{"id":"https://openalex.org/W2588347501","doi":"https://doi.org/10.1109/ssci.2016.7849956","title":"Automated blood vessel segmentation of fundus images using region features of vessels","display_name":"Automated blood vessel segmentation of fundus images using region features of vessels","publication_year":2016,"publication_date":"2016-12-01","ids":{"openalex":"https://openalex.org/W2588347501","doi":"https://doi.org/10.1109/ssci.2016.7849956","mag":"2588347501"},"language":"en","primary_location":{"id":"doi:10.1109/ssci.2016.7849956","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ssci.2016.7849956","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE Symposium Series on Computational Intelligence (SSCI)","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/A5043499959","display_name":"Zhun Fan","orcid":"https://orcid.org/0000-0002-4232-8229"},"institutions":[{"id":"https://openalex.org/I32574673","display_name":"Shantou University","ror":"https://ror.org/01a099706","country_code":"CN","type":"education","lineage":["https://openalex.org/I32574673"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhun Fan","raw_affiliation_strings":["Department of Electronic Engineering, Shantou University, Shantou, Guangdong"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, Shantou University, Shantou, Guangdong","institution_ids":["https://openalex.org/I32574673"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076499682","display_name":"Jiewei Lu","orcid":"https://orcid.org/0000-0001-5342-0939"},"institutions":[{"id":"https://openalex.org/I32574673","display_name":"Shantou University","ror":"https://ror.org/01a099706","country_code":"CN","type":"education","lineage":["https://openalex.org/I32574673"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiewei Lu","raw_affiliation_strings":["Department of Electronic Engineering, Shantou University, Shantou, Guangdong"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, Shantou University, Shantou, Guangdong","institution_ids":["https://openalex.org/I32574673"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5041255503","display_name":"Yibiao Rong","orcid":"https://orcid.org/0000-0002-8776-9415"},"institutions":[{"id":"https://openalex.org/I32574673","display_name":"Shantou University","ror":"https://ror.org/01a099706","country_code":"CN","type":"education","lineage":["https://openalex.org/I32574673"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yibiao Rong","raw_affiliation_strings":["Department of Electronic Engineering, Shantou University, Shantou, Guangdong"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, Shantou University, Shantou, Guangdong","institution_ids":["https://openalex.org/I32574673"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I32574673"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":10,"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/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/T10250","display_name":"Glaucoma and retinal disorders","score":0.9943000078201294,"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":0.9905999898910522,"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":0.8424238562583923},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6598267555236816},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6580064296722412},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.5965997576713562},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5735794901847839},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.554309070110321},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5514631271362305},{"id":"https://openalex.org/keywords/binary-image","display_name":"Binary image","score":0.5407782196998596},{"id":"https://openalex.org/keywords/connected-component-labeling","display_name":"Connected-component labeling","score":0.4802963435649872},{"id":"https://openalex.org/keywords/fundus","display_name":"Fundus (uterus)","score":0.45348450541496277},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.34309518337249756},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.30810707807540894},{"id":"https://openalex.org/keywords/scale-space-segmentation","display_name":"Scale-space segmentation","score":0.2642613649368286}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8424238562583923},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6598267555236816},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6580064296722412},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5965997576713562},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5735794901847839},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.554309070110321},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5514631271362305},{"id":"https://openalex.org/C193828747","wikidata":"https://www.wikidata.org/wiki/Q864118","display_name":"Binary image","level":4,"score":0.5407782196998596},{"id":"https://openalex.org/C58737948","wikidata":"https://www.wikidata.org/wiki/Q3136397","display_name":"Connected-component labeling","level":5,"score":0.4802963435649872},{"id":"https://openalex.org/C2776391266","wikidata":"https://www.wikidata.org/wiki/Q9612","display_name":"Fundus (uterus)","level":2,"score":0.45348450541496277},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.34309518337249756},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.30810707807540894},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.2642613649368286},{"id":"https://openalex.org/C118487528","wikidata":"https://www.wikidata.org/wiki/Q161437","display_name":"Ophthalmology","level":1,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ssci.2016.7849956","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ssci.2016.7849956","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE Symposium Series on Computational Intelligence (SSCI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.49000000953674316,"id":"https://metadata.un.org/sdg/14","display_name":"Life below water"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W1564419782","https://openalex.org/W2010965043","https://openalex.org/W2018593404","https://openalex.org/W2033723371","https://openalex.org/W2051578148","https://openalex.org/W2078239496","https://openalex.org/W2104195344","https://openalex.org/W2105839704","https://openalex.org/W2105923875","https://openalex.org/W2112251921","https://openalex.org/W2112783556","https://openalex.org/W2115680416","https://openalex.org/W2116628223","https://openalex.org/W2118246710","https://openalex.org/W2121913681","https://openalex.org/W2123434300","https://openalex.org/W2129098176","https://openalex.org/W2139915254","https://openalex.org/W2145305441","https://openalex.org/W2150769593","https://openalex.org/W2163344010","https://openalex.org/W2170092083","https://openalex.org/W2171459511","https://openalex.org/W2400557149","https://openalex.org/W6712637581"],"related_works":["https://openalex.org/W3186605777","https://openalex.org/W3107295340","https://openalex.org/W2574769845","https://openalex.org/W146855993","https://openalex.org/W2220864757","https://openalex.org/W2071355008","https://openalex.org/W2170080636","https://openalex.org/W1982749290","https://openalex.org/W3080815883","https://openalex.org/W2378792248"],"abstract_inverted_index":{"This":[0],"paper":[1],"proposes":[2],"a":[3,20,27,128],"novel":[4],"and":[5,36,94,123,134,142,151],"simple":[6,95],"unsupervised":[7,122],"vessel":[8,48,55,72,87,108,129],"segmentation":[9,130],"algorithm":[10,112],"using":[11],"fundus":[12,21],"images.":[13,64],"At":[14],"first,":[15],"the":[16,31,41,54,59,66,77,100,106],"green":[17],"channel":[18],"of":[19,132,140],"image":[22,29,39],"is":[23],"preprocessed":[24],"to":[25,53,69],"extract":[26],"binary":[28,38,63],"after":[30],"isotropic":[32],"undecimated":[33],"wavelet":[34],"transform,":[35],"another":[37],"from":[40,146],"morphologically":[42],"reconstructed":[43],"image.":[44],"Secondly,":[45],"two":[46,85,147],"initial":[47,71,86],"images":[49,73,88,145],"are":[50,74,89,103],"extracted":[51,75],"according":[52],"region":[56],"features":[57],"for":[58],"connected":[60],"regions":[61,67],"in":[62,84,136],"Next,":[65],"common":[68],"both":[70],"as":[76],"major":[78,101],"vessels.":[79],"Then":[80],"all":[81],"remaining":[82],"pixels":[83],"processed":[90,107],"with":[91,105,118],"skeleton":[92],"extraction":[93],"linear":[96],"iterative":[97],"clustering.":[98],"Finally":[99],"vessels":[102],"combined":[104],"pixels.":[109],"The":[110],"proposed":[111],"outperforms":[113],"its":[114],"competitors":[115],"when":[116],"compared":[117],"other":[119],"widely":[120],"used":[121],"supervised":[124],"methods,":[125],"which":[126],"achieves":[127],"accuracy":[131],"95.8%":[133,135],"an":[137],"average":[138],"time":[139],"9.7s":[141],"14.6s":[143],"on":[144],"public":[148],"datasets":[149],"DRIVE":[150],"STARE,":[152],"respectively.":[153]},"counts_by_year":[{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}