{"id":"https://openalex.org/W2796279265","doi":"https://doi.org/10.1142/s0219467818500080","title":"VEA: Vessel Extraction Algorithm by Active Contour Model and a Novel Wavelet Analyzer for Diabetic Retinopathy Detection","display_name":"VEA: Vessel Extraction Algorithm by Active Contour Model and a Novel Wavelet Analyzer for Diabetic Retinopathy Detection","publication_year":2018,"publication_date":"2018-04-01","ids":{"openalex":"https://openalex.org/W2796279265","doi":"https://doi.org/10.1142/s0219467818500080","mag":"2796279265"},"language":"en","primary_location":{"id":"doi:10.1142/s0219467818500080","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0219467818500080","pdf_url":null,"source":{"id":"https://openalex.org/S60080701","display_name":"International Journal of Image and Graphics","issn_l":"0219-4678","issn":["0219-4678","1793-6756"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Image and Graphics","raw_type":"journal-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/A5004893982","display_name":"Swarup Kr Ghosh","orcid":"https://orcid.org/0000-0002-9312-4189"},"institutions":[{"id":"https://openalex.org/I106542073","display_name":"University of Calcutta","ror":"https://ror.org/01e7v7w47","country_code":"IN","type":"education","lineage":["https://openalex.org/I106542073"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Swarup Kr Ghosh","raw_affiliation_strings":["AKCSIT, University of Calcutta, Kolkata 700098, India"],"affiliations":[{"raw_affiliation_string":"AKCSIT, University of Calcutta, Kolkata 700098, India","institution_ids":["https://openalex.org/I106542073"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013183968","display_name":"Anupam Ghosh","orcid":"https://orcid.org/0000-0003-2166-3957"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Anupam Ghosh","raw_affiliation_strings":["Department of Computer Science and Engineering, Netaji Subhash Engineering College, Kolkata 700152, India"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Netaji Subhash Engineering College, Kolkata 700152, India","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5043543748","display_name":"Amlan Chakrabarti","orcid":"https://orcid.org/0000-0003-4380-3172"},"institutions":[{"id":"https://openalex.org/I106542073","display_name":"University of Calcutta","ror":"https://ror.org/01e7v7w47","country_code":"IN","type":"education","lineage":["https://openalex.org/I106542073"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Amlan Chakrabarti","raw_affiliation_strings":["AKCSIT, University of Calcutta, Kolkata 700098, India"],"affiliations":[{"raw_affiliation_string":"AKCSIT, University of Calcutta, Kolkata 700098, India","institution_ids":["https://openalex.org/I106542073"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5004893982"],"corresponding_institution_ids":["https://openalex.org/I106542073"],"apc_list":null,"apc_paid":null,"fwci":2.4754,"has_fulltext":false,"cited_by_count":17,"citation_normalized_percentile":{"value":0.89448567,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"18","issue":"02","first_page":"1850008","last_page":"1850008"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11438","display_name":"Retinal Imaging and Analysis","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/T11438","display_name":"Retinal Imaging and Analysis","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/T12874","display_name":"Digital Imaging for Blood Diseases","score":0.9911999702453613,"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"}},{"id":"https://openalex.org/T10170","display_name":"Retinal Diseases and Treatments","score":0.983299970626831,"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":0.718818187713623},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.7054538130760193},{"id":"https://openalex.org/keywords/diabetic-retinopathy","display_name":"Diabetic retinopathy","score":0.704566240310669},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6800369024276733},{"id":"https://openalex.org/keywords/retinal","display_name":"Retinal","score":0.618257462978363},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5759311318397522},{"id":"https://openalex.org/keywords/retina","display_name":"Retina","score":0.5398212671279907},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5346882343292236},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.5203589797019958},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4861997961997986},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4651305079460144},{"id":"https://openalex.org/keywords/wavelet-transform","display_name":"Wavelet transform","score":0.4469081461429596},{"id":"https://openalex.org/keywords/active-contour-model","display_name":"Active contour model","score":0.41706210374832153},{"id":"https://openalex.org/keywords/diabetes-mellitus","display_name":"Diabetes mellitus","score":0.19680145382881165},{"id":"https://openalex.org/keywords/ophthalmology","display_name":"Ophthalmology","score":0.16654616594314575},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.13614490628242493},{"id":"https://openalex.org/keywords/optics","display_name":"Optics","score":0.060809552669525146}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.718818187713623},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7054538130760193},{"id":"https://openalex.org/C2779829184","wikidata":"https://www.wikidata.org/wiki/Q631361","display_name":"Diabetic retinopathy","level":3,"score":0.704566240310669},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6800369024276733},{"id":"https://openalex.org/C2780827179","wikidata":"https://www.wikidata.org/wiki/Q422001","display_name":"Retinal","level":2,"score":0.618257462978363},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5759311318397522},{"id":"https://openalex.org/C2777093970","wikidata":"https://www.wikidata.org/wiki/Q169342","display_name":"Retina","level":2,"score":0.5398212671279907},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5346882343292236},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.5203589797019958},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4861997961997986},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4651305079460144},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.4469081461429596},{"id":"https://openalex.org/C112353826","wikidata":"https://www.wikidata.org/wiki/Q127313","display_name":"Active contour model","level":4,"score":0.41706210374832153},{"id":"https://openalex.org/C555293320","wikidata":"https://www.wikidata.org/wiki/Q12206","display_name":"Diabetes mellitus","level":2,"score":0.19680145382881165},{"id":"https://openalex.org/C118487528","wikidata":"https://www.wikidata.org/wiki/Q161437","display_name":"Ophthalmology","level":1,"score":0.16654616594314575},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.13614490628242493},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.060809552669525146},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"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/C134018914","wikidata":"https://www.wikidata.org/wiki/Q162606","display_name":"Endocrinology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1142/s0219467818500080","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0219467818500080","pdf_url":null,"source":{"id":"https://openalex.org/S60080701","display_name":"International Journal of Image and Graphics","issn_l":"0219-4678","issn":["0219-4678","1793-6756"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Image and Graphics","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","score":0.8100000023841858,"display_name":"Good health and well-being"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W115782596","https://openalex.org/W1091878006","https://openalex.org/W1533162639","https://openalex.org/W1586355707","https://openalex.org/W2018593404","https://openalex.org/W2021293964","https://openalex.org/W2031740343","https://openalex.org/W2037760632","https://openalex.org/W2042497109","https://openalex.org/W2057158483","https://openalex.org/W2058005326","https://openalex.org/W2104095591","https://openalex.org/W2125014106","https://openalex.org/W2130411939","https://openalex.org/W2140431812","https://openalex.org/W2142501586","https://openalex.org/W2145305441","https://openalex.org/W2150012904","https://openalex.org/W2150769593","https://openalex.org/W2166672191","https://openalex.org/W2167086999","https://openalex.org/W3103045201","https://openalex.org/W4302369956"],"related_works":["https://openalex.org/W2362796209","https://openalex.org/W2027168247","https://openalex.org/W2038488634","https://openalex.org/W2387003628","https://openalex.org/W2350259958","https://openalex.org/W2350399162","https://openalex.org/W4210537690","https://openalex.org/W2885157826","https://openalex.org/W1979702773","https://openalex.org/W2159463658"],"abstract_inverted_index":{"The":[0],"process":[1],"of":[2,10,17,38,72,101,130,136,157,159,183],"retinal":[3,28,89,131,147],"vessel":[4,103,161],"segmentation":[5,83,162],"is":[6,30,34],"important":[7],"for":[8,68,75,113,128,181],"detection":[9],"various":[11],"eye":[12],"conditions":[13],"including":[14],"the":[15,27,35,39,70,99,102,122,146,152,160,184],"effect":[16],"diabetes":[18],"on":[19,98,167],"eyes,":[20],"or":[21],"diabetic":[22,114],"retinopathy.":[23,115],"As":[24],"we":[25,77,94,177],"know,":[26],"microvasculature":[29],"unique":[31],"since":[32],"it":[33],"only":[36],"part":[37],"human":[40],"circulation":[41],"system":[42,112],"that":[43,85,125],"can":[44],"be":[45],"directly":[46],"and":[47,107,134,139,150,164],"non-evasively":[48],"visualized":[49],"in":[50,87],"vivo;":[51],"readily":[52],"photographed":[53],"as":[54,56,121],"well":[55],"subjected":[57],"to":[58,144],"digital":[59],"image":[60,82,169],"analysis.":[61],"This":[62,116],"paper":[63,117],"explores":[64],"a":[65],"new":[66],"technique":[67],"detecting":[69,88],"idiosyncrasies":[71],"retina":[73,105],"images,":[74],"which":[76],"have":[78,95,178],"reviewed":[79],"some":[80],"well-known":[81],"algorithms":[84],"help":[86],"abnormalities.":[90],"In":[91,174],"this":[92,175],"work,":[93],"also":[96],"focused":[97],"extraction":[100],"from":[104],"images":[106],"developed":[108],"an":[109,155],"automated":[110],"diagnostic":[111],"represents":[118],"techniques,":[119],"such":[120],"snake":[123],"model":[124],"was":[126],"used":[127,179],"auto-extraction":[129],"blood":[132],"vessels":[133,148],"use":[135],"wavelet":[137,165],"decomposition":[138],"back":[140],"propagation":[141],"neural":[142],"network":[143],"extract":[145],"features":[149],"analyze":[151],"dataset.":[153],"Finally,":[154],"analysis":[156,166],"performance":[158],"algorithm":[163],"standard":[168],"databases":[170],"has":[171],"been":[172],"done.":[173],"context,":[176],"F-score":[180],"validation":[182],"result.":[185]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}