{"id":"https://openalex.org/W2605176288","doi":"https://doi.org/10.3233/fi-2017-1507","title":"Texture Analysis Method Based on Fractional Fourier Entropy and Fitness-scaling Adaptive Genetic Algorithm for Detecting Left-sided and Right-sided Sensorineural Hearing Loss","display_name":"Texture Analysis Method Based on Fractional Fourier Entropy and Fitness-scaling Adaptive Genetic Algorithm for Detecting Left-sided and Right-sided Sensorineural Hearing Loss","publication_year":2017,"publication_date":"2017-03-11","ids":{"openalex":"https://openalex.org/W2605176288","doi":"https://doi.org/10.3233/fi-2017-1507","mag":"2605176288"},"language":"en","primary_location":{"id":"doi:10.3233/fi-2017-1507","is_oa":false,"landing_page_url":"https://doi.org/10.3233/fi-2017-1507","pdf_url":null,"source":{"id":"https://openalex.org/S39012697","display_name":"Fundamenta Informaticae","issn_l":"0169-2968","issn":["0169-2968","1875-8681"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Fundamenta Informaticae","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/A5007987858","display_name":"Shuihua Wang\u200e","orcid":"https://orcid.org/0000-0003-4713-2791"},"institutions":[{"id":"https://openalex.org/I152031979","display_name":"Nanjing Normal University","ror":"https://ror.org/036trcv74","country_code":"CN","type":"education","lineage":["https://openalex.org/I152031979"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Shuihua Wang","raw_affiliation_strings":["School of Computer Science and Technology, Nanjing Normal University, Nanjing, Jiangsu 210023, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Nanjing Normal University, Nanjing, Jiangsu 210023, China","institution_ids":["https://openalex.org/I152031979"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053886291","display_name":"Ming Yang","orcid":"https://orcid.org/0000-0001-5307-8272"},"institutions":[{"id":"https://openalex.org/I4210090625","display_name":"Nanjing Children's Hospital","ror":"https://ror.org/000xvke80","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210090625"]},{"id":"https://openalex.org/I83519826","display_name":"Nanjing Medical University","ror":"https://ror.org/059gcgy73","country_code":"CN","type":"education","lineage":["https://openalex.org/I83519826"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ming Yang","raw_affiliation_strings":["Department of Radiology, Nanjing Childrens Hospital, Nanjing Medical University, Nanjing 210008, China"],"affiliations":[{"raw_affiliation_string":"Department of Radiology, Nanjing Childrens Hospital, Nanjing Medical University, Nanjing 210008, China","institution_ids":["https://openalex.org/I4210090625","https://openalex.org/I83519826"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101817245","display_name":"Jianwu Li","orcid":"https://orcid.org/0000-0002-8632-4334"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianwu Li","raw_affiliation_strings":["School of Computer Science and Technology, Beijing Institute of Technology, Beijing 100081, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Beijing Institute of Technology, Beijing 100081, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036357168","display_name":"Xueyan Wu","orcid":"https://orcid.org/0000-0002-2275-3834"},"institutions":[{"id":"https://openalex.org/I152031979","display_name":"Nanjing Normal University","ror":"https://ror.org/036trcv74","country_code":"CN","type":"education","lineage":["https://openalex.org/I152031979"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xueyan Wu","raw_affiliation_strings":["School of Computer Science and Technology, Nanjing Normal University, Nanjing, Jiangsu 210023, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Nanjing Normal University, Nanjing, Jiangsu 210023, China","institution_ids":["https://openalex.org/I152031979"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032583833","display_name":"Hainan Wang","orcid":"https://orcid.org/0009-0004-6848-7772"},"institutions":[{"id":"https://openalex.org/I152031979","display_name":"Nanjing Normal University","ror":"https://ror.org/036trcv74","country_code":"CN","type":"education","lineage":["https://openalex.org/I152031979"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hainan Wang","raw_affiliation_strings":["School of Computer Science and Technology, Nanjing Normal University, Nanjing, Jiangsu 210023, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Nanjing Normal University, Nanjing, Jiangsu 210023, China","institution_ids":["https://openalex.org/I152031979"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100395471","display_name":"Bin Liu","orcid":"https://orcid.org/0000-0002-1072-6601"},"institutions":[{"id":"https://openalex.org/I4210105806","display_name":"Zhongda Hospital Southeast University","ror":"https://ror.org/01k3hq685","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210105806"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bin Liu","raw_affiliation_strings":["Department of Radiology, Zhong-Da Hospital of Southeast University, Nanjing 210009, China"],"affiliations":[{"raw_affiliation_string":"Department of Radiology, Zhong-Da Hospital of Southeast University, Nanjing 210009, China","institution_ids":["https://openalex.org/I4210105806"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101822160","display_name":"Zhengchao Dong","orcid":"https://orcid.org/0000-0001-7746-5963"},"institutions":[{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]},{"id":"https://openalex.org/I33086117","display_name":"New York Psychoanalytic Society and Institute","ror":"https://ror.org/05azenf09","country_code":"US","type":"other","lineage":["https://openalex.org/I33086117"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhengchao Dong","raw_affiliation_strings":["Translational Imaging Division & MRI Unit, Columbia University and New York, State Psychiatric Institute, New York, NY 10032, USA"],"affiliations":[{"raw_affiliation_string":"Translational Imaging Division & MRI Unit, Columbia University and New York, State Psychiatric Institute, New York, NY 10032, USA","institution_ids":["https://openalex.org/I33086117","https://openalex.org/I78577930"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100434437","display_name":"Yudong Zhang","orcid":"https://orcid.org/0000-0002-4870-1493"},"institutions":[{"id":"https://openalex.org/I152031979","display_name":"Nanjing Normal University","ror":"https://ror.org/036trcv74","country_code":"CN","type":"education","lineage":["https://openalex.org/I152031979"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yudong Zhang","raw_affiliation_strings":["School of Computer Science and Technology, Nanjing Normal University, Nanjing, Jiangsu 210023, China. zhangyudong@njnu.edu.cn"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Nanjing Normal University, Nanjing, Jiangsu 210023, China. zhangyudong@njnu.edu.cn","institution_ids":["https://openalex.org/I152031979"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5007987858"],"corresponding_institution_ids":["https://openalex.org/I152031979"],"apc_list":null,"apc_paid":null,"fwci":5.0488,"has_fulltext":false,"cited_by_count":55,"citation_normalized_percentile":{"value":0.96055962,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":"151","issue":"1-4","first_page":"505","last_page":"521"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10542","display_name":"Vestibular and auditory disorders","score":0.989300012588501,"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"}},"topics":[{"id":"https://openalex.org/T10542","display_name":"Vestibular and auditory disorders","score":0.989300012588501,"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"}},{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9753999710083008,"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/T13731","display_name":"Advanced Computing and Algorithms","score":0.9376999735832214,"subfield":{"id":"https://openalex.org/subfields/3322","display_name":"Urban Studies"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.5212219953536987},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.511372983455658},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4936164617538452},{"id":"https://openalex.org/keywords/cad","display_name":"CAD","score":0.4875888228416443},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4874317944049835},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4847257137298584},{"id":"https://openalex.org/keywords/fourier-transform","display_name":"Fourier transform","score":0.45232659578323364},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.4326576590538025},{"id":"https://openalex.org/keywords/fitness-function","display_name":"Fitness function","score":0.42906349897384644},{"id":"https://openalex.org/keywords/magnetic-resonance-imaging","display_name":"Magnetic resonance imaging","score":0.4290527403354645},{"id":"https://openalex.org/keywords/scaling","display_name":"Scaling","score":0.42116329073905945},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.3714313805103302},{"id":"https://openalex.org/keywords/genetic-algorithm","display_name":"Genetic algorithm","score":0.3418075442314148},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3334695100784302},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.12511387467384338},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.09861773252487183},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.0948217511177063}],"concepts":[{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.5212219953536987},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.511372983455658},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4936164617538452},{"id":"https://openalex.org/C194789388","wikidata":"https://www.wikidata.org/wiki/Q17855283","display_name":"CAD","level":2,"score":0.4875888228416443},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4874317944049835},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4847257137298584},{"id":"https://openalex.org/C102519508","wikidata":"https://www.wikidata.org/wiki/Q6520159","display_name":"Fourier transform","level":2,"score":0.45232659578323364},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.4326576590538025},{"id":"https://openalex.org/C176066374","wikidata":"https://www.wikidata.org/wiki/Q629118","display_name":"Fitness function","level":3,"score":0.42906349897384644},{"id":"https://openalex.org/C143409427","wikidata":"https://www.wikidata.org/wiki/Q161238","display_name":"Magnetic resonance imaging","level":2,"score":0.4290527403354645},{"id":"https://openalex.org/C99844830","wikidata":"https://www.wikidata.org/wiki/Q102441924","display_name":"Scaling","level":2,"score":0.42116329073905945},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3714313805103302},{"id":"https://openalex.org/C8880873","wikidata":"https://www.wikidata.org/wiki/Q187787","display_name":"Genetic algorithm","level":2,"score":0.3418075442314148},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3334695100784302},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.12511387467384338},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.09861773252487183},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0948217511177063},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3233/fi-2017-1507","is_oa":false,"landing_page_url":"https://doi.org/10.3233/fi-2017-1507","pdf_url":null,"source":{"id":"https://openalex.org/S39012697","display_name":"Fundamenta Informaticae","issn_l":"0169-2968","issn":["0169-2968","1875-8681"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Fundamenta Informaticae","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":48,"referenced_works":["https://openalex.org/W169847426","https://openalex.org/W307994486","https://openalex.org/W1150696571","https://openalex.org/W1512995041","https://openalex.org/W1557268456","https://openalex.org/W1568319463","https://openalex.org/W1581627189","https://openalex.org/W1672221038","https://openalex.org/W1696102839","https://openalex.org/W1746384894","https://openalex.org/W1819349231","https://openalex.org/W1847687305","https://openalex.org/W1857434909","https://openalex.org/W1940090105","https://openalex.org/W1949503316","https://openalex.org/W1963939054","https://openalex.org/W1976806715","https://openalex.org/W1988619868","https://openalex.org/W2003342876","https://openalex.org/W2005324096","https://openalex.org/W2015920770","https://openalex.org/W2049742767","https://openalex.org/W2060117429","https://openalex.org/W2071881327","https://openalex.org/W2080537046","https://openalex.org/W2084861524","https://openalex.org/W2097392854","https://openalex.org/W2164857990","https://openalex.org/W2172846474","https://openalex.org/W2172975581","https://openalex.org/W2173548012","https://openalex.org/W2177332526","https://openalex.org/W2197252596","https://openalex.org/W2202656477","https://openalex.org/W2208264322","https://openalex.org/W2212264674","https://openalex.org/W2248397492","https://openalex.org/W2271760492","https://openalex.org/W2274774795","https://openalex.org/W2275123641","https://openalex.org/W2275933073","https://openalex.org/W2289495092","https://openalex.org/W2296119179","https://openalex.org/W2310869573","https://openalex.org/W2318839563","https://openalex.org/W2342656419","https://openalex.org/W2385559904","https://openalex.org/W2400559871"],"related_works":["https://openalex.org/W2334610590","https://openalex.org/W2320366403","https://openalex.org/W3204197061","https://openalex.org/W4251350712","https://openalex.org/W637098845","https://openalex.org/W2410116073","https://openalex.org/W3044972437","https://openalex.org/W4287707480","https://openalex.org/W2275866607","https://openalex.org/W3198805702"],"abstract_inverted_index":{"To":[0],"detect":[1],"the":[2,19,32,39,61,81],"sensorineural":[3],"hearing":[4],"loss":[5],"(SNHL)":[6],"from":[7,45],"healthy":[8],"people":[9],"accurately,":[10],"we":[11,41],"used":[12],"magnetic":[13],"resonance":[14],"imaging":[15,20],"(MRI)":[16],"to":[17],"obtain":[18],"data,":[21],"and":[22,99],"then":[23],"proposed":[24],"a":[25,67],"new":[26],"computer-aided":[27],"diagnosis":[28],"(CAD)":[29],"system,":[30],"on":[31],"basis":[33],"of":[34,84],"texture":[35],"analysis":[36,76],"method.":[37],"In":[38],"first,":[40],"extracted":[42],"12-element":[43],"feature":[44],"each":[46],"brain":[47],"image":[48],"via":[49],"fractional":[50],"Fourier":[51],"entropy":[52],"(FRFE).":[53],"Afterwards,":[54],"multilayer":[55],"perceptron":[56],"(MLP)":[57],"was":[58,64],"employed":[59],"as":[60],"classifier,":[62],"which":[63],"trained":[65],"by":[66],"novel":[68],"fitness-scaling":[69],"adaptive":[70],"genetic":[71],"algorithm":[72],"(FSAGA).":[73],"The":[74],"statistical":[75],"over":[77],"49":[78],"subjects":[79],"showed":[80],"overall":[82],"accuracy":[83],"our":[85],"method":[86],"yielded":[87],"95.51%.":[88],"Experimental":[89],"results":[90],"performed":[91],"better":[92,105],"than":[93,107],"four":[94],"state-of-the-art":[95],"weight":[96],"optimization":[97],"methods,":[98],"this":[100],"CAD":[101],"system":[102],"give":[103],"significantly":[104],"performance":[106],"manual":[108],"interpretation.":[109]},"counts_by_year":[{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":7},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":11},{"year":2019,"cited_by_count":8},{"year":2018,"cited_by_count":14},{"year":2017,"cited_by_count":6}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
