{"id":"https://openalex.org/W3047155262","doi":"https://doi.org/10.1109/tfuzz.2020.3013681","title":"Hierarchical Fused Model With Deep Learning and Type-2 Fuzzy Learning for Breast Cancer Diagnosis","display_name":"Hierarchical Fused Model With Deep Learning and Type-2 Fuzzy Learning for Breast Cancer Diagnosis","publication_year":2020,"publication_date":"2020-08-03","ids":{"openalex":"https://openalex.org/W3047155262","doi":"https://doi.org/10.1109/tfuzz.2020.3013681","mag":"3047155262"},"language":"en","primary_location":{"id":"doi:10.1109/tfuzz.2020.3013681","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tfuzz.2020.3013681","pdf_url":null,"source":{"id":"https://openalex.org/S134177497","display_name":"IEEE Transactions on Fuzzy Systems","issn_l":"1063-6706","issn":["1063-6706","1941-0034"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Fuzzy Systems","raw_type":"journal-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/A5029149757","display_name":"Tianyu Shen","orcid":"https://orcid.org/0000-0001-7614-7015"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210094879","display_name":"Shandong Institute of Automation","ror":"https://ror.org/00qdtba35","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210094879","https://openalex.org/I4210142748"]},{"id":"https://openalex.org/I4210112270","display_name":"Qingdao Academy of Intelligent Industries","ror":"https://ror.org/02a0rnh86","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210112270"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tianyu Shen","raw_affiliation_strings":["Qingdao Academy of Intelligent Industries, Qingdao, China","State Key Laboratory for Management and Control of Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China,","University of Chinese Academy of Sciences, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-7614-7015","affiliations":[{"raw_affiliation_string":"Qingdao Academy of Intelligent Industries, Qingdao, China","institution_ids":["https://openalex.org/I4210112270"]},{"raw_affiliation_string":"State Key Laboratory for Management and Control of Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China,","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210094879"]},{"raw_affiliation_string":"University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085577263","display_name":"Jiangong Wang","orcid":"https://orcid.org/0000-0002-0259-0118"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210094879","display_name":"Shandong Institute of Automation","ror":"https://ror.org/00qdtba35","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210094879","https://openalex.org/I4210142748"]},{"id":"https://openalex.org/I4210112270","display_name":"Qingdao Academy of Intelligent Industries","ror":"https://ror.org/02a0rnh86","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210112270"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiangong Wang","raw_affiliation_strings":["Qingdao Academy of Intelligent Industries, Qingdao, China","State Key Laboratory for Management and Control of Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China,","University of Chinese Academy of Sciences, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-0259-0118","affiliations":[{"raw_affiliation_string":"Qingdao Academy of Intelligent Industries, Qingdao, China","institution_ids":["https://openalex.org/I4210112270"]},{"raw_affiliation_string":"State Key Laboratory for Management and Control of Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China,","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210094879"]},{"raw_affiliation_string":"University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042895349","display_name":"Chao Gou","orcid":"https://orcid.org/0000-0002-4128-886X"},"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":"Chao Gou","raw_affiliation_strings":["School of Intelligent Systems Engineering, Sun Yat-Sen University, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-4128-886X","affiliations":[{"raw_affiliation_string":"School of Intelligent Systems Engineering, Sun Yat-Sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5113600509","display_name":"Fei\u2013Yue Wang","orcid":"https://orcid.org/0000-0001-9185-3989"},"institutions":[{"id":"https://openalex.org/I111950717","display_name":"Macau University of Science and Technology","ror":"https://ror.org/03jqs2n27","country_code":"MO","type":"education","lineage":["https://openalex.org/I111950717","https://openalex.org/I4391767947"]},{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]},{"id":"https://openalex.org/I4210112270","display_name":"Qingdao Academy of Intelligent Industries","ror":"https://ror.org/02a0rnh86","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210112270"]}],"countries":["CN","MO"],"is_corresponding":false,"raw_author_name":"Fei-Yue Wang","raw_affiliation_strings":["Institute of Systems Engineering, Macau University of Science and Technology, Macau, China","Qingdao Academy of Intelligent Industries, Qingdao, China","State Key Laboratory for Management and Control of Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-9185-3989","affiliations":[{"raw_affiliation_string":"Institute of Systems Engineering, Macau University of Science and Technology, Macau, China","institution_ids":["https://openalex.org/I111950717"]},{"raw_affiliation_string":"Qingdao Academy of Intelligent Industries, Qingdao, China","institution_ids":["https://openalex.org/I4210112270"]},{"raw_affiliation_string":"State Key Laboratory for Management and Control of Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":7,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":6.3002,"has_fulltext":false,"cited_by_count":89,"citation_normalized_percentile":{"value":0.97157514,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":"28","issue":"12","first_page":"3204","last_page":"3218"},"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":0.996999979019165,"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/T12702","display_name":"Brain Tumor Detection and Classification","score":0.9958999752998352,"subfield":{"id":"https://openalex.org/subfields/2808","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7844469547271729},{"id":"https://openalex.org/keywords/interpretability","display_name":"Interpretability","score":0.6951939463615417},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6932726502418518},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5918639898300171},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5703415870666504},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5346113443374634},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.5134056806564331},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5058434009552002},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.48876309394836426},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.47444188594818115},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.4664532542228699},{"id":"https://openalex.org/keywords/mammography","display_name":"Mammography","score":0.42644989490509033},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.42609933018684387},{"id":"https://openalex.org/keywords/multilayer-perceptron","display_name":"Multilayer perceptron","score":0.4177383482456207},{"id":"https://openalex.org/keywords/breast-cancer","display_name":"Breast cancer","score":0.29429322481155396},{"id":"https://openalex.org/keywords/cancer","display_name":"Cancer","score":0.10695910453796387}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7844469547271729},{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.6951939463615417},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6932726502418518},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5918639898300171},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5703415870666504},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5346113443374634},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.5134056806564331},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5058434009552002},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.48876309394836426},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.47444188594818115},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.4664532542228699},{"id":"https://openalex.org/C2780472235","wikidata":"https://www.wikidata.org/wiki/Q324634","display_name":"Mammography","level":4,"score":0.42644989490509033},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.42609933018684387},{"id":"https://openalex.org/C179717631","wikidata":"https://www.wikidata.org/wiki/Q2991667","display_name":"Multilayer perceptron","level":3,"score":0.4177383482456207},{"id":"https://openalex.org/C530470458","wikidata":"https://www.wikidata.org/wiki/Q128581","display_name":"Breast cancer","level":3,"score":0.29429322481155396},{"id":"https://openalex.org/C121608353","wikidata":"https://www.wikidata.org/wiki/Q12078","display_name":"Cancer","level":2,"score":0.10695910453796387},{"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/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tfuzz.2020.3013681","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tfuzz.2020.3013681","pdf_url":null,"source":{"id":"https://openalex.org/S134177497","display_name":"IEEE Transactions on Fuzzy Systems","issn_l":"1063-6706","issn":["1063-6706","1941-0034"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Fuzzy Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4832151346","display_name":"\u57fa\u4e8eCPSS\u7684\u6d41\u7a0b\u5de5\u4e1a\u751f\u4ea7\u8ba1\u5212\u77e5\u8bc6\u81ea\u52a8\u5316\u7cfb\u7edf\u53ca\u5e94\u7528\u9a8c\u8bc1","funder_award_id":"61533019","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":69,"referenced_works":["https://openalex.org/W74434018","https://openalex.org/W104184427","https://openalex.org/W118196362","https://openalex.org/W147723833","https://openalex.org/W304373761","https://openalex.org/W1686810756","https://openalex.org/W1901129140","https://openalex.org/W1903029394","https://openalex.org/W1926368015","https://openalex.org/W1963691800","https://openalex.org/W1964468250","https://openalex.org/W1989907351","https://openalex.org/W2010938273","https://openalex.org/W2015701733","https://openalex.org/W2019207321","https://openalex.org/W2028672930","https://openalex.org/W2031534613","https://openalex.org/W2035009069","https://openalex.org/W2035028362","https://openalex.org/W2103535990","https://openalex.org/W2103754534","https://openalex.org/W2113076747","https://openalex.org/W2126801281","https://openalex.org/W2149914169","https://openalex.org/W2157041604","https://openalex.org/W2160182247","https://openalex.org/W2163605009","https://openalex.org/W2194775991","https://openalex.org/W2217755689","https://openalex.org/W2294923432","https://openalex.org/W2580480204","https://openalex.org/W2585496890","https://openalex.org/W2606880313","https://openalex.org/W2610981713","https://openalex.org/W2614710595","https://openalex.org/W2618530766","https://openalex.org/W2633139931","https://openalex.org/W2755855890","https://openalex.org/W2781525129","https://openalex.org/W2788133288","https://openalex.org/W2792983091","https://openalex.org/W2798753173","https://openalex.org/W2807106332","https://openalex.org/W2895089584","https://openalex.org/W2912492375","https://openalex.org/W2912565176","https://openalex.org/W2958533996","https://openalex.org/W2962835968","https://openalex.org/W2963553763","https://openalex.org/W2963881378","https://openalex.org/W2969719351","https://openalex.org/W2977153525","https://openalex.org/W2978017498","https://openalex.org/W2992973523","https://openalex.org/W2997568695","https://openalex.org/W3000638052","https://openalex.org/W3100715827","https://openalex.org/W4211007335","https://openalex.org/W4245152641","https://openalex.org/W4252813286","https://openalex.org/W6603016037","https://openalex.org/W6604254268","https://openalex.org/W6604844929","https://openalex.org/W6637373629","https://openalex.org/W6639824700","https://openalex.org/W6697325517","https://openalex.org/W6736906655","https://openalex.org/W6751648627","https://openalex.org/W6754808139"],"related_works":["https://openalex.org/W2905433371","https://openalex.org/W2888392564","https://openalex.org/W4310278675","https://openalex.org/W4388422664","https://openalex.org/W4390569940","https://openalex.org/W4361193272","https://openalex.org/W2963326959","https://openalex.org/W4388685194","https://openalex.org/W3135897568","https://openalex.org/W4309346246"],"abstract_inverted_index":{"Breast":[0],"cancer":[1],"diagnosis":[2],"based":[3,62],"on":[4,63,195],"medical":[5],"imaging":[6],"necessitates":[7],"both":[8],"fine-grained":[9],"lesion":[10],"segmentation":[11,74,88],"and":[12,22,48,65,75,91,107,135,145,158,171,203,215],"disease":[13,76,140],"grading.":[14],"Although":[15],"deep":[16],"learning":[17,27,67,169],"(DL)":[18],"offers":[19],"an":[20],"emerging":[21],"powerful":[23],"paradigm":[24],"of":[25,44,78,86,101,116,151,174,189,201],"feature":[26,152],"for":[28,72],"these":[29],"two":[30],"tasks,":[31],"it":[32],"is":[33,98,178,184,193],"hampered":[34],"from":[35,119,132],"popularizing":[36],"in":[37,166],"practical":[38],"application":[39],"due":[40],"to":[41,68,137],"the":[42,70,114,120,127,130,139,149,161,172,182,190,196],"lack":[43],"interpretability,":[45],"generalization":[46,176],"ability,":[47],"large":[49],"labeled":[50],"training":[51],"sets.":[52],"In":[53,180],"this":[54],"article,":[55],"we":[56],"propose":[57],"a":[58,87,92,99,167,204],"hierarchical":[59,93],"fused":[60],"model":[61,89],"DL":[64],"fuzzy":[66,94,105,108,143,159],"overcome":[69],"drawbacks":[71],"pixelwise":[73],"grading":[77,141],"mammography":[79],"breast":[80],"images.":[81],"The":[82,111,187],"proposed":[83,191],"system":[84,162,192],"consists":[85],"(ResU-segNet)":[90],"classifier":[95],"(HFC)":[96],"that":[97],"fusion":[100],"interval":[102],"type-2":[103],"possibilistic":[104],"c-means":[106],"neural":[109,124],"network.":[110],"ResU-segNet":[112],"segments":[113],"masks":[115,136],"mass":[117,133],"regions":[118],"images":[121,134],"through":[122,142,207],"convolutional":[123],"networks,":[125],"while":[126],"HFC":[128],"encodes":[129],"features":[131],"obtain":[138],"representation":[144],"rule-based":[146],"learning.":[147],"Through":[148],"integration":[150],"extraction":[153],"aided":[154],"by":[155],"domain":[156],"knowledge":[157],"learning,":[160],"achieves":[163],"favorable":[164],"performance":[165],"few-shot":[168],"manner,":[170],"deterioration":[173],"cross-dataset":[175],"ability":[177],"alleviated.":[179],"addition,":[181],"interpretability":[183],"further":[185],"enhanced.":[186],"effectiveness":[188],"analyzed":[194],"publicly":[197],"available":[198],"mammogram":[199],"database":[200,206],"INbreast":[202],"private":[205],"cross-validation.":[208],"Thorough":[209],"comparative":[210],"experiments":[211],"are":[212],"also":[213],"conducted":[214],"demonstrated.":[216]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":18},{"year":2024,"cited_by_count":19},{"year":2023,"cited_by_count":22},{"year":2022,"cited_by_count":11},{"year":2021,"cited_by_count":13},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}
