{"id":"https://openalex.org/W2766793238","doi":"https://doi.org/10.23919/eusipco.2017.8081168","title":"A new method for breast cancer identification using multi-modal features in quaternionic form","display_name":"A new method for breast cancer identification using multi-modal features in quaternionic form","publication_year":2017,"publication_date":"2017-08-01","ids":{"openalex":"https://openalex.org/W2766793238","doi":"https://doi.org/10.23919/eusipco.2017.8081168","mag":"2766793238"},"language":"en","primary_location":{"id":"doi:10.23919/eusipco.2017.8081168","is_oa":false,"landing_page_url":"https://doi.org/10.23919/eusipco.2017.8081168","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 25th European Signal Processing Conference (EUSIPCO)","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/A5034996156","display_name":"George Apostolopoulos","orcid":"https://orcid.org/0000-0002-0816-6561"},"institutions":[{"id":"https://openalex.org/I174878644","display_name":"University of Patras","ror":"https://ror.org/017wvtq80","country_code":"GR","type":"education","lineage":["https://openalex.org/I174878644"]}],"countries":["GR"],"is_corresponding":true,"raw_author_name":"G. Apostolopoulos","raw_affiliation_strings":["Electrical and Computer Engineering Department, University of Patras, Greece"],"affiliations":[{"raw_affiliation_string":"Electrical and Computer Engineering Department, University of Patras, Greece","institution_ids":["https://openalex.org/I174878644"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059003636","display_name":"Athanasios Koutras","orcid":"https://orcid.org/0000-0002-1411-8697"},"institutions":[{"id":"https://openalex.org/I1319660883","display_name":"Technological Educational Institute of Western Greece","ror":"https://ror.org/01mymm084","country_code":"GR","type":"education","lineage":["https://openalex.org/I1319660883"]},{"id":"https://openalex.org/I174878644","display_name":"University of Patras","ror":"https://ror.org/017wvtq80","country_code":"GR","type":"education","lineage":["https://openalex.org/I174878644"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"A. Koutras","raw_affiliation_strings":["Electrical and Computer Engineering Department, University of Patras, Greece","Informatics and Mass Media Department, Technical Educational Institute of Western Greece, Greece"],"affiliations":[{"raw_affiliation_string":"Electrical and Computer Engineering Department, University of Patras, Greece","institution_ids":["https://openalex.org/I174878644"]},{"raw_affiliation_string":"Informatics and Mass Media Department, Technical Educational Institute of Western Greece, Greece","institution_ids":["https://openalex.org/I1319660883"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081154983","display_name":"Ioanna Christoyianni","orcid":null},"institutions":[{"id":"https://openalex.org/I174878644","display_name":"University of Patras","ror":"https://ror.org/017wvtq80","country_code":"GR","type":"education","lineage":["https://openalex.org/I174878644"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"I. Christoyianni","raw_affiliation_strings":["Electrical and Computer Engineering Department, University of Patras, Greece"],"affiliations":[{"raw_affiliation_string":"Electrical and Computer Engineering Department, University of Patras, Greece","institution_ids":["https://openalex.org/I174878644"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5111324975","display_name":"Evangelos Dermatas","orcid":null},"institutions":[{"id":"https://openalex.org/I174878644","display_name":"University of Patras","ror":"https://ror.org/017wvtq80","country_code":"GR","type":"education","lineage":["https://openalex.org/I174878644"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"E. Dermatas","raw_affiliation_strings":["Electrical and Computer Engineering Department, University of Patras, Greece"],"affiliations":[{"raw_affiliation_string":"Electrical and Computer Engineering Department, University of Patras, Greece","institution_ids":["https://openalex.org/I174878644"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5034996156"],"corresponding_institution_ids":["https://openalex.org/I174878644"],"apc_list":null,"apc_paid":null,"fwci":0.182,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.5793018,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":"338","issue":null,"first_page":"56","last_page":"60"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9998999834060669,"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/T10862","display_name":"AI in cancer detection","score":0.9976000189781189,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9936000108718872,"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/zernike-polynomials","display_name":"Zernike polynomials","score":0.7090393900871277},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6925716996192932},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6890058517456055},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.641828715801239},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6122204661369324},{"id":"https://openalex.org/keywords/mammography","display_name":"Mammography","score":0.5601485371589661},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5564054846763611},{"id":"https://openalex.org/keywords/receiver-operating-characteristic","display_name":"Receiver operating characteristic","score":0.5552875399589539},{"id":"https://openalex.org/keywords/cad","display_name":"CAD","score":0.5312095880508423},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5113048553466797},{"id":"https://openalex.org/keywords/modal","display_name":"Modal","score":0.49360454082489014},{"id":"https://openalex.org/keywords/computer-aided-diagnosis","display_name":"Computer-aided diagnosis","score":0.4525616765022278},{"id":"https://openalex.org/keywords/breast-cancer","display_name":"Breast cancer","score":0.4319501519203186},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.15818312764167786},{"id":"https://openalex.org/keywords/cancer","display_name":"Cancer","score":0.14079329371452332},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.09127360582351685}],"concepts":[{"id":"https://openalex.org/C92423082","wikidata":"https://www.wikidata.org/wiki/Q132146","display_name":"Zernike polynomials","level":3,"score":0.7090393900871277},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6925716996192932},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6890058517456055},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.641828715801239},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6122204661369324},{"id":"https://openalex.org/C2780472235","wikidata":"https://www.wikidata.org/wiki/Q324634","display_name":"Mammography","level":4,"score":0.5601485371589661},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5564054846763611},{"id":"https://openalex.org/C58471807","wikidata":"https://www.wikidata.org/wiki/Q327120","display_name":"Receiver operating characteristic","level":2,"score":0.5552875399589539},{"id":"https://openalex.org/C194789388","wikidata":"https://www.wikidata.org/wiki/Q17855283","display_name":"CAD","level":2,"score":0.5312095880508423},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5113048553466797},{"id":"https://openalex.org/C71139939","wikidata":"https://www.wikidata.org/wiki/Q910194","display_name":"Modal","level":2,"score":0.49360454082489014},{"id":"https://openalex.org/C2779549770","wikidata":"https://www.wikidata.org/wiki/Q1122413","display_name":"Computer-aided diagnosis","level":2,"score":0.4525616765022278},{"id":"https://openalex.org/C530470458","wikidata":"https://www.wikidata.org/wiki/Q128581","display_name":"Breast cancer","level":3,"score":0.4319501519203186},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.15818312764167786},{"id":"https://openalex.org/C121608353","wikidata":"https://www.wikidata.org/wiki/Q12078","display_name":"Cancer","level":2,"score":0.14079329371452332},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.09127360582351685},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"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/C188027245","wikidata":"https://www.wikidata.org/wiki/Q750446","display_name":"Polymer chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C199639397","wikidata":"https://www.wikidata.org/wiki/Q1788588","display_name":"Engineering drawing","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C165699331","wikidata":"https://www.wikidata.org/wiki/Q461533","display_name":"Wavefront","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.23919/eusipco.2017.8081168","is_oa":false,"landing_page_url":"https://doi.org/10.23919/eusipco.2017.8081168","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 25th European Signal Processing Conference (EUSIPCO)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","score":0.7300000190734863,"display_name":"Good health and well-being"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W1521586765","https://openalex.org/W1757407923","https://openalex.org/W1977910068","https://openalex.org/W1978167298","https://openalex.org/W1986923534","https://openalex.org/W1988264599","https://openalex.org/W1998242976","https://openalex.org/W2006500012","https://openalex.org/W2016959837","https://openalex.org/W2019036560","https://openalex.org/W2039321332","https://openalex.org/W2055783626","https://openalex.org/W2061079740","https://openalex.org/W2081737161","https://openalex.org/W2102679304","https://openalex.org/W2103986031","https://openalex.org/W2118390174","https://openalex.org/W2141955292","https://openalex.org/W2146880335","https://openalex.org/W2154051385","https://openalex.org/W2164842737","https://openalex.org/W2237008727","https://openalex.org/W2293451440","https://openalex.org/W3106132744","https://openalex.org/W6665594779","https://openalex.org/W6677724871"],"related_works":["https://openalex.org/W1589419489","https://openalex.org/W4229543669","https://openalex.org/W1783185948","https://openalex.org/W615772105","https://openalex.org/W2999505641","https://openalex.org/W2401866201","https://openalex.org/W2945629533","https://openalex.org/W1554029525","https://openalex.org/W1978794434","https://openalex.org/W2013631688"],"abstract_inverted_index":{"Mammography":[0],"is":[1,166,175],"still":[2],"the":[3,11,125,129,133,169,191,216],"most":[4],"effective":[5,197],"procedure":[6],"for":[7,25,51,205],"early":[8],"diagnosis":[9],"of":[10,33,55,58,74,100,106,141,154],"breast":[12,52,208],"cancer.":[13],"Computer-aided":[14],"Diagnosis":[15],"(CAD)":[16],"systems":[17],"can":[18,194,199],"be":[19,195,200],"very":[20],"helpful":[21],"in":[22,35,60,66,121,128,215],"this":[23,44],"direction":[24],"radiologists":[26],"to":[27,97,124,211],"recognize":[28],"abnormal":[29,159],"and":[30,94,119,151,158,198,222],"normal":[31,157],"regions":[32],"interest":[34],"digital":[36,61],"mammograms":[37,62],"faster":[38],"than":[39],"traditional":[40],"screening":[41],"program.":[42],"In":[43],"work,":[45],"we":[46,136],"propose":[47,137],"a":[48,67,78,104,138,203],"new":[49,139],"method":[50,72,165,193],"cancer":[53,209],"identification":[54],"all":[56],"types":[57],"lesions":[59],"using":[63,177],"multimodal":[64],"features":[65,115],"quaternionic":[68,122],"representation.":[69],"The":[70,113,163,172,183],"proposed":[71,164,192],"consists":[73],"two":[75,84],"steps:":[76],"First,":[77],"novel":[79],"feature":[80],"extraction":[81],"module":[82,127],"utilizes":[83],"dimensional":[85],"discrete":[86],"transforms":[87],"based":[88],"on":[89,168],"ART,":[90],"Shapelets,":[91],"Zernike":[92],"moments":[93],"Gabor":[95],"filters":[96],"decompose":[98],"Regions":[99],"Suspicion":[101],"(ROS)":[102],"into":[103],"set":[105],"localized":[107],"basis":[108],"functions":[109],"with":[110,147],"different":[111],"shapes.":[112],"extracted":[114],"are":[116],"then":[117],"fused":[118],"presented":[120,214],"representation":[123],"classification":[126,134],"second":[130],"step.":[131],"For":[132],"task,":[135],"type":[140],"classifier":[142],"(Q-classifier)":[143],"that":[144,190,218],"successfully,":[145],"accurately,":[146],"low":[148],"computational":[149],"cost":[150],"higher":[152],"speed":[153],"diagnosis,":[155],"recognizes":[156],"ROS":[160],"from":[161],"mammograms.":[162],"evaluated":[167,176],"Mini-MIAS":[170],"database.":[171],"methods'":[173],"performance":[174],"Receiver":[178],"Operating":[179],"Characteristics":[180],"(ROC)":[181],"curve.":[182],"achieved":[184],"result":[185],"AUC":[186],"=":[187],"0.934":[188],"shows":[189],"quite":[196],"used":[201],"as":[202],"tool":[204],"efficiently":[206],"diagnosing":[207],"compared":[210],"similar":[212],"techniques":[213],"literature":[217],"use":[219],"SVM":[220],"classifiers":[221],"unimodal":[223],"features.":[224]},"counts_by_year":[{"year":2021,"cited_by_count":2},{"year":2020,"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"}