{"id":"https://openalex.org/W1980293828","doi":"https://doi.org/10.1109/bmei.2012.6513144","title":"A combined method for automatic identification of the breast boundary in mammograms","display_name":"A combined method for automatic identification of the breast boundary in mammograms","publication_year":2012,"publication_date":"2012-10-01","ids":{"openalex":"https://openalex.org/W1980293828","doi":"https://doi.org/10.1109/bmei.2012.6513144","mag":"1980293828"},"language":"en","primary_location":{"id":"doi:10.1109/bmei.2012.6513144","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bmei.2012.6513144","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 5th International Conference on BioMedical Engineering and Informatics","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/A5018009756","display_name":"Zhili Chen","orcid":"https://orcid.org/0000-0002-2231-3652"},"institutions":[{"id":"https://openalex.org/I83714178","display_name":"Shenyang Jianzhu University","ror":"https://ror.org/01zr73v18","country_code":"CN","type":"education","lineage":["https://openalex.org/I83714178"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhili Chen","raw_affiliation_strings":["School of Information and Control Engineering, Shenyang Jianzhu University, Shenyang, China"],"affiliations":[{"raw_affiliation_string":"School of Information and Control Engineering, Shenyang Jianzhu University, Shenyang, China","institution_ids":["https://openalex.org/I83714178"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5075394907","display_name":"Reyer Zwiggelaar","orcid":"https://orcid.org/0000-0002-4360-0896"},"institutions":[{"id":"https://openalex.org/I16038530","display_name":"Aberystwyth University","ror":"https://ror.org/015m2p889","country_code":"GB","type":"education","lineage":["https://openalex.org/I16038530"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Reyer Zwiggelaar","raw_affiliation_strings":["Department of Computer Science, Aberystwyth University, Aberystwyth, United Kingdom","Department of Computer Science, Aberystwyth University, Aberystwyth, UK"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Aberystwyth University, Aberystwyth, United Kingdom","institution_ids":["https://openalex.org/I16038530"]},{"raw_affiliation_string":"Department of Computer Science, Aberystwyth University, Aberystwyth, UK","institution_ids":["https://openalex.org/I16038530"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5018009756"],"corresponding_institution_ids":["https://openalex.org/I83714178"],"apc_list":null,"apc_paid":null,"fwci":0.8563,"has_fulltext":false,"cited_by_count":30,"citation_normalized_percentile":{"value":0.77803055,"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":"121","last_page":"125"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9973999857902527,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9908000230789185,"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/segmentation","display_name":"Segmentation","score":0.7854906916618347},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7188706398010254},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6922581195831299},{"id":"https://openalex.org/keywords/thresholding","display_name":"Thresholding","score":0.594881534576416},{"id":"https://openalex.org/keywords/boundary","display_name":"Boundary (topology)","score":0.5641099810600281},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5317733883857727},{"id":"https://openalex.org/keywords/histogram","display_name":"Histogram","score":0.5184047222137451},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5070908069610596},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.48881933093070984},{"id":"https://openalex.org/keywords/mammography","display_name":"Mammography","score":0.4857097566127777},{"id":"https://openalex.org/keywords/region-growing","display_name":"Region growing","score":0.42785656452178955},{"id":"https://openalex.org/keywords/scale-space-segmentation","display_name":"Scale-space segmentation","score":0.3427277207374573},{"id":"https://openalex.org/keywords/breast-cancer","display_name":"Breast cancer","score":0.22541427612304688},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.19983786344528198},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.141606867313385},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.11904528737068176}],"concepts":[{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7854906916618347},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7188706398010254},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6922581195831299},{"id":"https://openalex.org/C191178318","wikidata":"https://www.wikidata.org/wiki/Q2256906","display_name":"Thresholding","level":3,"score":0.594881534576416},{"id":"https://openalex.org/C62354387","wikidata":"https://www.wikidata.org/wiki/Q875399","display_name":"Boundary (topology)","level":2,"score":0.5641099810600281},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5317733883857727},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.5184047222137451},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5070908069610596},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.48881933093070984},{"id":"https://openalex.org/C2780472235","wikidata":"https://www.wikidata.org/wiki/Q324634","display_name":"Mammography","level":4,"score":0.4857097566127777},{"id":"https://openalex.org/C206824153","wikidata":"https://www.wikidata.org/wiki/Q1169834","display_name":"Region growing","level":5,"score":0.42785656452178955},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.3427277207374573},{"id":"https://openalex.org/C530470458","wikidata":"https://www.wikidata.org/wiki/Q128581","display_name":"Breast cancer","level":3,"score":0.22541427612304688},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.19983786344528198},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.141606867313385},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.11904528737068176},{"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/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bmei.2012.6513144","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bmei.2012.6513144","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 5th International Conference on BioMedical Engineering and Informatics","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W1541960437","https://openalex.org/W1605502870","https://openalex.org/W1676195771","https://openalex.org/W1978379382","https://openalex.org/W1980642726","https://openalex.org/W1996223772","https://openalex.org/W2017977879","https://openalex.org/W2040434704","https://openalex.org/W2043979709","https://openalex.org/W2054162039","https://openalex.org/W2065789139","https://openalex.org/W2104254046","https://openalex.org/W2140490307","https://openalex.org/W2145023731","https://openalex.org/W2166739600","https://openalex.org/W2514575318","https://openalex.org/W6636058543","https://openalex.org/W6680960565","https://openalex.org/W6726088282","https://openalex.org/W7028171504"],"related_works":["https://openalex.org/W2122667464","https://openalex.org/W2054831422","https://openalex.org/W2106731176","https://openalex.org/W2387104004","https://openalex.org/W3047671631","https://openalex.org/W1548186045","https://openalex.org/W2902098370","https://openalex.org/W4283267580","https://openalex.org/W2394279717","https://openalex.org/W2786233476"],"abstract_inverted_index":{"Breast":[0],"region":[1,23,102],"segmentation":[2,39,90,200],"is":[3,113,174],"an":[4],"essential":[5],"prerequisite":[6],"in":[7,27,66,190,195,208],"the":[8,21,48,51,56,59,62,82,106,109,119,129,133,145,152,179,185,192],"(semi-)automatic":[9],"analysis":[10,207],"of":[11,32,61,81,89,108],"digital":[12],"or":[13],"digitised":[14,196],"mammographic":[15,117],"images,":[16],"which":[17,36],"aims":[18],"to":[19],"separate":[20],"breast":[22,52,83,193],"from":[24,128],"background":[25],"information":[26],"mammograms.":[28,197],"It":[29],"normally":[30],"consists":[31],"two":[33,116,166,171],"independent":[34],"segmentations,":[35],"are":[37,142,162],"breast-background":[38,134],"and":[40,53,55,101,123,137,147,157],"pectoral":[41,63,153],"muscle":[42,64,154],"segmentation,":[43,135,155],"respectively.":[44,150],"The":[45,198],"first":[46],"identifies":[47,58],"boundary":[49,60,84,194],"between":[50],"background,":[54],"second":[57],"(present":[65],"medio-lateral":[67],"oblique":[68],"(MLO)":[69],"views).":[70],"In":[71],"this":[72],"paper,":[73],"we":[74],"propose":[75],"a":[76,87,124],"method":[77,187],"for":[78,144,164,205],"automatic":[79],"identification":[80],"based":[85,177],"on":[86,178],"combination":[88],"approaches,":[91],"including":[92],"histogram":[93],"thresholding,":[94],"edge":[95],"detection,":[96],"contour":[97],"growing,":[98],"polynomial":[99],"fitting,":[100],"growing.":[103],"To":[104],"demonstrate":[105],"validity":[107],"proposed":[110,186],"method,":[111],"it":[112],"tested":[114],"using":[115],"datasets:":[118],"full":[120,180],"MIAS":[121,146,181],"database":[122],"large":[125],"dataset":[126],"taken":[127],"EPIC":[130,148],"database.":[131,182],"For":[132,151],"98.8%":[136],"91.5%":[138],"nearly":[139,159],"accurate":[140,160],"results":[141,161,201],"obtained":[143,199],"data,":[149],"92.8%":[156],"87.9%":[158],"achieved":[163],"these":[165],"datasets.":[167],"A":[168],"comparison":[169],"with":[170],"other":[172],"methods":[173],"also":[175],"provided":[176],"These":[183],"indicate":[184],"performs":[188],"effectively":[189],"identifying":[191],"can":[202],"be":[203],"used":[204],"further":[206],"computer-aided":[209],"diagnosis.":[210]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":6},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":6},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":1},{"year":2015,"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"}
