{"id":"https://openalex.org/W2062080136","doi":"https://doi.org/10.1117/12.2006164","title":"A robust region-based active contour model with point classification for ultrasound breast lesion segmentation","display_name":"A robust region-based active contour model with point classification for ultrasound breast lesion segmentation","publication_year":2013,"publication_date":"2013-02-28","ids":{"openalex":"https://openalex.org/W2062080136","doi":"https://doi.org/10.1117/12.2006164","mag":"2062080136"},"language":"en","primary_location":{"id":"doi:10.1117/12.2006164","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2006164","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/A5100406781","display_name":"Zhihua Liu","orcid":"https://orcid.org/0000-0003-4994-6764"},"institutions":[{"id":"https://openalex.org/I4210155230","display_name":"Samsung (China)","ror":"https://ror.org/04yt00889","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250650973","https://openalex.org/I4210155230"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhihua Liu","raw_affiliation_strings":["Samsung Advanced Institute of Technology (China)"],"affiliations":[{"raw_affiliation_string":"Samsung Advanced Institute of Technology (China)","institution_ids":["https://openalex.org/I4210155230"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100600484","display_name":"Lidan Zhang","orcid":"https://orcid.org/0000-0002-1813-781X"},"institutions":[{"id":"https://openalex.org/I4210155230","display_name":"Samsung (China)","ror":"https://ror.org/04yt00889","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250650973","https://openalex.org/I4210155230"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lidan Zhang","raw_affiliation_strings":["Samsung Advanced Institute of Technology (China)"],"affiliations":[{"raw_affiliation_string":"Samsung Advanced Institute of Technology (China)","institution_ids":["https://openalex.org/I4210155230"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100764066","display_name":"Haibing Ren","orcid":"https://orcid.org/0009-0002-5751-7062"},"institutions":[{"id":"https://openalex.org/I4210155230","display_name":"Samsung (China)","ror":"https://ror.org/04yt00889","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250650973","https://openalex.org/I4210155230"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haibing Ren","raw_affiliation_strings":["Samsung Advanced Institute of Technology (China)"],"affiliations":[{"raw_affiliation_string":"Samsung Advanced Institute of Technology (China)","institution_ids":["https://openalex.org/I4210155230"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5111640805","display_name":"Ji-Yeun Kim","orcid":null},"institutions":[{"id":"https://openalex.org/I4210155230","display_name":"Samsung (China)","ror":"https://ror.org/04yt00889","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250650973","https://openalex.org/I4210155230"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ji-Yeun Kim","raw_affiliation_strings":["Samsung Advanced Institute of Technology (China)"],"affiliations":[{"raw_affiliation_string":"Samsung Advanced Institute of Technology (China)","institution_ids":["https://openalex.org/I4210155230"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100406781"],"corresponding_institution_ids":["https://openalex.org/I4210155230"],"apc_list":null,"apc_paid":null,"fwci":0.9618,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.82216183,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"8670","issue":null,"first_page":"86701P","last_page":"86701P"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.9988999962806702,"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":0.9988999962806702,"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":0.9968000054359436,"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/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.9876000285148621,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/initialization","display_name":"Initialization","score":0.754061758518219},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.7309424877166748},{"id":"https://openalex.org/keywords/active-contour-model","display_name":"Active contour model","score":0.7001339197158813},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6835302710533142},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6671034097671509},{"id":"https://openalex.org/keywords/level-set","display_name":"Level set (data structures)","score":0.5715755820274353},{"id":"https://openalex.org/keywords/contrast","display_name":"Contrast (vision)","score":0.553459107875824},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5476065278053284},{"id":"https://openalex.org/keywords/point-distribution-model","display_name":"Point distribution model","score":0.48150572180747986},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4561348557472229},{"id":"https://openalex.org/keywords/breast-ultrasound","display_name":"Breast ultrasound","score":0.4537998139858246},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.45138436555862427},{"id":"https://openalex.org/keywords/energy","display_name":"Energy (signal processing)","score":0.42593491077423096},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.42317748069763184},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.4221256375312805},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.20270276069641113},{"id":"https://openalex.org/keywords/mammography","display_name":"Mammography","score":0.16396179795265198},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.0723235011100769}],"concepts":[{"id":"https://openalex.org/C114466953","wikidata":"https://www.wikidata.org/wiki/Q6034165","display_name":"Initialization","level":2,"score":0.754061758518219},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7309424877166748},{"id":"https://openalex.org/C112353826","wikidata":"https://www.wikidata.org/wiki/Q127313","display_name":"Active contour model","level":4,"score":0.7001339197158813},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6835302710533142},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6671034097671509},{"id":"https://openalex.org/C153008295","wikidata":"https://www.wikidata.org/wiki/Q6535093","display_name":"Level set (data structures)","level":2,"score":0.5715755820274353},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.553459107875824},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5476065278053284},{"id":"https://openalex.org/C118317068","wikidata":"https://www.wikidata.org/wiki/Q2100760","display_name":"Point distribution model","level":2,"score":0.48150572180747986},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4561348557472229},{"id":"https://openalex.org/C2777423100","wikidata":"https://www.wikidata.org/wiki/Q1888238","display_name":"Breast ultrasound","level":5,"score":0.4537998139858246},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.45138436555862427},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.42593491077423096},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.42317748069763184},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.4221256375312805},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.20270276069641113},{"id":"https://openalex.org/C2780472235","wikidata":"https://www.wikidata.org/wiki/Q324634","display_name":"Mammography","level":4,"score":0.16396179795265198},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0723235011100769},{"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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"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/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","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/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1117/12.2006164","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2006164","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":[{"id":"https://metadata.un.org/sdg/7","score":0.8100000023841858,"display_name":"Affordable and clean energy"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2351917300","https://openalex.org/W2368150111","https://openalex.org/W2125739208","https://openalex.org/W2098360446","https://openalex.org/W2417159703","https://openalex.org/W2888165508","https://openalex.org/W2168406752","https://openalex.org/W3023152879","https://openalex.org/W2766054123","https://openalex.org/W2055260435"],"abstract_inverted_index":{"Lesion":[0],"segmentation":[1,136],"is":[2,44,77,99,115,125],"one":[3],"of":[4],"the":[5,48,75,97,101,119,123,129,135,153],"key":[6],"technologies":[7],"for":[8,68,105],"computer-aided":[9],"diagnosis":[10],"(CAD)":[11],"system.":[12],"In":[13],"this":[14],"paper,":[15],"we":[16,64],"propose":[17],"a":[18,37,66,89,147],"robust":[19],"region-based":[20],"active":[21],"contour":[22,49,132],"model":[23,86,104,114,124],"(ACM)":[24],"with":[25,83,142],"point":[26],"classification":[27],"to":[28,46,87,133],"segment":[29],"high-variant":[30],"breast":[31],"lesion":[32],"in":[33],"ultrasound":[34,150],"images.":[35],"First,":[36],"local":[38,54,59,84,102],"signed":[39],"pressure":[40],"force":[41],"(LSPF)":[42],"function":[43],"proposed":[45],"classify":[47],"points":[50],"into":[51],"two":[52,120],"classes:":[53],"low":[55,72],"contrast":[56,61,73,95],"class":[57],"and":[58,127,152],"high":[60,94],"class.":[62,70],"Secondly,":[63],"build":[65],"sub-model":[67,76,98],"each":[69],"For":[71,93],"class,":[74,96],"built":[78,116],"by":[79,117],"combining":[80],"global":[81,90],"energy":[82,85,103,113],"find":[88],"optimal":[91],"solution.":[92],"just":[100],"its":[106],"good":[107],"level":[108,130],"set":[109,131],"initialization.":[110],"Our":[111],"final":[112],"adding":[118],"sub-models.":[121],"Finally,":[122],"minimized":[126],"evolves":[128],"get":[134],"result.":[137],"We":[138],"compare":[139],"our":[140,157],"method":[141,158],"other":[143],"state-of-art":[144],"methods":[145],"on":[146],"very":[148],"large":[149],"database":[151],"result":[154],"shows":[155],"that":[156],"can":[159],"achieve":[160],"better":[161],"performance.":[162]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2016,"cited_by_count":1},{"year":2014,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
