{"id":"https://openalex.org/W4206480638","doi":"https://doi.org/10.3390/axioms11010015","title":"Automated Detection and Classification of Meningioma Tumor from MR Images Using Sea Lion Optimization and Deep Learning Models","display_name":"Automated Detection and Classification of Meningioma Tumor from MR Images Using Sea Lion Optimization and Deep Learning Models","publication_year":2021,"publication_date":"2021-12-30","ids":{"openalex":"https://openalex.org/W4206480638","doi":"https://doi.org/10.3390/axioms11010015"},"language":"en","primary_location":{"id":"doi:10.3390/axioms11010015","is_oa":true,"landing_page_url":"https://doi.org/10.3390/axioms11010015","pdf_url":"https://www.mdpi.com/2075-1680/11/1/15/pdf?version=1640850618","source":{"id":"https://openalex.org/S4210173132","display_name":"Axioms","issn_l":"2075-1680","issn":["2075-1680"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Axioms","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2075-1680/11/1/15/pdf?version=1640850618","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5013158228","display_name":"Aswathy Sukumaran","orcid":"https://orcid.org/0000-0003-0459-9260"},"institutions":[{"id":"https://openalex.org/I133769559","display_name":"Government Medical College","ror":"https://ror.org/016je1253","country_code":"IN","type":"education","lineage":["https://openalex.org/I133769559"]},{"id":"https://openalex.org/I4210107658","display_name":"Machine Intelligence Research Labs","ror":"https://ror.org/013kgb629","country_code":"US","type":"facility","lineage":["https://openalex.org/I4210107658"]}],"countries":["IN","US"],"is_corresponding":true,"raw_author_name":"Aswathy Sukumaran","raw_affiliation_strings":["Department of Computer Science and Engineering, Jyothi Engineering College, Thrissur 679531, Kerala, India","Machine Intelligence Research Labs (MIR Labs), Scientific Network for Innovation and Research Excellence, P.O. Box 2259, Auburn, WA 98071-2259, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Jyothi Engineering College, Thrissur 679531, Kerala, India","institution_ids":["https://openalex.org/I133769559"]},{"raw_affiliation_string":"Machine Intelligence Research Labs (MIR Labs), Scientific Network for Innovation and Research Excellence, P.O. Box 2259, Auburn, WA 98071-2259, USA","institution_ids":["https://openalex.org/I4210107658"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5087542455","display_name":"Ajith Abraham","orcid":"https://orcid.org/0000-0002-0169-6738"},"institutions":[{"id":"https://openalex.org/I4210116741","display_name":"Innopolis University","ror":"https://ror.org/02b7jh107","country_code":"RU","type":"education","lineage":["https://openalex.org/I4210116741"]},{"id":"https://openalex.org/I4210107658","display_name":"Machine Intelligence Research Labs","ror":"https://ror.org/013kgb629","country_code":"US","type":"facility","lineage":["https://openalex.org/I4210107658"]}],"countries":["RU","US"],"is_corresponding":false,"raw_author_name":"Ajith Abraham","raw_affiliation_strings":["Centre for Artificial Intelligence, Innopolis University, 420500 Innopolis, Russia","Machine Intelligence Research Labs (MIR Labs), Scientific Network for Innovation and Research Excellence, P.O. Box 2259, Auburn, WA 98071-2259, USA"],"affiliations":[{"raw_affiliation_string":"Centre for Artificial Intelligence, Innopolis University, 420500 Innopolis, Russia","institution_ids":["https://openalex.org/I4210116741"]},{"raw_affiliation_string":"Machine Intelligence Research Labs (MIR Labs), Scientific Network for Innovation and Research Excellence, P.O. Box 2259, Auburn, WA 98071-2259, USA","institution_ids":["https://openalex.org/I4210107658"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5013158228"],"corresponding_institution_ids":["https://openalex.org/I133769559","https://openalex.org/I4210107658"],"apc_list":{"value":1400,"currency":"CHF","value_usd":1515},"apc_paid":{"value":1400,"currency":"CHF","value_usd":1515},"fwci":1.0001,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.75560129,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":97},"biblio":{"volume":"11","issue":"1","first_page":"15","last_page":"15"},"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9977999925613403,"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":0.9927999973297119,"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/benchmark","display_name":"Benchmark (surveying)","score":0.6997030973434448},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6732243895530701},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6519927978515625},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5847897529602051},{"id":"https://openalex.org/keywords/magnetic-resonance-imaging","display_name":"Magnetic resonance imaging","score":0.5127459764480591},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.505577802658081},{"id":"https://openalex.org/keywords/brain-tumor","display_name":"Brain tumor","score":0.4895256459712982},{"id":"https://openalex.org/keywords/s\u00f8rensen\u2013dice-coefficient","display_name":"S\u00f8rensen\u2013Dice coefficient","score":0.4786325991153717},{"id":"https://openalex.org/keywords/meningioma","display_name":"Meningioma","score":0.4501398503780365},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4435354471206665},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.27781134843826294},{"id":"https://openalex.org/keywords/radiology","display_name":"Radiology","score":0.16702741384506226},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.15916213393211365},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.10530698299407959},{"id":"https://openalex.org/keywords/pathology","display_name":"Pathology","score":0.08009707927703857}],"concepts":[{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6997030973434448},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6732243895530701},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6519927978515625},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5847897529602051},{"id":"https://openalex.org/C143409427","wikidata":"https://www.wikidata.org/wiki/Q161238","display_name":"Magnetic resonance imaging","level":2,"score":0.5127459764480591},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.505577802658081},{"id":"https://openalex.org/C2779130545","wikidata":"https://www.wikidata.org/wiki/Q233309","display_name":"Brain tumor","level":2,"score":0.4895256459712982},{"id":"https://openalex.org/C163892561","wikidata":"https://www.wikidata.org/wiki/Q2613728","display_name":"S\u00f8rensen\u2013Dice coefficient","level":4,"score":0.4786325991153717},{"id":"https://openalex.org/C2779160599","wikidata":"https://www.wikidata.org/wiki/Q369157","display_name":"Meningioma","level":2,"score":0.4501398503780365},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4435354471206665},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.27781134843826294},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.16702741384506226},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.15916213393211365},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.10530698299407959},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.08009707927703857},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/axioms11010015","is_oa":true,"landing_page_url":"https://doi.org/10.3390/axioms11010015","pdf_url":"https://www.mdpi.com/2075-1680/11/1/15/pdf?version=1640850618","source":{"id":"https://openalex.org/S4210173132","display_name":"Axioms","issn_l":"2075-1680","issn":["2075-1680"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Axioms","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:91f219a4f3ba477f8048785380dc4c9d","is_oa":true,"landing_page_url":"https://doaj.org/article/91f219a4f3ba477f8048785380dc4c9d","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":"Axioms, Vol 11, Iss 1, p 15 (2021)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2075-1680/11/1/15/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/axioms11010015","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Axioms; Volume 11; Issue 1; Pages: 15","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/axioms11010015","is_oa":true,"landing_page_url":"https://doi.org/10.3390/axioms11010015","pdf_url":"https://www.mdpi.com/2075-1680/11/1/15/pdf?version=1640850618","source":{"id":"https://openalex.org/S4210173132","display_name":"Axioms","issn_l":"2075-1680","issn":["2075-1680"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Axioms","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/14","score":0.800000011920929,"display_name":"Life below water"}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4206480638.pdf","grobid_xml":"https://content.openalex.org/works/W4206480638.grobid-xml"},"referenced_works_count":47,"referenced_works":["https://openalex.org/W213114031","https://openalex.org/W1533861849","https://openalex.org/W1967551258","https://openalex.org/W2011832499","https://openalex.org/W2029630915","https://openalex.org/W2182635617","https://openalex.org/W2308961649","https://openalex.org/W2314688663","https://openalex.org/W2519606635","https://openalex.org/W2730803689","https://openalex.org/W2761475227","https://openalex.org/W2766374185","https://openalex.org/W2780099243","https://openalex.org/W2791609473","https://openalex.org/W2796680681","https://openalex.org/W2810138651","https://openalex.org/W2889685514","https://openalex.org/W2897188827","https://openalex.org/W2899671259","https://openalex.org/W2919979744","https://openalex.org/W2921483513","https://openalex.org/W2938518631","https://openalex.org/W2954205860","https://openalex.org/W2955805844","https://openalex.org/W2959645102","https://openalex.org/W2963384288","https://openalex.org/W2971689172","https://openalex.org/W2974878728","https://openalex.org/W2980001902","https://openalex.org/W2987256191","https://openalex.org/W2995003683","https://openalex.org/W3011430986","https://openalex.org/W3015757828","https://openalex.org/W3016988868","https://openalex.org/W3039513141","https://openalex.org/W3043327973","https://openalex.org/W3047489282","https://openalex.org/W3048804154","https://openalex.org/W3065287867","https://openalex.org/W3083878718","https://openalex.org/W3091501175","https://openalex.org/W3102680000","https://openalex.org/W3105505025","https://openalex.org/W3109801163","https://openalex.org/W3161959969","https://openalex.org/W6686076587","https://openalex.org/W6775961247"],"related_works":["https://openalex.org/W2378211422","https://openalex.org/W2745001401","https://openalex.org/W4321353415","https://openalex.org/W2130974462","https://openalex.org/W972276598","https://openalex.org/W4246352526","https://openalex.org/W2028665553","https://openalex.org/W4230315250","https://openalex.org/W2553444198","https://openalex.org/W3041660763"],"abstract_inverted_index":{"Meningiomas":[0],"are":[1],"the":[2,19,28,49,150,165,172],"most":[3,70],"prevalent":[4],"benign":[5],"intracranial":[6],"life-threatening":[7],"brain":[8,29,168],"tumors,":[9,169],"with":[10,126,147,153],"a":[11,15,76,84,154],"life":[12],"expectancy":[13],"of":[14,25,39,60,93,124,156,167],"few":[16],"months":[17],"in":[18,27,128,164],"later":[20],"stages,":[21],"so":[22],"this":[23],"type":[24],"tumor":[26,71],"image":[30],"should":[31],"be":[32],"recognized":[33,51],"and":[34,78,114,145],"detected":[35],"efficiently.":[36],"The":[37,57,158],"source":[38],"meningiomas":[40],"is":[41,48,65,75,133],"unknown.":[42],"Radiation":[43],"exposure,":[44],"particularly":[45],"during":[46],"childhood,":[47],"sole":[50],"environmental":[52],"risk":[53],"factor":[54],"for":[55,97,139],"meningiomas.":[56],"imaging":[58,63],"technique":[59],"magnetic":[61],"resonance":[62],"(MRI)":[64],"commonly":[66],"used":[67],"to":[68,104,119,171],"detect":[69],"forms":[72],"as":[73,111],"it":[74],"non-invasive":[77],"painless":[79],"method.":[80],"This":[81],"study":[82],"introduces":[83],"CNN-HHO":[85],"integrated":[86],"automated":[87],"identification":[88],"model,":[89],"which":[90],"makes":[91],"use":[92],"SeaLion":[94,127],"optimization":[95],"methods":[96,160],"improving":[98],"overall":[99,122],"network":[100],"optimization.":[101],"In":[102],"addition":[103],"these":[105],"techniques,":[106],"various":[107],"CNN":[108,125],"models":[109,152],"such":[110],"Resnet,":[112],"VGG,":[113],"DenseNet":[115,148],"have":[116],"been":[117],"utilized":[118],"give":[120],"an":[121],"influence":[123],"each":[129],"methodology.":[130],"Each":[131],"model":[132],"tested":[134],"on":[135],"our":[136],"benchmark":[137],"dataset":[138],"accuracy,":[140],"specificity,":[141],"dice":[142],"coefficient,":[143],"MCC,":[144],"sensitivity,":[146],"outperforming":[149],"other":[151],"precision":[155],"98%.":[157],"proposed":[159],"outperform":[161],"existing":[162,173],"alternatives":[163],"detection":[166],"according":[170],"experimental":[174],"findings.":[175]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":4}],"updated_date":"2025-11-14T23:14:49.485078","created_date":"2022-01-26T00:00:00"}