{"id":"https://openalex.org/W2806445499","doi":"https://doi.org/10.1109/isbi.2018.8363567","title":"Reducing the effect of false positives in classification of detected clustered microcalcifications","display_name":"Reducing the effect of false positives in classification of detected clustered microcalcifications","publication_year":2018,"publication_date":"2018-04-01","ids":{"openalex":"https://openalex.org/W2806445499","doi":"https://doi.org/10.1109/isbi.2018.8363567","mag":"2806445499"},"language":"en","primary_location":{"id":"doi:10.1109/isbi.2018.8363567","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi.2018.8363567","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018)","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/A5048510347","display_name":"Yongyi Yang","orcid":"https://orcid.org/0000-0003-3564-3260"},"institutions":[{"id":"https://openalex.org/I180949307","display_name":"Illinois Institute of Technology","ror":"https://ror.org/037t3ry66","country_code":"US","type":"education","lineage":["https://openalex.org/I180949307"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Yongyi Yang","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Illinois Institute of Technology, Chicago, IL 60616, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Illinois Institute of Technology, Chicago, IL 60616, USA","institution_ids":["https://openalex.org/I180949307"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079423135","display_name":"Robert M. Nishikawa","orcid":"https://orcid.org/0000-0001-7720-9951"},"institutions":[{"id":"https://openalex.org/I180949307","display_name":"Illinois Institute of Technology","ror":"https://ror.org/037t3ry66","country_code":"US","type":"education","lineage":["https://openalex.org/I180949307"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Robert M. Nishikawa","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Illinois Institute of Technology, Chicago, IL, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Illinois Institute of Technology, Chicago, IL, USA","institution_ids":["https://openalex.org/I180949307"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5026995491","display_name":"Maria V. Sainz de","orcid":null},"institutions":[{"id":"https://openalex.org/I170201317","display_name":"University of Pittsburgh","ror":"https://ror.org/01an3r305","country_code":"US","type":"education","lineage":["https://openalex.org/I170201317"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Maria V. Sainz de Cea","raw_affiliation_strings":["Department of Radiology, University of Pittsburgh, Pittsburgh, PA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Radiology, University of Pittsburgh, Pittsburgh, PA, USA","institution_ids":["https://openalex.org/I170201317"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5048510347"],"corresponding_institution_ids":["https://openalex.org/I180949307"],"apc_list":null,"apc_paid":null,"fwci":0.1629,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.57058409,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"253","last_page":"256"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.9997000098228455,"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":0.9997000098228455,"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":0.9988999962806702,"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9961000084877014,"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":0.8549933433532715},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7411878705024719},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6798098683357239},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6606892943382263},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5847309231758118},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5177189707756042},{"id":"https://openalex.org/keywords/cluster","display_name":"Cluster (spacecraft)","score":0.47059690952301025},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.35753270983695984}],"concepts":[{"id":"https://openalex.org/C64869954","wikidata":"https://www.wikidata.org/wiki/Q1859747","display_name":"False positive paradox","level":2,"score":0.8549933433532715},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7411878705024719},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6798098683357239},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6606892943382263},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5847309231758118},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5177189707756042},{"id":"https://openalex.org/C164866538","wikidata":"https://www.wikidata.org/wiki/Q367351","display_name":"Cluster (spacecraft)","level":2,"score":0.47059690952301025},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.35753270983695984},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isbi.2018.8363567","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi.2018.8363567","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018)","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":14,"referenced_works":["https://openalex.org/W1536258358","https://openalex.org/W1978167298","https://openalex.org/W1981103483","https://openalex.org/W2050883594","https://openalex.org/W2050997943","https://openalex.org/W2058238527","https://openalex.org/W2066387791","https://openalex.org/W2076053181","https://openalex.org/W2095585056","https://openalex.org/W2133458583","https://openalex.org/W2136584955","https://openalex.org/W2511875022","https://openalex.org/W2560830114","https://openalex.org/W4241283611"],"related_works":["https://openalex.org/W1557094818","https://openalex.org/W2183246718","https://openalex.org/W2099261052","https://openalex.org/W3209204065","https://openalex.org/W1755711892","https://openalex.org/W2160907113","https://openalex.org/W2070813941","https://openalex.org/W2105707930","https://openalex.org/W3046510185","https://openalex.org/W2348583279"],"abstract_inverted_index":{"In":[0,49,108],"classification":[1,47,135],"of":[2,14,31,63,81,92,99,105,115,122,142],"clustered":[3],"microcalcifications":[4],"(MCs),":[5],"a":[6,12,25,54,70,74,90,120,139],"typical":[7],"approach":[8,58,118],"is":[9],"to":[10,59,77,95,133],"extract":[11],"set":[13,91,121],"quantitative":[15],"features":[16,94],"from":[17],"the":[18,36,46,61,79,85,97,102,106,109,113,116],"MC":[19],"objects":[20],"for":[21],"subsequent":[22],"analysis":[23],"by":[24],"machine":[26],"learning":[27],"algorithm.":[28],"The":[29,126],"presence":[30,62],"false":[32],"positives":[33],"(FPs)":[34],"among":[35,66],"identified":[37],"MCs":[38,68,83],"will":[39],"inevitably":[40],"cause":[41],"an":[42],"adverse":[43],"impact":[44,98],"on":[45,101,119],"accuracy.":[48],"this":[50],"work,":[51],"we":[52,111],"present":[53],"new":[55],"feature":[56],"extraction":[57],"accommodate":[60],"potential":[64],"FPs":[65,100],"detected":[67],"in":[69,84],"cluster.":[71,107],"We":[72],"introduce":[73],"quality":[75],"factor":[76],"enhance":[78],"contribution":[80],"true":[82],"extracted":[86],"features,":[87],"and":[88,145],"devise":[89],"cluster":[93],"reduce":[96],"spatial":[103],"distribution":[104],"experiments,":[110],"demonstrated":[112],"performance":[114,136],"proposed":[117],"186":[123],"FFDM":[124],"images.":[125],"results":[127],"show":[128],"that":[129],"it":[130],"could":[131],"lead":[132],"improved":[134],"consistently":[137],"over":[138],"wide":[140],"range":[141],"detection":[143],"sensitivity":[144],"FP":[146],"levels.":[147]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2018,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}