Türkiye"],"affiliations":[{"raw_affiliation_string":"Bilgisayar Teknolojileri Bölümü, Bilgisayar Mühendisliği Bölümü,Gümüşhane Üniversitesi, Atatürk Üniversitesi Gümüşhane, Türkiye,Erzurum,Türkiye","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5092234227"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.3823,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.84374128,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13169","display_name":"Consumer Perception and Purchasing Behavior","score":0.853600025177002,"subfield":{"id":"https://openalex.org/subfields/1406","display_name":"Marketing"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T13169","display_name":"Consumer Perception and Purchasing Behavior","score":0.853600025177002,"subfield":{"id":"https://openalex.org/subfields/1406","display_name":"Marketing"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T13243","display_name":"Innovation in Digital Healthcare Systems","score":0.8431000113487244,"subfield":{"id":"https://openalex.org/subfields/3605","display_name":"Health Information Management"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T12647","display_name":"Traditional Chinese Medicine Studies","score":0.7721999883651733,"subfield":{"id":"https://openalex.org/subfields/2707","display_name":"Complementary and alternative medicine"},"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/cluster-analysis","display_name":"Cluster analysis","score":0.6643678545951843},{"id":"https://openalex.org/keywords/diabetic-retinopathy","display_name":"Diabetic retinopathy","score":0.6513078212738037},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6242302060127258},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5938712954521179},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5830433964729309},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.5817582011222839},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.48210859298706055},{"id":"https://openalex.org/keywords/k-means-clustering","display_name":"k-means clustering","score":0.4638082981109619},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.34610283374786377},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.24412429332733154},{"id":"https://openalex.org/keywords/diabetes-mellitus","display_name":"Diabetes mellitus","score":0.2242480218410492}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6643678545951843},{"id":"https://openalex.org/C2779829184","wikidata":"https://www.wikidata.org/wiki/Q631361","display_name":"Diabetic retinopathy","level":3,"score":0.6513078212738037},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6242302060127258},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5938712954521179},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5830433964729309},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5817582011222839},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.48210859298706055},{"id":"https://openalex.org/C207968372","wikidata":"https://www.wikidata.org/wiki/Q310401","display_name":"k-means clustering","level":3,"score":0.4638082981109619},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.34610283374786377},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.24412429332733154},{"id":"https://openalex.org/C555293320","wikidata":"https://www.wikidata.org/wiki/Q12206","display_name":"Diabetes mellitus","level":2,"score":0.2242480218410492},{"id":"https://openalex.org/C134018914","wikidata":"https://www.wikidata.org/wiki/Q162606","display_name":"Endocrinology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/siu61531.2024.10600987","is_oa":false,"landing_page_url":"https://doi.org/10.1109/siu61531.2024.10600987","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 32nd Signal Processing and Communications Applications Conference (SIU)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W1522196789","https://openalex.org/W2390267673","https://openalex.org/W2120258591","https://openalex.org/W2378227553","https://openalex.org/W1584028106","https://openalex.org/W2113424041","https://openalex.org/W2385548616","https://openalex.org/W4313193953","https://openalex.org/W2967215460","https://openalex.org/W1789480965"],"abstract_inverted_index":{"Diabetic":[0],"Retinopathy":[1],"(DR)":[2],"is":[3],"a":[4],"retinal":[5],"disease":[6,49],"caused":[7],"by":[8],"diabetes,":[9],"representing":[10],"one":[11],"of":[12,17,22,29,64,68,118,126],"the":[13,36,55,60,78,88,109,112,124,127,135],"most":[14],"prevalent":[15],"causes":[16],"vision":[18],"loss":[19],"affecting":[20],"millions":[21],"people":[23],"worldwide.":[24],"Swift":[25],"detection":[26,50],"and":[27,41,51,104],"treatment":[28],"this":[30,65],"condition":[31],"are":[32],"crucial":[33],"for":[34,48],"preventing":[35],"disease.":[37],"Various":[38],"deep":[39],"learning":[40,43],"machine":[42],"algorithms":[44],"have":[45],"been":[46],"employed":[47],"classification,":[52],"often":[53],"overlooking":[54],"data":[56,61,132],"preprocessing":[57,62,133],"stage.":[58],"In":[59],"phase":[63],"study,":[66],"segmentation":[67],"important":[69],"lesions,":[70],"such":[71],"as":[72],"hard":[73],"exudates,":[74],"was":[75,94],"conducted":[76],"using":[77,97],"K-Means":[79],"clustering":[80],"method.":[81],"The":[82,91,120],"identified":[83],"lesions":[84],"were":[85],"highlighted":[86],"on":[87,108],"original":[89],"images.":[90],"resulting":[92],"dataset":[93],"then":[95],"classified":[96],"pre-trained":[98],"architectures,":[99],"namely":[100],"EfficientNetV2-M,":[101],"ResNet50,":[102],"MobileNet,":[103],"DenseNet121.":[105],"After":[106],"training":[107],"APTOS":[110],"dataset,":[111],"EfficientNetV2-M":[113],"model":[114],"achieved":[115],"an":[116],"accuracy":[117,138],"95.16%.":[119],"classification":[121,137],"results":[122],"indicated":[123],"contribution":[125],"lesion":[128],"highlighting":[129],"process":[130],"during":[131],"to":[134],"overall":[136]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2025-12-26T23:08:49.675405","created_date":"2025-10-10T00:00:00"}