{"id":"https://openalex.org/W2634517207","doi":"https://doi.org/10.1109/isbi.2017.7950581","title":"Domain specific convolutional neural nets for detection of architectural distortion in mammograms","display_name":"Domain specific convolutional neural nets for detection of architectural distortion in mammograms","publication_year":2017,"publication_date":"2017-04-01","ids":{"openalex":"https://openalex.org/W2634517207","doi":"https://doi.org/10.1109/isbi.2017.7950581","mag":"2634517207"},"language":"en","primary_location":{"id":"doi:10.1109/isbi.2017.7950581","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi.2017.7950581","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017)","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/A5000712908","display_name":"Rami Ben\u2010Ari","orcid":"https://orcid.org/0000-0001-7162-7351"},"institutions":[{"id":"https://openalex.org/I4210167297","display_name":"IBM Research - Haifa","ror":"https://ror.org/05rw9t746","country_code":"IL","type":"facility","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210114115","https://openalex.org/I4210167297"]}],"countries":["IL"],"is_corresponding":true,"raw_author_name":"Rami Ben-Ari","raw_affiliation_strings":["IBM Research - Haifa, Israel"],"affiliations":[{"raw_affiliation_string":"IBM Research - Haifa, Israel","institution_ids":["https://openalex.org/I4210167297"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041055356","display_name":"Ayelet Akselrod-Ballin","orcid":null},"institutions":[{"id":"https://openalex.org/I4210167297","display_name":"IBM Research - Haifa","ror":"https://ror.org/05rw9t746","country_code":"IL","type":"facility","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210114115","https://openalex.org/I4210167297"]}],"countries":["IL"],"is_corresponding":false,"raw_author_name":"Ayelet Akselrod-Ballin","raw_affiliation_strings":["IBM Research - Haifa, Israel"],"affiliations":[{"raw_affiliation_string":"IBM Research - Haifa, Israel","institution_ids":["https://openalex.org/I4210167297"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020676344","display_name":"Leonid Karlinsky","orcid":"https://orcid.org/0000-0003-2524-2068"},"institutions":[{"id":"https://openalex.org/I4210167297","display_name":"IBM Research - Haifa","ror":"https://ror.org/05rw9t746","country_code":"IL","type":"facility","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210114115","https://openalex.org/I4210167297"]}],"countries":["IL"],"is_corresponding":false,"raw_author_name":"Leonid Karlinsky","raw_affiliation_strings":["IBM Research - Haifa, Israel"],"affiliations":[{"raw_affiliation_string":"IBM Research - Haifa, Israel","institution_ids":["https://openalex.org/I4210167297"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5085159082","display_name":"Sharbell Hashoul","orcid":null},"institutions":[{"id":"https://openalex.org/I4210167297","display_name":"IBM Research - Haifa","ror":"https://ror.org/05rw9t746","country_code":"IL","type":"facility","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210114115","https://openalex.org/I4210167297"]}],"countries":["IL"],"is_corresponding":false,"raw_author_name":"Sharbell Hashoul","raw_affiliation_strings":["IBM Research - Haifa, Israel"],"affiliations":[{"raw_affiliation_string":"IBM Research - Haifa, Israel","institution_ids":["https://openalex.org/I4210167297"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5000712908"],"corresponding_institution_ids":["https://openalex.org/I4210167297"],"apc_list":null,"apc_paid":null,"fwci":3.1203,"has_fulltext":false,"cited_by_count":35,"citation_normalized_percentile":{"value":0.93342418,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"552","last_page":"556"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":1.0,"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":1.0,"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/T12874","display_name":"Digital Imaging for Blood Diseases","score":0.9973000288009644,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9951000213623047,"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/false-positive-paradox","display_name":"False positive paradox","score":0.8622840642929077},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.8080776929855347},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.7057026028633118},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6768460273742676},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.670656681060791},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5985342264175415},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5467202067375183},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5465776920318604},{"id":"https://openalex.org/keywords/test-set","display_name":"Test set","score":0.5198729038238525},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5165099501609802},{"id":"https://openalex.org/keywords/binary-classification","display_name":"Binary classification","score":0.5145913362503052},{"id":"https://openalex.org/keywords/distortion","display_name":"Distortion (music)","score":0.5103489756584167},{"id":"https://openalex.org/keywords/sensitivity","display_name":"Sensitivity (control systems)","score":0.4997727870941162},{"id":"https://openalex.org/keywords/binary-number","display_name":"Binary number","score":0.46832138299942017},{"id":"https://openalex.org/keywords/true-positive-rate","display_name":"True positive rate","score":0.4240814447402954},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.4224904477596283},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3992186188697815},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.17674222588539124},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.062235862016677856}],"concepts":[{"id":"https://openalex.org/C64869954","wikidata":"https://www.wikidata.org/wiki/Q1859747","display_name":"False positive paradox","level":2,"score":0.8622840642929077},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.8080776929855347},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.7057026028633118},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6768460273742676},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.670656681060791},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5985342264175415},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5467202067375183},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5465776920318604},{"id":"https://openalex.org/C169903167","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Test set","level":2,"score":0.5198729038238525},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5165099501609802},{"id":"https://openalex.org/C66905080","wikidata":"https://www.wikidata.org/wiki/Q17005494","display_name":"Binary classification","level":3,"score":0.5145913362503052},{"id":"https://openalex.org/C126780896","wikidata":"https://www.wikidata.org/wiki/Q899871","display_name":"Distortion (music)","level":4,"score":0.5103489756584167},{"id":"https://openalex.org/C21200559","wikidata":"https://www.wikidata.org/wiki/Q7451068","display_name":"Sensitivity (control systems)","level":2,"score":0.4997727870941162},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.46832138299942017},{"id":"https://openalex.org/C2989486834","wikidata":"https://www.wikidata.org/wiki/Q3808900","display_name":"True positive rate","level":2,"score":0.4240814447402954},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.4224904477596283},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3992186188697815},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.17674222588539124},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.062235862016677856},{"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/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.0},{"id":"https://openalex.org/C194257627","wikidata":"https://www.wikidata.org/wiki/Q211554","display_name":"Amplifier","level":3,"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/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isbi.2017.7950581","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi.2017.7950581","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"No poverty","score":0.4399999976158142,"id":"https://metadata.un.org/sdg/1"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W652229124","https://openalex.org/W1570613334","https://openalex.org/W1965169669","https://openalex.org/W2062118960","https://openalex.org/W2063817871","https://openalex.org/W2067191022","https://openalex.org/W2087550369","https://openalex.org/W2102605133","https://openalex.org/W2161381512","https://openalex.org/W2165731505","https://openalex.org/W2181901042","https://openalex.org/W2216351247","https://openalex.org/W2294815452","https://openalex.org/W2425224815","https://openalex.org/W2523382659","https://openalex.org/W2963173190","https://openalex.org/W3097096317","https://openalex.org/W6648737282"],"related_works":["https://openalex.org/W1557094818","https://openalex.org/W3129715955","https://openalex.org/W4287692494","https://openalex.org/W3027053746","https://openalex.org/W3047594718","https://openalex.org/W4299651861","https://openalex.org/W2953243682","https://openalex.org/W4386222044","https://openalex.org/W2183246718","https://openalex.org/W4226316650"],"abstract_inverted_index":{"Detection":[0],"of":[1],"Architectural":[2],"distortion":[3],"(AD)":[4],"is":[5,21,49],"important":[6],"for":[7,135],"ruling":[8],"out":[9],"possible":[10],"pre-malignant":[11],"lesions":[12],"in":[13,55,145],"breast,":[14],"but":[15],"due":[16],"to":[17,100],"its":[18],"subtlety,":[19],"it":[20],"often":[22],"missed":[23],"on":[24,39,79,91],"the":[25,47,53,92,101,142,146],"screening":[26],"mammograms.":[27],"In":[28,62],"this":[29,63,72],"work":[30],"we":[31,65],"suggest":[32,66],"a":[33,67,76,80],"novel":[34],"AD":[35],"detection":[36,109],"method":[37,70,90],"based":[38],"region":[40,82],"proposal":[41],"convolution":[42],"neural":[43],"nets":[44],"(R-CNN).":[45],"When":[46],"data":[48,96],"scarce,":[50],"as":[51],"typically":[52],"case":[54],"medical":[56],"domain,":[57],"R-CNN":[58,69,104],"yields":[59,126],"poor":[60],"results.":[61],"study,":[64],"new":[68],"addressing":[71],"shortcoming":[73],"by":[74,84],"using":[75],"pretrained":[77],"network":[78],"candidate":[81],"guided":[83],"clinical":[85],"observations.":[86],"We":[87],"test":[88],"our":[89],"publicly":[93],"available":[94],"DDSM":[95],"set,":[97],"with":[98,119],"comparison":[99],"latest":[102],"faster":[103],"and":[105,123,125],"previous":[106],"works.":[107],"Our":[108],"accuracy":[110],"allows":[111],"binary":[112],"image":[113,130],"classification":[114],"(normal":[115],"vs.":[116],"containing":[117],"AD)":[118],"over":[120],"80%":[121],"sensitivity":[122],"specificity,":[124],"0.46":[127],"false-positives":[128],"per":[129],"at":[131],"83%":[132],"true-positive":[133],"rate,":[134],"localization":[136],"accuracy.":[137],"These":[138],"measures":[139],"significantly":[140],"improve":[141],"best":[143],"results":[144],"literature.":[147]},"counts_by_year":[{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":7},{"year":2020,"cited_by_count":7},{"year":2019,"cited_by_count":8},{"year":2017,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}