{"id":"https://openalex.org/W3195485661","doi":"https://doi.org/10.1109/access.2021.3104627","title":"Multi-Scale Convolutional Neural Networks for Classification of Digital Mammograms With Breast Calcifications","display_name":"Multi-Scale Convolutional Neural Networks for Classification of Digital Mammograms With Breast Calcifications","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3195485661","doi":"https://doi.org/10.1109/access.2021.3104627","mag":"3195485661"},"language":"en","primary_location":{"id":"doi:10.1109/access.2021.3104627","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3104627","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09513257.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09513257.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5068897260","display_name":"Chatsuda Songsaeng","orcid":null},"institutions":[{"id":"https://openalex.org/I131868736","display_name":"Prince of Songkla University","ror":"https://ror.org/0575ycz84","country_code":"TH","type":"education","lineage":["https://openalex.org/I131868736"]}],"countries":["TH"],"is_corresponding":false,"raw_author_name":"Chatsuda Songsaeng","raw_affiliation_strings":["Department of Radiology, Faculty of Medicine, Prince of Songkla University, Songkhla, Thailand"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Radiology, Faculty of Medicine, Prince of Songkla University, Songkhla, Thailand","institution_ids":["https://openalex.org/I131868736"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002671493","display_name":"Piyanoot Woodtichartpreecha","orcid":null},"institutions":[{"id":"https://openalex.org/I131868736","display_name":"Prince of Songkla University","ror":"https://ror.org/0575ycz84","country_code":"TH","type":"education","lineage":["https://openalex.org/I131868736"]}],"countries":["TH"],"is_corresponding":false,"raw_author_name":"Piyanoot Woodtichartpreecha","raw_affiliation_strings":["Department of Radiology, Faculty of Medicine, Prince of Songkla University, Songkhla, Thailand"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Radiology, Faculty of Medicine, Prince of Songkla University, Songkhla, Thailand","institution_ids":["https://openalex.org/I131868736"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5069430065","display_name":"Sitthichok Chaichulee","orcid":"https://orcid.org/0000-0002-3159-7925"},"institutions":[{"id":"https://openalex.org/I131868736","display_name":"Prince of Songkla University","ror":"https://ror.org/0575ycz84","country_code":"TH","type":"education","lineage":["https://openalex.org/I131868736"]}],"countries":["TH"],"is_corresponding":false,"raw_author_name":"Sitthichok Chaichulee","raw_affiliation_strings":["Department of Biomedical Sciences and Biomedical Engineering, Faculty of Medicine, Prince of Songkla University, Songkhla, Thailand","Medical Data Center for Research and Innovation, Faculty of Medicine, Prince of Songkla University, Songkhla, Thailand","Research Center for Applied Medical Data Analytics, Faculty of Medicine, Prince of Songkla University, Songkhla, Thailand"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Biomedical Sciences and Biomedical Engineering, Faculty of Medicine, Prince of Songkla University, Songkhla, Thailand","institution_ids":["https://openalex.org/I131868736"]},{"raw_affiliation_string":"Medical Data Center for Research and Innovation, Faculty of Medicine, Prince of Songkla University, Songkhla, Thailand","institution_ids":["https://openalex.org/I131868736"]},{"raw_affiliation_string":"Research Center for Applied Medical Data Analytics, Faculty of Medicine, Prince of Songkla University, Songkhla, Thailand","institution_ids":["https://openalex.org/I131868736"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I131868736"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":2.4567,"has_fulltext":true,"cited_by_count":30,"citation_normalized_percentile":{"value":0.90755628,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":"9","issue":null,"first_page":"114741","last_page":"114753"},"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":0.9851999878883362,"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/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9836000204086304,"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/mammography","display_name":"Mammography","score":0.7466237545013428},{"id":"https://openalex.org/keywords/breast-cancer","display_name":"Breast cancer","score":0.7186059355735779},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6761084198951721},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6372345089912415},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6046243906021118},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6036776900291443},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5273845195770264},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.5028192400932312},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.46001526713371277},{"id":"https://openalex.org/keywords/digital-mammography","display_name":"Digital mammography","score":0.4558921158313751},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4509262442588806},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.42568355798721313},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.34369510412216187},{"id":"https://openalex.org/keywords/cancer","display_name":"Cancer","score":0.28669142723083496},{"id":"https://openalex.org/keywords/cartography","display_name":"Cartography","score":0.09431162476539612},{"id":"https://openalex.org/keywords/internal-medicine","display_name":"Internal medicine","score":0.08403456211090088}],"concepts":[{"id":"https://openalex.org/C2780472235","wikidata":"https://www.wikidata.org/wiki/Q324634","display_name":"Mammography","level":4,"score":0.7466237545013428},{"id":"https://openalex.org/C530470458","wikidata":"https://www.wikidata.org/wiki/Q128581","display_name":"Breast cancer","level":3,"score":0.7186059355735779},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6761084198951721},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6372345089912415},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6046243906021118},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6036776900291443},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5273845195770264},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.5028192400932312},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.46001526713371277},{"id":"https://openalex.org/C2781281974","wikidata":"https://www.wikidata.org/wiki/Q324634","display_name":"Digital mammography","level":5,"score":0.4558921158313751},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4509262442588806},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.42568355798721313},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.34369510412216187},{"id":"https://openalex.org/C121608353","wikidata":"https://www.wikidata.org/wiki/Q12078","display_name":"Cancer","level":2,"score":0.28669142723083496},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.09431162476539612},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.08403456211090088},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"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/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2021.3104627","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3104627","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09513257.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:3a1338931aaf4f8abe2df032305f8196","is_oa":true,"landing_page_url":"https://doaj.org/article/3a1338931aaf4f8abe2df032305f8196","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 9, Pp 114741-114753 (2021)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2021.3104627","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3104627","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09513257.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3","score":0.7400000095367432}],"awards":[],"funders":[{"id":"https://openalex.org/F4320322692","display_name":"Prince of Songkla University","ror":"https://ror.org/0575ycz84"},{"id":"https://openalex.org/F4320326657","display_name":"Faculty of Medicine, Prince of Songkla University","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3195485661.pdf","grobid_xml":"https://content.openalex.org/works/W3195485661.grobid-xml"},"referenced_works_count":30,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W1995387292","https://openalex.org/W2010938273","https://openalex.org/W2053480757","https://openalex.org/W2084147164","https://openalex.org/W2133911584","https://openalex.org/W2145283065","https://openalex.org/W2194775991","https://openalex.org/W2409650203","https://openalex.org/W2411894266","https://openalex.org/W2549139847","https://openalex.org/W2588570836","https://openalex.org/W2616247523","https://openalex.org/W2783597708","https://openalex.org/W2918834327","https://openalex.org/W2928165649","https://openalex.org/W2945697643","https://openalex.org/W2962835968","https://openalex.org/W2963323244","https://openalex.org/W2963420686","https://openalex.org/W2964081807","https://openalex.org/W3049536867","https://openalex.org/W3096695019","https://openalex.org/W3099705112","https://openalex.org/W3102564565","https://openalex.org/W3128646645","https://openalex.org/W6637373629","https://openalex.org/W6714838507","https://openalex.org/W6762625080","https://openalex.org/W6785710124"],"related_works":["https://openalex.org/W2557931800","https://openalex.org/W2116047071","https://openalex.org/W54977395","https://openalex.org/W1993531705","https://openalex.org/W3197491245","https://openalex.org/W1966034269","https://openalex.org/W2000845075","https://openalex.org/W1766776469","https://openalex.org/W2029515485","https://openalex.org/W1990413141"],"abstract_inverted_index":{"Breast":[0,20],"cancer":[1,7,18],"is":[2,11],"the":[3,47,71,135,164,185,192],"most":[4],"commonly":[5],"diagnosed":[6],"in":[8,52,179],"women.":[9],"Mammography":[10],"a":[12,33,180],"widely":[13],"used":[14],"tool":[15],"for":[16,60,77,86],"breast":[17,82,89,106,148,165,176],"screening.":[19],"calcifications":[21,83,107],"appear":[22],"on":[23,100],"mammograms":[24,80,102],"as":[25],"tiny":[26],"white":[27],"spots":[28],"or":[29],"grainy":[30],"dots":[31],"with":[32,81,118],"variety":[34],"of":[35,79,88,129,141,163,187],"clustering":[36],"structures":[37],"which":[38],"may":[39],"be":[40,75],"time-consuming":[41],"and":[42,65,84,121,131,158],"difficult":[43],"to":[44,173],"identify":[45],"by":[46],"human":[48],"eye.":[49],"Recent":[50],"advances":[51],"multi-scale":[53,98,115,193],"architectures":[54,73,99],"have":[55],"demonstrated":[56],"strong":[57,188],"feature":[58,123,189],"representation":[59,124,190],"both":[61,155],"large-scale":[62],"contextual":[63],"information":[64],"small-scale":[66],"features.":[67],"We":[68],"hypothesized":[69],"that":[70,103,170],"new":[72],"could":[74],"employed":[76],"classification":[78],"possibly":[85],"localization":[87],"calcification":[90,177],"regions.":[91],"In":[92],"this":[93],"study,":[94],"we":[95],"investigated":[96],"different":[97],"1,617":[101],"contained":[104],"only":[105],"locally":[108],"curated":[109],"from":[110],"our":[111],"institution.":[112],"Our":[113,151],"best":[114],"attention":[116],"network":[117,152],"hierarchical":[119],"block-wise":[120],"layer-wise":[122],"capability":[125],"achieved":[126],"an":[127,132],"accuracy":[128],"84.34%":[130],"area":[133],"under":[134],"receiver":[136],"operating":[137],"characteristic":[138],"curve":[139],"(AUROC)":[140],"90.36%.":[142],"Similar":[143],"performance":[144],"was":[145],"observed":[146],"across":[147],"density":[149],"categories.":[150],"simultaneously":[153],"processes":[154],"craniocaudal":[156],"(CC)":[157],"mediolateral":[159],"oblique":[160],"(MLO)":[161],"views":[162],"providing":[166],"class":[167],"activation":[168],"maps":[169],"were":[171],"able":[172],"precisely":[174],"localize":[175],"regions":[178],"weakly":[181],"supervised":[182],"manner,":[183],"indicating":[184],"benefits":[186],"through":[191],"architectures.":[194]},"counts_by_year":[{"year":2025,"cited_by_count":12},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":6}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
