{"id":"https://openalex.org/W3131231694","doi":"https://doi.org/10.1109/access.2021.3061487","title":"An Efficient Classification of MRI Brain Images","display_name":"An Efficient Classification of MRI Brain Images","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3131231694","doi":"https://doi.org/10.1109/access.2021.3061487","mag":"3131231694"},"language":"en","primary_location":{"id":"doi:10.1109/access.2021.3061487","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3061487","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09360738.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09360738.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5073073869","display_name":"Muhammad Assam","orcid":"https://orcid.org/0000-0001-7331-5351"},"institutions":[{"id":"https://openalex.org/I168879160","display_name":"Zhejiang University of Science and Technology","ror":"https://ror.org/05mx0wr29","country_code":"CN","type":"education","lineage":["https://openalex.org/I168879160"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Muhammad Assam","raw_affiliation_strings":["College of Computer Science and Technology, Zhejiang University, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I168879160"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004287063","display_name":"Hira Kanwal","orcid":"https://orcid.org/0000-0002-0479-5539"},"institutions":[{"id":"https://openalex.org/I174731842","display_name":"Islamia University of Bahawalpur","ror":"https://ror.org/002rc4w13","country_code":"PK","type":"education","lineage":["https://openalex.org/I174731842"]}],"countries":["PK"],"is_corresponding":false,"raw_author_name":"Hira Kanwal","raw_affiliation_strings":["The Islamia University of Bahawalpur, Bahawalpur, Pakistan"],"affiliations":[{"raw_affiliation_string":"The Islamia University of Bahawalpur, Bahawalpur, Pakistan","institution_ids":["https://openalex.org/I174731842"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056975287","display_name":"Umar Farooq","orcid":"https://orcid.org/0000-0003-4947-7267"},"institutions":[{"id":"https://openalex.org/I4210154218","display_name":"University of Science and Technology Bannu","ror":"https://ror.org/04be2dn15","country_code":"PK","type":"education","lineage":["https://openalex.org/I4210154218"]}],"countries":["PK"],"is_corresponding":false,"raw_author_name":"Umar Farooq","raw_affiliation_strings":["University of Science and Technology~(UST) at Bannu, Bannu, Pakistan"],"affiliations":[{"raw_affiliation_string":"University of Science and Technology~(UST) at Bannu, Bannu, Pakistan","institution_ids":["https://openalex.org/I4210154218"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021669484","display_name":"Said Khalid Shah","orcid":"https://orcid.org/0000-0002-7841-687X"},"institutions":[{"id":"https://openalex.org/I4210154218","display_name":"University of Science and Technology Bannu","ror":"https://ror.org/04be2dn15","country_code":"PK","type":"education","lineage":["https://openalex.org/I4210154218"]}],"countries":["PK"],"is_corresponding":false,"raw_author_name":"Said Khalid Shah","raw_affiliation_strings":["University of Science and Technology~(UST) at Bannu, Bannu, Pakistan"],"affiliations":[{"raw_affiliation_string":"University of Science and Technology~(UST) at Bannu, Bannu, Pakistan","institution_ids":["https://openalex.org/I4210154218"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087270783","display_name":"Arif Mehmood","orcid":"https://orcid.org/0000-0001-5822-4005"},"institutions":[{"id":"https://openalex.org/I174731842","display_name":"Islamia University of Bahawalpur","ror":"https://ror.org/002rc4w13","country_code":"PK","type":"education","lineage":["https://openalex.org/I174731842"]}],"countries":["PK"],"is_corresponding":false,"raw_author_name":"Arif Mehmood","raw_affiliation_strings":["The Islamia University of Bahawalpur, Bahawalpur, Pakistan"],"affiliations":[{"raw_affiliation_string":"The Islamia University of Bahawalpur, Bahawalpur, Pakistan","institution_ids":["https://openalex.org/I174731842"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044080887","display_name":"Gyu Sang Choi","orcid":"https://orcid.org/0000-0002-0854-768X"},"institutions":[{"id":"https://openalex.org/I55240360","display_name":"Yeungnam University","ror":"https://ror.org/05yc6p159","country_code":"KR","type":"education","lineage":["https://openalex.org/I55240360"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Gyu Sang Choi","raw_affiliation_strings":["Yeungnam University, Gyeongsan, South Korea"],"affiliations":[{"raw_affiliation_string":"Yeungnam University, Gyeongsan, South Korea","institution_ids":["https://openalex.org/I55240360"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5073073869"],"corresponding_institution_ids":["https://openalex.org/I168879160"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":2.7691,"has_fulltext":true,"cited_by_count":43,"citation_normalized_percentile":{"value":0.90837455,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"9","issue":null,"first_page":"33313","last_page":"33322"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12702","display_name":"Brain Tumor Detection and Classification","score":0.9998999834060669,"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/T12702","display_name":"Brain Tumor Detection and Classification","score":0.9998999834060669,"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/T12874","display_name":"Digital Imaging for Blood Diseases","score":0.991100013256073,"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/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9850000143051147,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7803890109062195},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.772733211517334},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5774350762367249},{"id":"https://openalex.org/keywords/discrete-wavelet-transform","display_name":"Discrete wavelet transform","score":0.5666380524635315},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5347100496292114},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.5298523902893066},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5127209424972534},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.4936850965023041},{"id":"https://openalex.org/keywords/medical-imaging","display_name":"Medical imaging","score":0.4840487837791443},{"id":"https://openalex.org/keywords/grayscale","display_name":"Grayscale","score":0.4778710901737213},{"id":"https://openalex.org/keywords/wavelet-transform","display_name":"Wavelet transform","score":0.42971891164779663},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.40340298414230347},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.1699867844581604},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.12339213490486145}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7803890109062195},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.772733211517334},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5774350762367249},{"id":"https://openalex.org/C46286280","wikidata":"https://www.wikidata.org/wiki/Q2414958","display_name":"Discrete wavelet transform","level":4,"score":0.5666380524635315},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5347100496292114},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.5298523902893066},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5127209424972534},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.4936850965023041},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.4840487837791443},{"id":"https://openalex.org/C78201319","wikidata":"https://www.wikidata.org/wiki/Q685727","display_name":"Grayscale","level":3,"score":0.4778710901737213},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.42971891164779663},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.40340298414230347},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.1699867844581604},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.12339213490486145}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2021.3061487","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3061487","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09360738.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:328736f9d99f406ba78232afd4ad2aab","is_oa":true,"landing_page_url":"https://doaj.org/article/328736f9d99f406ba78232afd4ad2aab","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 9, Pp 33313-33322 (2021)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2021.3061487","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3061487","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09360738.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/15","display_name":"Life in Land","score":0.5299999713897705}],"awards":[{"id":"https://openalex.org/G1739134435","display_name":null,"funder_award_id":"IITP-","funder_id":"https://openalex.org/F4320324891","funder_display_name":"Iran Telecommunication Research Center"},{"id":"https://openalex.org/G1989376136","display_name":null,"funder_award_id":"NRF-2019R1A2C1006159","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"},{"id":"https://openalex.org/G342704958","display_name":null,"funder_award_id":"funded","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"},{"id":"https://openalex.org/G6072120315","display_name":null,"funder_award_id":"funded","funder_id":"https://openalex.org/F4320335489","funder_display_name":"Institute for Information and Communications Technology Promotion"},{"id":"https://openalex.org/G6082346649","display_name":null,"funder_award_id":"IITP-2020-2016-0-00313","funder_id":"https://openalex.org/F4320335489","funder_display_name":"Institute for Information and Communications Technology Promotion"},{"id":"https://openalex.org/G6354916557","display_name":null,"funder_award_id":"IITP-2020-2016-0-00313","funder_id":"https://openalex.org/F4320324891","funder_display_name":"Iran Telecommunication Research Center"},{"id":"https://openalex.org/G6933364494","display_name":null,"funder_award_id":"IITP-2020-2016-0-00313","funder_id":"https://openalex.org/F4320328359","funder_display_name":"Ministry of Science and ICT, South Korea"},{"id":"https://openalex.org/G7685055460","display_name":null,"funder_award_id":"Grant","funder_id":"https://openalex.org/F4320328359","funder_display_name":"Ministry of Science and ICT, South Korea"},{"id":"https://openalex.org/G982292920","display_name":null,"funder_award_id":"NRF-20","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"}],"funders":[{"id":"https://openalex.org/F4320320671","display_name":"National Research Foundation","ror":"https://ror.org/05s0g1g46"},{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"},{"id":"https://openalex.org/F4320324891","display_name":"Iran Telecommunication Research Center","ror":"https://ror.org/01a3g2z22"},{"id":"https://openalex.org/F4320328359","display_name":"Ministry of Science and ICT, South Korea","ror":"https://ror.org/01wpjm123"},{"id":"https://openalex.org/F4320335489","display_name":"Institute for Information and Communications Technology Promotion","ror":"https://ror.org/01g0hqq23"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3131231694.pdf","grobid_xml":"https://content.openalex.org/works/W3131231694.grobid-xml"},"referenced_works_count":39,"referenced_works":["https://openalex.org/W1534477342","https://openalex.org/W1578884157","https://openalex.org/W1967551258","https://openalex.org/W1974314515","https://openalex.org/W1978417612","https://openalex.org/W1986075844","https://openalex.org/W1988819287","https://openalex.org/W1993566723","https://openalex.org/W1995642009","https://openalex.org/W1999286885","https://openalex.org/W2017896827","https://openalex.org/W2032054866","https://openalex.org/W2038344945","https://openalex.org/W2047355037","https://openalex.org/W2054702571","https://openalex.org/W2055957434","https://openalex.org/W2063131317","https://openalex.org/W2075710390","https://openalex.org/W2090221122","https://openalex.org/W2090341258","https://openalex.org/W2095649164","https://openalex.org/W2098765040","https://openalex.org/W2113242816","https://openalex.org/W2131346203","https://openalex.org/W2139211873","https://openalex.org/W2162567222","https://openalex.org/W2558107930","https://openalex.org/W2718656419","https://openalex.org/W2888044560","https://openalex.org/W2938518631","https://openalex.org/W2947692947","https://openalex.org/W2962728585","https://openalex.org/W3009718233","https://openalex.org/W3011430986","https://openalex.org/W3033621327","https://openalex.org/W3146352869","https://openalex.org/W3199248531","https://openalex.org/W4256068510","https://openalex.org/W6801041174"],"related_works":["https://openalex.org/W183670115","https://openalex.org/W4245420407","https://openalex.org/W1501179639","https://openalex.org/W3199035354","https://openalex.org/W2085792030","https://openalex.org/W4401371153","https://openalex.org/W1807354010","https://openalex.org/W3143644526","https://openalex.org/W598225674","https://openalex.org/W1588899229"],"abstract_inverted_index":{"The":[0,37,112,240],"unprecedented":[1],"improvements":[2],"in":[3,31,120,165,286,293,308,314],"computing":[4],"capabilities":[5],"and":[6,17,29,80,85,95,134,155,157,163,216,260,262,272,289,306],"the":[7,13,24,32,54,58,72,101,122,142,148,166,172,200,212,225,236,301],"introduction":[8],"of":[9,19,26,34,48,53,74,141,150,214,221,228,238,316,321],"advanced":[10,43],"techniques":[11],"for":[12,60,71,109,147,182,235,258],"analysis,":[14],"interpretation,":[15],"processing,":[16],"visualization":[18],"images":[20,52,77,82,89,173,181],"have":[21],"greatly":[22],"diversified":[23],"domain":[25],"medical":[27,35,107],"sciences":[28],"resulted":[30,285],"field":[33],"imaging.":[36],"Magnetic":[38],"Resonance":[39],"Imaging":[40],"(MRI),":[41],"an":[42,218,246],"imaging":[44],"technique,":[45,284],"is":[46,115,145,304],"capable":[47],"producing":[49],"high":[50],"quality":[51],"human":[55],"body":[56],"including":[57],"brain":[59,76,91],"diagnosis":[61],"purposes.":[62,111],"This":[63],"paper":[64],"proposes":[65],"a":[66,116,252],"simple":[67],"but":[68],"efficient":[69],"solution":[70],"classification":[73,237,312],"MRI":[75],"into":[78],"normal,":[79],"abnormal":[81],"containing":[83],"disorders":[84],"injuries.":[86],"It":[87],"uses":[88,189],"with":[90,224,268,275,318],"tumor,":[92],"acute":[93],"stroke":[94],"alzheimer,":[96],"besides":[97],"normal":[98],"images,":[99],"from":[100,176,199],"public":[102],"dataset":[103],"developed":[104],"by":[105],"harvard":[106],"school,":[108],"evaluation":[110],"proposed":[113,302],"model":[114],"four":[117],"step":[118],"process,":[119],"which":[121,249,279],"steps":[123],"are":[124,174,208,230],"named:":[125],"1).":[126],"Pre-processing,":[127],"2).":[128],"Features":[129,132],"Extraction,":[130],"3).":[131],"Reduction,":[133],"4).":[135],"Classification.":[136],"Median":[137],"filter,":[138],"being":[139],"one":[140],"best":[143],"algorithms,":[144],"used":[146,209,280],"removal":[149],"noise":[151],"such":[152,160],"as":[153,161],"salt":[154],"pepper,":[156],"unwanted":[158],"components":[159],"scalp":[162],"skull,":[164],"pre-processing":[167],"step.":[168],"During":[169],"this":[170],"stage,":[171,204],"converted":[175],"gray":[177],"scale":[178],"to":[179,195,210,232,254],"colored":[180],"further":[183],"processing.":[184],"In":[185,202],"second":[186],"step,":[187],"it":[188],"Discrete":[190],"Wavelet":[191],"Transform":[192],"(DWT)":[193],"technique":[194],"extract":[196],"different":[197,233],"features":[198,215,229],"images.":[201,239],"third":[203],"Color":[205],"Moments":[206],"(CMs)":[207],"reduce":[211],"number":[213,320],"get":[217],"optimal":[219,226,322],"set":[220,227],"characteristics.":[222],"Images":[223],"passed":[231],"classifiers":[234,264],"Feed":[241],"Forward":[242],"-":[243],"ANN":[244],"(FF-ANN),":[245],"individual":[247],"classifier,":[248],"was":[250],"given":[251],"65%":[253],"35%":[255],"split":[256],"ratio":[257],"training":[259],"testing,":[261],"hybrid":[263],"called:":[265],"Random":[266,269,273],"Subspace":[267,274],"Forest":[270],"(RSwithRF)":[271],"Bayesian":[276],"Network":[277],"(RSwithBN),":[278],"10-Fold":[281],"cross":[282],"validation":[283],"95.83%,":[287],"97.14%":[288],"95.71%":[290],"accurate":[291],"classification,":[292],"corresponding":[294],"order.":[295],"These":[296],"promising":[297],"results":[298],"show":[299],"that":[300],"method":[303],"robust":[305],"efficient,":[307],"comparison":[309],"with,":[310],"existing":[311],"methods":[313],"terms":[315],"accuracy":[317],"smaller":[319],"features.":[323]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":12},{"year":2022,"cited_by_count":8}],"updated_date":"2026-03-31T07:56:22.981413","created_date":"2025-10-10T00:00:00"}
