{"id":"https://openalex.org/W2164898173","doi":"https://doi.org/10.1109/icsmc.2008.4811832","title":"A cost-sensitive cascaded method for automatic mass detection","display_name":"A cost-sensitive cascaded method for automatic mass detection","publication_year":2008,"publication_date":"2008-10-01","ids":{"openalex":"https://openalex.org/W2164898173","doi":"https://doi.org/10.1109/icsmc.2008.4811832","mag":"2164898173"},"language":"en","primary_location":{"id":"doi:10.1109/icsmc.2008.4811832","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icsmc.2008.4811832","pdf_url":null,"source":{"id":"https://openalex.org/S4210195764","display_name":"Conference proceedings/Conference proceedings - IEEE International Conference on Systems, Man, and Cybernetics","issn_l":"1062-922X","issn":["1062-922X","2577-1655"],"is_oa":false,"is_in_doaj":false,"is_core":false,"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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2008 IEEE International Conference on Systems, Man and Cybernetics","raw_type":"proceedings-article"},"type":"conference-paper","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/A5100772272","display_name":"Ning Li","orcid":"https://orcid.org/0000-0001-9014-5913"},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ning Li","raw_affiliation_strings":["National Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, China","institution_ids":["https://openalex.org/I881766915"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110230403","display_name":"Huajie Zhou","orcid":null},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hua-Jie Zhou","raw_affiliation_strings":["National Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, China","institution_ids":["https://openalex.org/I881766915"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100547110","display_name":"Qiaojin Guo","orcid":null},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiao-Jin Guo","raw_affiliation_strings":["National Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, China","institution_ids":["https://openalex.org/I881766915"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5111673780","display_name":"Yu-Bin Yang","orcid":"https://orcid.org/0000-0002-3764-1114"},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yubin Yang","raw_affiliation_strings":["National Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, China","institution_ids":["https://openalex.org/I881766915"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I881766915"],"apc_list":null,"apc_paid":null,"fwci":0.2518,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.53039566,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"3454","last_page":"3458"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.9994999766349792,"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":0.9994999766349792,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9976999759674072,"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9929999709129333,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.8243600130081177},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7429780960083008},{"id":"https://openalex.org/keywords/histogram","display_name":"Histogram","score":0.712393581867218},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6925778388977051},{"id":"https://openalex.org/keywords/false-positive-paradox","display_name":"False positive paradox","score":0.6869736909866333},{"id":"https://openalex.org/keywords/local-binary-patterns","display_name":"Local binary patterns","score":0.6288802623748779},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5424057841300964},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5317223072052002},{"id":"https://openalex.org/keywords/gray-level","display_name":"Gray level","score":0.4754338264465332},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4694492518901825},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4571719765663147},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.44560375809669495},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.4134373664855957},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.24346357583999634}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8243600130081177},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7429780960083008},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.712393581867218},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6925778388977051},{"id":"https://openalex.org/C64869954","wikidata":"https://www.wikidata.org/wiki/Q1859747","display_name":"False positive paradox","level":2,"score":0.6869736909866333},{"id":"https://openalex.org/C87335442","wikidata":"https://www.wikidata.org/wiki/Q2494345","display_name":"Local binary patterns","level":4,"score":0.6288802623748779},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5424057841300964},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5317223072052002},{"id":"https://openalex.org/C2985861186","wikidata":"https://www.wikidata.org/wiki/Q685727","display_name":"Gray level","level":3,"score":0.4754338264465332},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4694492518901825},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4571719765663147},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.44560375809669495},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.4134373664855957},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.24346357583999634}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icsmc.2008.4811832","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icsmc.2008.4811832","pdf_url":null,"source":{"id":"https://openalex.org/S4210195764","display_name":"Conference proceedings/Conference proceedings - IEEE International Conference on Systems, Man, and Cybernetics","issn_l":"1062-922X","issn":["1062-922X","2577-1655"],"is_oa":false,"is_in_doaj":false,"is_core":false,"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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2008 IEEE International Conference on Systems, Man and Cybernetics","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.6000000238418579}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W193887030","https://openalex.org/W2014408515","https://openalex.org/W2036581391","https://openalex.org/W2039051707","https://openalex.org/W2045331387","https://openalex.org/W2053803205","https://openalex.org/W2058732827","https://openalex.org/W2083954772","https://openalex.org/W2085834212","https://openalex.org/W2106393550","https://openalex.org/W2109597745","https://openalex.org/W2122436376","https://openalex.org/W2132549764","https://openalex.org/W2163352848","https://openalex.org/W2166509719","https://openalex.org/W2606684948","https://openalex.org/W3097096317"],"related_works":["https://openalex.org/W2581696209","https://openalex.org/W2020430625","https://openalex.org/W2044065526","https://openalex.org/W2058306460","https://openalex.org/W2955952267","https://openalex.org/W2083564146","https://openalex.org/W2076436625","https://openalex.org/W2148428954","https://openalex.org/W2049095871","https://openalex.org/W3044709448"],"abstract_inverted_index":{"Mass":[0],"detection":[1],"in":[2,101],"mammograms":[3,38],"is":[4,99],"a":[5,13,75],"challenging":[6],"problem.":[7],"In":[8,32],"this":[9],"paper,":[10],"we":[11,34],"propose":[12],"cost-sensitive":[14,76],"cascaded":[15,77],"method":[16,98],"for":[17],"automatic":[18],"mass":[19,102],"detection,":[20],"which":[21],"employs":[22],"machine":[23],"learning":[24],"techniques":[25],"to":[26,74,87],"detect":[27],"region":[28],"of":[29],"interests":[30],"(ROI).":[31],"detail,":[33],"divide":[35],"the":[36,96],"original":[37],"into":[39],"overlapped":[40],"squared":[41],"sub-images.":[42],"For":[43],"each":[44],"sub-image,":[45],"intensity":[46],"features":[47,53,63],"based":[48,54,64],"on":[49,55,65],"gray":[50],"histogram,":[51],"texture":[52,62],"spatial":[56],"gray-level":[57],"co-occurrence":[58],"matrix":[59],"(SGLDM)":[60],"and":[61,72,82],"local":[66],"binary":[67],"patterns":[68],"(LBP)":[69],"are":[70,85],"extracted":[71],"input":[73],"classifier.":[78],"Simple":[79],"threshold":[80],"segmentation":[81],"neural":[83],"network":[84],"used":[86],"further":[88],"reduce":[89],"false":[90],"positives.":[91],"Experimental":[92],"results":[93],"show":[94],"that":[95],"proposed":[97],"effective":[100],"detection.":[103]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
