{"id":"https://openalex.org/W2920886319","doi":"https://doi.org/10.1117/12.2512355","title":"Computer-aided detection and classification of microcalcification clusters on full field digital mammograms using deep convolution neural network","display_name":"Computer-aided detection and classification of microcalcification clusters on full field digital mammograms using deep convolution neural network","publication_year":2019,"publication_date":"2019-03-13","ids":{"openalex":"https://openalex.org/W2920886319","doi":"https://doi.org/10.1117/12.2512355","mag":"2920886319"},"language":"en","primary_location":{"id":"doi:10.1117/12.2512355","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2512355","pdf_url":null,"source":{"id":"https://openalex.org/S4306519510","display_name":"Medical Imaging 2019: Computer-Aided Diagnosis","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Medical Imaging 2019: Computer-Aided Diagnosis","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/A5086968980","display_name":"Guanxiong Cai","orcid":null},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Guanxiong Cai","raw_affiliation_strings":["Sun Yat-Sen Univ. (China)"],"affiliations":[{"raw_affiliation_string":"Sun Yat-Sen Univ. (China)","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026927275","display_name":"Yanhui Guo","orcid":"https://orcid.org/0000-0003-1814-9682"},"institutions":[{"id":"https://openalex.org/I79884896","display_name":"University of Illinois at Springfield","ror":"https://ror.org/0126qma51","country_code":"US","type":"education","lineage":["https://openalex.org/I79884896"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yanhui Guo","raw_affiliation_strings":["Univ. of Illinois at Springfield (United States)"],"affiliations":[{"raw_affiliation_string":"Univ. of Illinois at Springfield (United States)","institution_ids":["https://openalex.org/I79884896"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100739071","display_name":"Weiguo Chen","orcid":"https://orcid.org/0000-0003-1552-0511"},"institutions":[{"id":"https://openalex.org/I58200834","display_name":"Southern Medical University","ror":"https://ror.org/01vjw4z39","country_code":"CN","type":"education","lineage":["https://openalex.org/I58200834"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weiguo Chen","raw_affiliation_strings":["Southern Medical Univ. (China)"],"affiliations":[{"raw_affiliation_string":"Southern Medical Univ. (China)","institution_ids":["https://openalex.org/I58200834"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101411795","display_name":"Hui Zeng","orcid":"https://orcid.org/0000-0002-3715-8317"},"institutions":[{"id":"https://openalex.org/I58200834","display_name":"Southern Medical University","ror":"https://ror.org/01vjw4z39","country_code":"CN","type":"education","lineage":["https://openalex.org/I58200834"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hui Zeng","raw_affiliation_strings":["Southern Medical Univ. (China)"],"affiliations":[{"raw_affiliation_string":"Southern Medical Univ. (China)","institution_ids":["https://openalex.org/I58200834"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082138060","display_name":"Yuanpin Zhou","orcid":"https://orcid.org/0000-0002-6297-9600"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuanpin Zhou","raw_affiliation_strings":["Sun Yat-Sen Univ. (China)"],"affiliations":[{"raw_affiliation_string":"Sun Yat-Sen Univ. (China)","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102027564","display_name":"Yao Lu","orcid":"https://orcid.org/0000-0001-9004-9569"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yao Lu","raw_affiliation_strings":["Sun Yat-Sen Univ. (China)"],"affiliations":[{"raw_affiliation_string":"Sun Yat-Sen Univ. (China)","institution_ids":["https://openalex.org/I157773358"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5086968980"],"corresponding_institution_ids":["https://openalex.org/I157773358"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.01812754,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"91","last_page":"91"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.9998999834060669,"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":0.9998999834060669,"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/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.9937000274658203,"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/T10885","display_name":"Gene expression and cancer classification","score":0.9817000031471252,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7487732172012329},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7438476085662842},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.6878261566162109},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6782116889953613},{"id":"https://openalex.org/keywords/microcalcification","display_name":"Microcalcification","score":0.5982853770256042},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.594364583492279},{"id":"https://openalex.org/keywords/receiver-operating-characteristic","display_name":"Receiver operating characteristic","score":0.5862027406692505},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5446299314498901},{"id":"https://openalex.org/keywords/mammography","display_name":"Mammography","score":0.5325374007225037},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5308566689491272},{"id":"https://openalex.org/keywords/digital-mammography","display_name":"Digital mammography","score":0.5237196087837219},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5220163464546204},{"id":"https://openalex.org/keywords/computer-aided-diagnosis","display_name":"Computer-aided diagnosis","score":0.4919102191925049},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4433024525642395},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4386947751045227},{"id":"https://openalex.org/keywords/breast-cancer","display_name":"Breast cancer","score":0.3966582417488098},{"id":"https://openalex.org/keywords/cancer","display_name":"Cancer","score":0.23946794867515564},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.14398455619812012},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.09466153383255005}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7487732172012329},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7438476085662842},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.6878261566162109},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6782116889953613},{"id":"https://openalex.org/C2781129008","wikidata":"https://www.wikidata.org/wiki/Q1933877","display_name":"Microcalcification","level":5,"score":0.5982853770256042},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.594364583492279},{"id":"https://openalex.org/C58471807","wikidata":"https://www.wikidata.org/wiki/Q327120","display_name":"Receiver operating characteristic","level":2,"score":0.5862027406692505},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5446299314498901},{"id":"https://openalex.org/C2780472235","wikidata":"https://www.wikidata.org/wiki/Q324634","display_name":"Mammography","level":4,"score":0.5325374007225037},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5308566689491272},{"id":"https://openalex.org/C2781281974","wikidata":"https://www.wikidata.org/wiki/Q324634","display_name":"Digital mammography","level":5,"score":0.5237196087837219},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5220163464546204},{"id":"https://openalex.org/C2779549770","wikidata":"https://www.wikidata.org/wiki/Q1122413","display_name":"Computer-aided diagnosis","level":2,"score":0.4919102191925049},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4433024525642395},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4386947751045227},{"id":"https://openalex.org/C530470458","wikidata":"https://www.wikidata.org/wiki/Q128581","display_name":"Breast cancer","level":3,"score":0.3966582417488098},{"id":"https://openalex.org/C121608353","wikidata":"https://www.wikidata.org/wiki/Q12078","display_name":"Cancer","level":2,"score":0.23946794867515564},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.14398455619812012},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.09466153383255005},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1117/12.2512355","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2512355","pdf_url":null,"source":{"id":"https://openalex.org/S4306519510","display_name":"Medical Imaging 2019: Computer-Aided Diagnosis","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Medical Imaging 2019: Computer-Aided Diagnosis","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4699999988079071,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W304373761","https://openalex.org/W1544532836","https://openalex.org/W1990529284","https://openalex.org/W2006625844","https://openalex.org/W2027594868","https://openalex.org/W2064123169","https://openalex.org/W2069141332","https://openalex.org/W2084161499","https://openalex.org/W2112525988","https://openalex.org/W2216361451","https://openalex.org/W2261689926","https://openalex.org/W2743328801","https://openalex.org/W2889646458","https://openalex.org/W3106050203","https://openalex.org/W4241283611","https://openalex.org/W6632481545","https://openalex.org/W6637131181","https://openalex.org/W6651930677","https://openalex.org/W6754669450"],"related_works":["https://openalex.org/W2378946663","https://openalex.org/W2031284012","https://openalex.org/W2354834859","https://openalex.org/W2340621660","https://openalex.org/W2557931800","https://openalex.org/W2116047071","https://openalex.org/W54977395","https://openalex.org/W1540588256","https://openalex.org/W4378191048","https://openalex.org/W3190666406"],"abstract_inverted_index":{"Breast":[0],"cancer":[1,9,53],"is":[2,24,42,60,94,119,137,204],"presently":[3],"one":[4],"of":[5,21,29,81,125,133,212],"the":[6,134,152,155,182,201,207],"most":[7],"common":[8],"among":[10],"women":[11],"and":[12,16,38,50,83,142,147,163,168,178,210],"has":[13],"high":[14],"morbidity":[15],"mortality":[17],"worldwide.":[18],"The":[19,130,196],"emergence":[20],"microcalcifications":[22],"(MCs)":[23],"an":[25],"important":[26],"early":[27],"sign":[28],"breast":[30],"cancer.":[31],"In":[32],"this":[33],"study,":[34],"a":[35,88,116,122],"computer-aided":[36],"detection":[37,67,114,209],"diagnosis":[39,150],"(CAD)":[40],"system":[41,136],"developed":[43],"to":[44,108,176],"automatically":[45,208],"detect":[46],"MC":[47,59,66,72,74],"clusters":[48],"(MCCs)":[49],"further":[51],"providing":[52],"likelihood":[54],"prediction.":[55],"Firstly,":[56],"each":[57],"individual":[58],"detected":[61],"using":[62,191],"our":[63],"previously":[64],"designed":[65],"system,":[68],"which":[69],"includes":[70],"preprocessing,":[71],"enhancement,":[73],"candidate":[75],"detection,":[76],"false":[77],"positive":[78],"(FP)":[79],"reduction":[80],"MCs":[82],"regional":[84],"clustering":[85],"procedures.":[86],"Secondly,":[87],"deep":[89,192],"convolution":[90,193],"neural":[91,194],"network":[92],"(DCNN)":[93],"trained":[95],"on":[96,139,144,161],"394":[97],"clinical":[98],"high-resolution":[99],"full":[100],"field":[101],"digital":[102],"mammograms":[103],"(FFDMs)":[104],"containing":[105],"biopsy-proven":[106],"MCCs":[107],"discriminate":[109],"MCC":[110],"lesions.":[111],"For":[112],"cluster-based":[113],"evaluation,":[115,151],"90%":[117],"sensitivity":[118],"obtained":[120,197],"with":[121],"FP":[123],"rate":[124],"0.2":[126],"FPs":[127],"per":[128],"image.":[129],"classification":[131,211],"performance":[132],"whole":[135],"validated":[138],"70":[140],"cases":[141],"tested":[143],"71":[145],"cases,":[146],"for":[148],"case-based":[149],"area":[153],"under":[154],"receiver":[156],"operating":[157],"characteristic":[158],"curve":[159],"(AUC)":[160],"validation":[162],"testing":[164],"sets":[165],"are":[166],"0.945":[167],"0.932,":[169],"respectively.":[170],"Different":[171],"from":[172],"previous":[173],"literatures":[174],"committing":[175],"finding":[177],"selecting":[179],"effective":[180,205],"features,":[181],"proposed":[183,202],"method":[184,203],"replaces":[185],"manual":[186],"feature":[187],"extraction":[188],"step":[189],"by":[190],"network.":[195],"results":[198],"demonstrate":[199],"that":[200],"in":[206],"MCCs.":[213]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-01-13T01:12:25.745995","created_date":"2025-10-10T00:00:00"}
