{"id":"https://openalex.org/W4412419263","doi":"https://doi.org/10.32604/cmc.2025.066314","title":"Switchable Normalization Based Faster RCNN for MRI Brain Tumor Segmentation","display_name":"Switchable Normalization Based Faster RCNN for MRI Brain Tumor Segmentation","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4412419263","doi":"https://doi.org/10.32604/cmc.2025.066314"},"language":"en","primary_location":{"id":"doi:10.32604/cmc.2025.066314","is_oa":true,"landing_page_url":"https://doi.org/10.32604/cmc.2025.066314","pdf_url":null,"source":{"id":"https://openalex.org/S4210191605","display_name":"Computers, materials & continua/Computers, materials & continua (Print)","issn_l":"1546-2218","issn":["1546-2218","1546-2226"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computers, Materials &amp; Continua","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://doi.org/10.32604/cmc.2025.066314","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5088411665","display_name":"Rachana Poongodan","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Rachana Poongodan","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5092069254","display_name":"Dayanand Lal Narayan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dayanand Lal Narayan","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5118987001","display_name":"Deepika Gadakatte Lokeshwarappa","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Deepika Gadakatte Lokeshwarappa","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002372334","display_name":"Hirald Dwaraka Praveena","orcid":"https://orcid.org/0000-0002-8785-3684"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hirald Dwaraka Praveena","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5029780795","display_name":"Dae-Ki Kang","orcid":"https://orcid.org/0000-0002-4147-2835"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dae-Ki Kang","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5088411665"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.26061571,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"84","issue":"3","first_page":"5751","last_page":"5772"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12702","display_name":"Brain Tumor Detection and Classification","score":0.9934999942779541,"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":0.9934999942779541,"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":0.9316999912261963,"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9190000295639038,"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/normalization","display_name":"Normalization (sociology)","score":0.6497205495834351},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5455561876296997},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5425710082054138},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.48129239678382874},{"id":"https://openalex.org/keywords/neuroscience","display_name":"Neuroscience","score":0.42981964349746704},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4255576729774475},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.3917522132396698},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.28586292266845703}],"concepts":[{"id":"https://openalex.org/C136886441","wikidata":"https://www.wikidata.org/wiki/Q926129","display_name":"Normalization (sociology)","level":2,"score":0.6497205495834351},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5455561876296997},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5425710082054138},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.48129239678382874},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.42981964349746704},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4255576729774475},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.3917522132396698},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.28586292266845703},{"id":"https://openalex.org/C19165224","wikidata":"https://www.wikidata.org/wiki/Q23404","display_name":"Anthropology","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.32604/cmc.2025.066314","is_oa":true,"landing_page_url":"https://doi.org/10.32604/cmc.2025.066314","pdf_url":null,"source":{"id":"https://openalex.org/S4210191605","display_name":"Computers, materials & continua/Computers, materials & continua (Print)","issn_l":"1546-2218","issn":["1546-2218","1546-2226"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computers, Materials &amp; Continua","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.32604/cmc.2025.066314","is_oa":true,"landing_page_url":"https://doi.org/10.32604/cmc.2025.066314","pdf_url":null,"source":{"id":"https://openalex.org/S4210191605","display_name":"Computers, materials & continua/Computers, materials & continua (Print)","issn_l":"1546-2218","issn":["1546-2218","1546-2226"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computers, Materials &amp; Continua","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W1884191083","https://openalex.org/W1985215121","https://openalex.org/W2310992461","https://openalex.org/W2587828787","https://openalex.org/W2791575870","https://openalex.org/W2891278843","https://openalex.org/W2895056585","https://openalex.org/W2901364394","https://openalex.org/W2903554604","https://openalex.org/W2919780733","https://openalex.org/W2924134239","https://openalex.org/W2938134567","https://openalex.org/W2943931219","https://openalex.org/W2962291057","https://openalex.org/W2966269666","https://openalex.org/W2971667786","https://openalex.org/W2995378448","https://openalex.org/W2998847595","https://openalex.org/W3013630101","https://openalex.org/W3016120846","https://openalex.org/W3017037418","https://openalex.org/W3018201087","https://openalex.org/W3021659040","https://openalex.org/W3032660954","https://openalex.org/W3037521341","https://openalex.org/W3044256341","https://openalex.org/W3087421454","https://openalex.org/W3116714234","https://openalex.org/W3118442183","https://openalex.org/W3126474728","https://openalex.org/W3134817303","https://openalex.org/W3135185854","https://openalex.org/W3172427256","https://openalex.org/W3187922971","https://openalex.org/W3194031773","https://openalex.org/W4224248334","https://openalex.org/W4392557518","https://openalex.org/W4409636408"],"related_works":["https://openalex.org/W2591697403","https://openalex.org/W2944728705","https://openalex.org/W2904022177","https://openalex.org/W2359348847","https://openalex.org/W3011538607","https://openalex.org/W4294432981","https://openalex.org/W4321441197","https://openalex.org/W2953716828","https://openalex.org/W2033914206","https://openalex.org/W2042327336"],"abstract_inverted_index":{"In":[0,144],"recent":[1],"decades,":[2],"brain":[3,202],"tumors":[4],"have":[5],"emerged":[6],"as":[7],"a":[8,42,61],"serious":[9],"neurological":[10],"disorder":[11],"that":[12,188],"often":[13],"leads":[14],"to":[15,24,76,98,162,170,183,224],"death.":[16],"Hence,":[17],"Brain":[18],"Tumor":[19,113],"Segmentation":[20,114],"(BTS)":[21],"is":[22,64,75,136,150,167,181],"significant":[23],"enable":[25],"the":[26,94,125,145,153,171,196,201,233,236],"visualization,":[27],"classification,":[28],"and":[29,54,80,120,159,211,245,251],"delineation":[30],"of":[31,46,72,175,242],"tumor":[32,96],"regions":[33],"in":[34,66,82,141,229],"Magnetic":[35],"Resonance":[36],"Imaging":[37],"(MRI).":[38],"However,":[39],"BTS":[40,83,140],"remains":[41],"challenging":[43],"task":[44],"because":[45],"noise,":[47],"non-uniform":[48],"object":[49],"texture,":[50],"diverse":[51,197],"image":[52,164],"content":[53],"clustered":[55],"objects.":[56],"To":[57],"address":[58],"these":[59],"challenges,":[60],"novel":[62],"model":[63,135,207,238],"implemented":[65],"this":[67,73],"research.":[68],"The":[69,178,204],"key":[70],"objective":[71],"research":[74],"improve":[77,189],"segmentation":[78,100,190,228,240],"accuracy":[79],"generalization":[81,157],"by":[84],"incorporating":[85],"Switchable":[86,126,148,193,222],"Normalization":[87,149,194],"into":[88,152],"Faster":[89,128,205],"R-CNN,":[90],"which":[91,166],"effectively":[92],"captures":[93,195],"fine-grained":[95],"features":[97,187],"enhance":[99],"precision.":[101],"MRI":[102,142,230],"images":[103],"are":[104],"initially":[105],"acquired":[106],"from":[107,200],"three":[108],"online":[109],"datasets:":[110],"Dataset":[111,117,121],"1\u2014Brain":[112],"(BraTS)":[115],"2018,":[116],"2\u2014BraTS":[118],"2019,":[119],"3\u2014BraTS":[122],"2020.":[123],"Subsequently,":[124],"Normalization-based":[127],"Regions":[129],"with":[130,216],"Convolutional":[131],"Neural":[132],"Networks":[133],"(SNFRC)":[134],"proposed":[137,146,237],"for":[138,260],"improved":[139],"images.":[143,203,231],"model,":[147],"integrated":[151],"conventional":[154,255],"architecture,":[155],"enhancing":[156],"capability":[158],"reducing":[160],"overfitting":[161],"unseen":[163],"data,":[165],"essential":[168],"due":[169],"typically":[172],"limited":[173],"size":[174],"available":[176],"datasets.":[177],"network":[179],"depth":[180],"increased":[182],"obtain":[184],"discriminative":[185],"semantic":[186],"performance.":[191],"Specifically,":[192],"feature":[198],"representations":[199],"R-CNN":[206],"develops":[208],"end-to-end":[209],"training":[210,219],"effective":[212,227],"regional":[213],"proposal":[214],"generation,":[215],"an":[217,226],"enhanced":[218],"stability":[220],"using":[221],"Normalization,":[223],"perform":[225],"From":[232],"experimental":[234],"results,":[235],"attains":[239],"accuracies":[241],"99.41%,":[243],"98.12%,":[244],"96.71%":[246],"on":[247],"Datasets":[248],"1,":[249],"2,":[250],"3,":[252],"respectively,":[253],"outperforming":[254],"deep":[256],"learning":[257],"models":[258],"used":[259],"BTS.":[261]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
