{"id":"https://openalex.org/W2061083508","doi":"https://doi.org/10.1117/12.876351","title":"Automatic lesion detection and segmentation algorithm on 2D breast ultrasound images","display_name":"Automatic lesion detection and segmentation algorithm on 2D breast ultrasound images","publication_year":2011,"publication_date":"2011-03-02","ids":{"openalex":"https://openalex.org/W2061083508","doi":"https://doi.org/10.1117/12.876351","mag":"2061083508"},"language":"en","primary_location":{"id":"doi:10.1117/12.876351","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.876351","pdf_url":null,"source":{"id":"https://openalex.org/S183492911","display_name":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","issn_l":"0277-786X","issn":["0277-786X","1996-756X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315543","host_organization_name":"SPIE","host_organization_lineage":["https://openalex.org/P4310315543"],"host_organization_lineage_names":["SPIE"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SPIE Proceedings","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/A5072386907","display_name":"Donghoon Yu","orcid":"https://orcid.org/0000-0001-7438-7349"},"institutions":[{"id":"https://openalex.org/I142401562","display_name":"Electronics and Telecommunications Research Institute","ror":"https://ror.org/03ysstz10","country_code":"KR","type":"facility","lineage":["https://openalex.org/I142401562","https://openalex.org/I2801339556","https://openalex.org/I4210144908","https://openalex.org/I4387152098"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Donghoon Yu","raw_affiliation_strings":["Electronics and Telecommunications Research Institute (Korea, Republic of)"],"affiliations":[{"raw_affiliation_string":"Electronics and Telecommunications Research Institute (Korea, Republic of)","institution_ids":["https://openalex.org/I142401562"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065856798","display_name":"Sooyeul Lee","orcid":"https://orcid.org/0000-0002-7902-0690"},"institutions":[{"id":"https://openalex.org/I142401562","display_name":"Electronics and Telecommunications Research Institute","ror":"https://ror.org/03ysstz10","country_code":"KR","type":"facility","lineage":["https://openalex.org/I142401562","https://openalex.org/I2801339556","https://openalex.org/I4210144908","https://openalex.org/I4387152098"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Sooyeul Lee","raw_affiliation_strings":["Electronics and Telecommunications Research Institute (Korea, Republic of)"],"affiliations":[{"raw_affiliation_string":"Electronics and Telecommunications Research Institute (Korea, Republic of)","institution_ids":["https://openalex.org/I142401562"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043069940","display_name":"Jeong Won Lee","orcid":"https://orcid.org/0000-0002-2697-3578"},"institutions":[{"id":"https://openalex.org/I142401562","display_name":"Electronics and Telecommunications Research Institute","ror":"https://ror.org/03ysstz10","country_code":"KR","type":"facility","lineage":["https://openalex.org/I142401562","https://openalex.org/I2801339556","https://openalex.org/I4210144908","https://openalex.org/I4387152098"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jeong Won Lee","raw_affiliation_strings":["Electronics and Telecommunications Research Institute (Korea, Republic of)"],"affiliations":[{"raw_affiliation_string":"Electronics and Telecommunications Research Institute (Korea, Republic of)","institution_ids":["https://openalex.org/I142401562"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100451559","display_name":"Seung-Hwan Kim","orcid":"https://orcid.org/0000-0002-4118-8703"},"institutions":[{"id":"https://openalex.org/I142401562","display_name":"Electronics and Telecommunications Research Institute","ror":"https://ror.org/03ysstz10","country_code":"KR","type":"facility","lineage":["https://openalex.org/I142401562","https://openalex.org/I2801339556","https://openalex.org/I4210144908","https://openalex.org/I4387152098"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Seunghwan Kim","raw_affiliation_strings":["Electronics and Telecommunications Research Institute (Korea, Republic of)"],"affiliations":[{"raw_affiliation_string":"Electronics and Telecommunications Research Institute (Korea, Republic of)","institution_ids":["https://openalex.org/I142401562"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5072386907"],"corresponding_institution_ids":["https://openalex.org/I142401562"],"apc_list":null,"apc_paid":null,"fwci":0.4276,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.72249501,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"7963","issue":null,"first_page":"79631Y","last_page":"79631Y"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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":0.9962999820709229,"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/T12549","display_name":"Image and Object Detection Techniques","score":0.9948999881744385,"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/computer-science","display_name":"Computer science","score":0.7633757591247559},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7024834156036377},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6139209866523743},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5772132873535156},{"id":"https://openalex.org/keywords/upsampling","display_name":"Upsampling","score":0.5416685938835144},{"id":"https://openalex.org/keywords/hough-transform","display_name":"Hough transform","score":0.5028335452079773},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.49006831645965576},{"id":"https://openalex.org/keywords/mammography","display_name":"Mammography","score":0.4618567228317261},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.41735172271728516},{"id":"https://openalex.org/keywords/lesion","display_name":"Lesion","score":0.4160258173942566},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.37853336334228516},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.15296858549118042},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.14026886224746704}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7633757591247559},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7024834156036377},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6139209866523743},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5772132873535156},{"id":"https://openalex.org/C110384440","wikidata":"https://www.wikidata.org/wiki/Q1143270","display_name":"Upsampling","level":3,"score":0.5416685938835144},{"id":"https://openalex.org/C200518788","wikidata":"https://www.wikidata.org/wiki/Q195076","display_name":"Hough transform","level":3,"score":0.5028335452079773},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.49006831645965576},{"id":"https://openalex.org/C2780472235","wikidata":"https://www.wikidata.org/wiki/Q324634","display_name":"Mammography","level":4,"score":0.4618567228317261},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.41735172271728516},{"id":"https://openalex.org/C2781156865","wikidata":"https://www.wikidata.org/wiki/Q827023","display_name":"Lesion","level":2,"score":0.4160258173942566},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37853336334228516},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.15296858549118042},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.14026886224746704},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C121608353","wikidata":"https://www.wikidata.org/wiki/Q12078","display_name":"Cancer","level":2,"score":0.0},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.0},{"id":"https://openalex.org/C530470458","wikidata":"https://www.wikidata.org/wiki/Q128581","display_name":"Breast cancer","level":3,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C118552586","wikidata":"https://www.wikidata.org/wiki/Q7867","display_name":"Psychiatry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1117/12.876351","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.876351","pdf_url":null,"source":{"id":"https://openalex.org/S183492911","display_name":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","issn_l":"0277-786X","issn":["0277-786X","1996-756X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315543","host_organization_name":"SPIE","host_organization_lineage":["https://openalex.org/P4310315543"],"host_organization_lineage_names":["SPIE"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SPIE Proceedings","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":6,"referenced_works":["https://openalex.org/W22745672","https://openalex.org/W2052099918","https://openalex.org/W2087998819","https://openalex.org/W2095905764","https://openalex.org/W2113282793","https://openalex.org/W2169388041"],"related_works":["https://openalex.org/W2062399876","https://openalex.org/W2030098947","https://openalex.org/W1974777989","https://openalex.org/W2363834444","https://openalex.org/W2003466055","https://openalex.org/W2070077862","https://openalex.org/W2765199790","https://openalex.org/W2607795551","https://openalex.org/W2164944168","https://openalex.org/W1522196789"],"abstract_inverted_index":{"Although":[0],"X-ray":[1],"mammography":[2],"(MG)":[3],"is":[4,61,71,95,99],"the":[5,21,42,64,76,84,103,113,122,125],"dominant":[6],"imaging":[7],"modality,":[8],"ultrasonography":[9],"(US),":[10],"with":[11,67],"recent":[12],"advances":[13],"in":[14,20,136],"technologies,":[15],"has":[16],"proven":[17],"very":[18,72],"useful":[19],"evaluation":[22],"of":[23,32,45,105,115,127,139,153],"breast":[24,52],"abnormalities.":[25],"But":[26],"radiologist":[27],"should":[28],"investigate":[29],"a":[30,130],"lot":[31],"images":[33,54],"for":[34],"proper":[35],"diagnosis":[36],"unlike":[37],"MG.":[38],"This":[39],"paper":[40],"proposes":[41],"automatic":[43],"algorithm":[44,133],"detecting":[46,59],"and":[47,80,149],"segmenting":[48,87],"lesions":[49,148,154],"on":[50,63],"2D":[51],"ultrasound":[53],"to":[55,74,82,101,121,146,150],"help":[56,145],"radiologist.":[57],"The":[58,141],"part":[60],"based":[62],"Hough":[65],"transform":[66],"downsampling":[68],"process":[69],"which":[70],"efficient":[73],"sharpen":[75],"smooth":[77],"lesion":[78,116],"boundary":[79,152],"also":[81],"reduce":[83],"noise.":[85],"In":[86],"part,":[88],"radial":[89],"dependent":[90],"contrast":[91,111,119],"adjustment":[92],"(RDCA)":[93],"method":[94],"newly":[96],"proposed.":[97],"RDCA":[98],"introduced":[100],"overcome":[102],"limitation":[104],"Gaussian":[106],"constraint":[107],"function.":[108],"It":[109],"decreases":[110],"around":[112],"center":[114,126],"but":[117],"increases":[118],"proportional":[120],"distance":[123],"from":[124],"lesion.":[128,140],"As":[129],"result,":[131],"segmentation":[132],"shows":[134],"robustness":[135],"various":[137],"shapes":[138],"proposed":[142],"algorithms":[143],"may":[144],"detect":[147],"find":[151],"efficiently.":[155]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":1},{"year":2013,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
