{"id":"https://openalex.org/W2040003485","doi":"https://doi.org/10.1109/ispa.2013.6703831","title":"A template matching technique for artifacts detection in retinal images","display_name":"A template matching technique for artifacts detection in retinal images","publication_year":2013,"publication_date":"2013-09-01","ids":{"openalex":"https://openalex.org/W2040003485","doi":"https://doi.org/10.1109/ispa.2013.6703831","mag":"2040003485"},"language":"en","primary_location":{"id":"doi:10.1109/ispa.2013.6703831","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ispa.2013.6703831","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 8th International Symposium on Image and Signal Processing and Analysis (ISPA)","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/A5051554638","display_name":"Andr\u00e9 Mora","orcid":"https://orcid.org/0000-0003-1354-4739"},"institutions":[{"id":"https://openalex.org/I83558840","display_name":"Universidade Nova de Lisboa","ror":"https://ror.org/02xankh89","country_code":"PT","type":"education","lineage":["https://openalex.org/I83558840"]}],"countries":["PT"],"is_corresponding":true,"raw_author_name":"Andre D. Mora","raw_affiliation_strings":["Dep. of Electrical Engineering, Universidade Nova de Lisboa, Portugal","FCT, Dept. of Electr. Eng., Centre of Technol. & Syst., Univ. Nova de Lisboa, Lisbon, Portugal"],"affiliations":[{"raw_affiliation_string":"Dep. of Electrical Engineering, Universidade Nova de Lisboa, Portugal","institution_ids":["https://openalex.org/I83558840"]},{"raw_affiliation_string":"FCT, Dept. of Electr. Eng., Centre of Technol. & Syst., Univ. Nova de Lisboa, Lisbon, Portugal","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013151399","display_name":"Jo\u00e3o\u2013Bruno Soares","orcid":"https://orcid.org/0009-0009-6596-2482"},"institutions":[{"id":"https://openalex.org/I83558840","display_name":"Universidade Nova de Lisboa","ror":"https://ror.org/02xankh89","country_code":"PT","type":"education","lineage":["https://openalex.org/I83558840"]}],"countries":["PT"],"is_corresponding":false,"raw_author_name":"Joao Soares","raw_affiliation_strings":["Dep. of Electrical Engineering, Universidade Nova de Lisboa, Portugal","FCT, Dept. of Electr. Eng., Centre of Technol. & Syst., Univ. Nova de Lisboa, Lisbon, Portugal"],"affiliations":[{"raw_affiliation_string":"Dep. of Electrical Engineering, Universidade Nova de Lisboa, Portugal","institution_ids":["https://openalex.org/I83558840"]},{"raw_affiliation_string":"FCT, Dept. of Electr. Eng., Centre of Technol. & Syst., Univ. Nova de Lisboa, Lisbon, Portugal","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5010179430","display_name":"Jos\u00e9 Fonseca","orcid":"https://orcid.org/0000-0001-7173-7374"},"institutions":[{"id":"https://openalex.org/I83558840","display_name":"Universidade Nova de Lisboa","ror":"https://ror.org/02xankh89","country_code":"PT","type":"education","lineage":["https://openalex.org/I83558840"]}],"countries":["PT"],"is_corresponding":false,"raw_author_name":"Jose M. Fonseca","raw_affiliation_strings":["Dep. of Electrical Engineering, Universidade Nova de Lisboa, Portugal","FCT, Dept. of Electr. Eng., Centre of Technol. & Syst., Univ. Nova de Lisboa, Lisbon, Portugal"],"affiliations":[{"raw_affiliation_string":"Dep. of Electrical Engineering, Universidade Nova de Lisboa, Portugal","institution_ids":["https://openalex.org/I83558840"]},{"raw_affiliation_string":"FCT, Dept. of Electr. Eng., Centre of Technol. & Syst., Univ. Nova de Lisboa, Lisbon, Portugal","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5051554638"],"corresponding_institution_ids":["https://openalex.org/I83558840"],"apc_list":null,"apc_paid":null,"fwci":0.2647,"has_fulltext":false,"cited_by_count":16,"citation_normalized_percentile":{"value":0.63798088,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"717","last_page":"722"},"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":0.9958999752998352,"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9854999780654907,"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":0.8355087041854858},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7924304008483887},{"id":"https://openalex.org/keywords/artifact","display_name":"Artifact (error)","score":0.7504575252532959},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.7021279335021973},{"id":"https://openalex.org/keywords/template-matching","display_name":"Template matching","score":0.6059627532958984},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5824652910232544},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.5807997584342957},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5478926301002502},{"id":"https://openalex.org/keywords/image-quality","display_name":"Image quality","score":0.5149036645889282},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.46528711915016174},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4283994436264038},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.2849188446998596}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8355087041854858},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7924304008483887},{"id":"https://openalex.org/C2779010991","wikidata":"https://www.wikidata.org/wiki/Q2720909","display_name":"Artifact (error)","level":2,"score":0.7504575252532959},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.7021279335021973},{"id":"https://openalex.org/C158096908","wikidata":"https://www.wikidata.org/wiki/Q3983303","display_name":"Template matching","level":3,"score":0.6059627532958984},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5824652910232544},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.5807997584342957},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5478926301002502},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.5149036645889282},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.46528711915016174},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4283994436264038},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2849188446998596}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ispa.2013.6703831","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ispa.2013.6703831","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 8th International Symposium on Image and Signal Processing and Analysis (ISPA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5299999713897705,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W140620772","https://openalex.org/W165417043","https://openalex.org/W585731469","https://openalex.org/W1661242586","https://openalex.org/W1997710192","https://openalex.org/W2071315556","https://openalex.org/W2131327864","https://openalex.org/W2133059825","https://openalex.org/W2137055403","https://openalex.org/W2145305441","https://openalex.org/W2150769593","https://openalex.org/W2156028354","https://openalex.org/W2156219382","https://openalex.org/W2158518042","https://openalex.org/W2158579015","https://openalex.org/W2164603662","https://openalex.org/W2165445908","https://openalex.org/W2169428761","https://openalex.org/W2496172062","https://openalex.org/W4232415436","https://openalex.org/W6637033827","https://openalex.org/W6680096826"],"related_works":["https://openalex.org/W52840052","https://openalex.org/W3162837891","https://openalex.org/W1687852313","https://openalex.org/W3029243869","https://openalex.org/W2502336004","https://openalex.org/W1741504538","https://openalex.org/W4308623176","https://openalex.org/W4230676417","https://openalex.org/W2019696434","https://openalex.org/W2801208768"],"abstract_inverted_index":{"The":[0,92,115,168],"continuous":[1],"development":[2],"of":[3,23,57,136,175,208,228],"automatic":[4,74],"retinal":[5,90],"diseases":[6],"diagnosis":[7,75],"systems":[8,25],"based":[9],"on":[10,89],"image":[11,47,51,66,102,206],"processing":[12],"has":[13],"shown":[14],"their":[15,157],"potential":[16],"for":[17,84,183,191,210,216],"clinical":[18],"practice.":[19],"However,":[20],"the":[21,32,37,46,64,95,128,144,150,184,188,195,198,211,217,226,229],"accuracy":[22],"these":[24],"is":[26,82,99,105],"often":[27],"compromised,":[28],"mainly":[29],"due":[30,42],"to":[31,43,107,123,127],"intrinsic":[33],"difficulty":[34],"in":[35,45],"detecting":[36,85],"abnormal":[38],"structures":[39],"and":[40,143,159,161,187,214,234],"also":[41],"deficiencies":[44,59],"acquisition":[48],"which":[49,179,231],"affects":[50],"quality.":[52],"Light":[53],"flares":[54,142],"are":[55,154,162],"one":[56],"such":[58],"that":[60,104],"usually":[61],"don't":[62],"compromise":[63],"overall":[65],"quality,":[67],"but":[68],"can":[69],"be":[70],"misclassified":[71],"by":[72,156,164],"an":[73,201],"system.":[76],"In":[77],"this":[78],"article":[79],"a":[80,100,119,165,173],"method":[81,117,169,199],"proposed":[83,116],"light":[86,96,137,141,151,218],"artifacts":[87,125,138],"(flares)":[88],"images.":[91,132,237],"output":[93],"from":[94,111,178],"artifact":[97,131,152,213],"detection":[98,204],"binary":[101],"mask":[103],"useful":[106],"reject":[108],"those":[109],"pixels":[110],"being":[112],"further":[113],"processed.":[114],"uses":[118],"template":[120,130],"matching":[121],"algorithm":[122],"detect":[124],"similar":[126],"predefined":[129],"Two":[133],"main":[134],"types":[135],"were":[139,181,221],"identified:":[140],"central":[145,212],"artifact.":[146],"To":[147],"reduce":[148],"over-segmentation":[149],"candidates":[153],"characterized":[155],"shape":[158],"color":[160],"classified":[163],"decision":[166],"tree.":[167],"was":[170],"developed":[171],"using":[172],"dataset":[174,197,230],"61":[176],"images":[177],"20":[180],"used":[182],"classifier":[185],"training":[186],"remaining":[189],"41":[190],"independent":[192],"testing.":[193],"With":[194],"test":[196],"obtained":[200],"average":[202],"sensitivity/false":[203],"per":[205],"pairs":[207],"0.97/0.12":[209],"0.73/0.36":[215],"flares,":[219],"what":[220],"considered":[222],"good":[223],"results":[224],"regarding":[225],"heterogeneity":[227],"contain":[232],"low":[233],"high":[235],"quality":[236]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2013,"cited_by_count":1}],"updated_date":"2026-03-18T14:38:29.013473","created_date":"2025-10-10T00:00:00"}