{"id":"https://openalex.org/W2079967231","doi":"https://doi.org/10.1109/iww-bci.2013.6506632","title":"Efficient edge detection method for anatomic feature extraction of neuro-sensory tissue image based on optical coherence tomography","display_name":"Efficient edge detection method for anatomic feature extraction of neuro-sensory tissue image based on optical coherence tomography","publication_year":2013,"publication_date":"2013-02-01","ids":{"openalex":"https://openalex.org/W2079967231","doi":"https://doi.org/10.1109/iww-bci.2013.6506632","mag":"2079967231"},"language":"en","primary_location":{"id":"doi:10.1109/iww-bci.2013.6506632","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iww-bci.2013.6506632","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 International Winter Workshop on Brain-Computer Interface (BCI)","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/A5055965722","display_name":"Yeong-Mun Cha","orcid":null},"institutions":[{"id":"https://openalex.org/I197347611","display_name":"Korea University","ror":"https://ror.org/047dqcg40","country_code":"KR","type":"education","lineage":["https://openalex.org/I197347611"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Yeong-Mun Cha","raw_affiliation_strings":["Department of Brain and Cognitive Engineering, Korea University, Seoul, South Korea","Dept. of brain and cognitive engineering, Korea University Seoul, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Brain and Cognitive Engineering, Korea University, Seoul, South Korea","institution_ids":["https://openalex.org/I197347611"]},{"raw_affiliation_string":"Dept. of brain and cognitive engineering, Korea University Seoul, South Korea","institution_ids":["https://openalex.org/I197347611"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016279912","display_name":"Jae\u2010Ho Han","orcid":"https://orcid.org/0000-0002-6490-9825"},"institutions":[{"id":"https://openalex.org/I197347611","display_name":"Korea University","ror":"https://ror.org/047dqcg40","country_code":"KR","type":"education","lineage":["https://openalex.org/I197347611"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jae-Ho Han","raw_affiliation_strings":["Department of Brain and Cognitive Engineering, Korea University, Seoul, South Korea","Dept. of brain and cognitive engineering, Korea University Seoul, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Brain and Cognitive Engineering, Korea University, Seoul, South Korea","institution_ids":["https://openalex.org/I197347611"]},{"raw_affiliation_string":"Dept. of brain and cognitive engineering, Korea University Seoul, South Korea","institution_ids":["https://openalex.org/I197347611"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I197347611"],"apc_list":null,"apc_paid":null,"fwci":1.8629,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.85140489,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"22","issue":null,"first_page":"65","last_page":"66"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11569","display_name":"Optical Coherence Tomography Applications","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11569","display_name":"Optical Coherence Tomography Applications","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11438","display_name":"Retinal Imaging and Analysis","score":0.9911999702453613,"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":0.9739000201225281,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.8126183748245239},{"id":"https://openalex.org/keywords/optical-coherence-tomography","display_name":"Optical coherence tomography","score":0.7397267818450928},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7251043319702148},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.6825342178344727},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.6620905995368958},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6596184372901917},{"id":"https://openalex.org/keywords/edge-detection","display_name":"Edge detection","score":0.6295406222343445},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6120665073394775},{"id":"https://openalex.org/keywords/coherence","display_name":"Coherence (philosophical gambling strategy)","score":0.5293021202087402},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5139767527580261},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5124664902687073},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4749348759651184},{"id":"https://openalex.org/keywords/sliding-window-protocol","display_name":"Sliding window protocol","score":0.4503466486930847},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.4319489598274231},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.4110686182975769},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.35312163829803467},{"id":"https://openalex.org/keywords/window","display_name":"Window (computing)","score":0.2938250005245209},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.2746383547782898},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.17651808261871338},{"id":"https://openalex.org/keywords/optics","display_name":"Optics","score":0.10975643992424011},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.0767812430858612}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8126183748245239},{"id":"https://openalex.org/C2778818243","wikidata":"https://www.wikidata.org/wiki/Q899552","display_name":"Optical coherence tomography","level":2,"score":0.7397267818450928},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7251043319702148},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.6825342178344727},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.6620905995368958},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6596184372901917},{"id":"https://openalex.org/C193536780","wikidata":"https://www.wikidata.org/wiki/Q1513153","display_name":"Edge detection","level":4,"score":0.6295406222343445},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6120665073394775},{"id":"https://openalex.org/C2781181686","wikidata":"https://www.wikidata.org/wiki/Q4226068","display_name":"Coherence (philosophical gambling strategy)","level":2,"score":0.5293021202087402},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5139767527580261},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5124664902687073},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4749348759651184},{"id":"https://openalex.org/C102392041","wikidata":"https://www.wikidata.org/wiki/Q592860","display_name":"Sliding window protocol","level":3,"score":0.4503466486930847},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.4319489598274231},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.4110686182975769},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.35312163829803467},{"id":"https://openalex.org/C2778751112","wikidata":"https://www.wikidata.org/wiki/Q835016","display_name":"Window (computing)","level":2,"score":0.2938250005245209},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.2746383547782898},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.17651808261871338},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.10975643992424011},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0767812430858612},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iww-bci.2013.6506632","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iww-bci.2013.6506632","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 International Winter Workshop on Brain-Computer Interface (BCI)","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":12,"referenced_works":["https://openalex.org/W1972544340","https://openalex.org/W2003111639","https://openalex.org/W2009206745","https://openalex.org/W2030917850","https://openalex.org/W2059471177","https://openalex.org/W2063440562","https://openalex.org/W2071795438","https://openalex.org/W2082503527","https://openalex.org/W2085232786","https://openalex.org/W2096412116","https://openalex.org/W2153394113","https://openalex.org/W2488678869"],"related_works":["https://openalex.org/W2323668004","https://openalex.org/W2348498086","https://openalex.org/W3093461874","https://openalex.org/W2063232638","https://openalex.org/W2353818951","https://openalex.org/W1000914229","https://openalex.org/W3021342607","https://openalex.org/W2488331324","https://openalex.org/W4400976415","https://openalex.org/W2770255720"],"abstract_inverted_index":{"In":[0],"this":[1,87],"work,":[2],"we":[3],"propose":[4],"a":[5,25],"reliable":[6],"and":[7],"detailed":[8,47],"edge":[9,53],"detection":[10,54],"method":[11,90],"customized":[12],"on":[13,38,61,81],"characteristics":[14],"of":[15,74],"optical":[16],"coherence":[17],"tomography":[18],"images":[19],"for":[20,31],"stable":[21],"feature":[22,88],"extraction.":[23],"Using":[24],"local":[26],"window":[27],"holding":[28],"many":[29],"pixels":[30],"tracking":[32],"structural":[33],"tendencies,":[34],"edges":[35,69,80],"are":[36],"detected":[37,68],"reliably":[39],"limited":[40],"areas":[41],"in":[42,96],"reduced":[43],"noise":[44],"effect.":[45],"For":[46],"pixel":[48],"separation":[49],"between":[50],"structures,":[51],"the":[52,67],"is":[55],"also":[56],"achieved":[57],"through":[58],"clustering":[59],"based":[60],"Gaussian":[62],"mixture":[63],"model.":[64],"As":[65],"results,":[66],"showed":[70],"less":[71],"than":[72],"3-\u03bcm":[73],"average":[75],"distant":[76],"differences":[77],"compared":[78],"to":[79],"manually":[82],"recognized":[83],"images.":[84],"We":[85],"believe":[86],"extraction":[89],"will":[91],"provide":[92],"improved":[93],"quantitative":[94],"analyses":[95],"wide":[97],"OCT":[98],"research":[99],"areas.":[100]},"counts_by_year":[{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":2}],"updated_date":"2026-08-21T09:56:20.448147","created_date":"2025-10-10T00:00:00"}
