{"id":"https://openalex.org/W3045151954","doi":"https://doi.org/10.1108/ijicc-02-2020-0013","title":"Deep learning-based approach for segmentation of glioma sub-regions in MRI","display_name":"Deep learning-based approach for segmentation of glioma sub-regions in MRI","publication_year":2020,"publication_date":"2020-07-21","ids":{"openalex":"https://openalex.org/W3045151954","doi":"https://doi.org/10.1108/ijicc-02-2020-0013","mag":"3045151954"},"language":"en","primary_location":{"id":"doi:10.1108/ijicc-02-2020-0013","is_oa":false,"landing_page_url":"https://doi.org/10.1108/ijicc-02-2020-0013","pdf_url":null,"source":{"id":"https://openalex.org/S124503262","display_name":"International Journal of Intelligent Computing and Cybernetics","issn_l":"1756-378X","issn":["1756-378X","1756-3798"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319811","host_organization_name":"Emerald Publishing Limited","host_organization_lineage":["https://openalex.org/P4310319811"],"host_organization_lineage_names":["Emerald Publishing Limited"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Intelligent Computing and Cybernetics","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/A5054839030","display_name":"Jiten Chaudhary","orcid":null},"institutions":[{"id":"https://openalex.org/I70971781","display_name":"Dr. B. R. Ambedkar National Institute of Technology Jalandhar","ror":"https://ror.org/03xt0bg88","country_code":"IN","type":"education","lineage":["https://openalex.org/I70971781"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Jiten Chaudhary","raw_affiliation_strings":["Dr BR Ambedkar National Institute of Technology, Jalandhar, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dr BR Ambedkar National Institute of Technology, Jalandhar, India","institution_ids":["https://openalex.org/I70971781"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030978363","display_name":"Rajneesh Rani","orcid":"https://orcid.org/0000-0003-2104-227X"},"institutions":[{"id":"https://openalex.org/I70971781","display_name":"Dr. B. R. Ambedkar National Institute of Technology Jalandhar","ror":"https://ror.org/03xt0bg88","country_code":"IN","type":"education","lineage":["https://openalex.org/I70971781"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Rajneesh Rani","raw_affiliation_strings":["Dr BR Ambedkar National Institute of Technology, Jalandhar, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dr BR Ambedkar National Institute of Technology, Jalandhar, India","institution_ids":["https://openalex.org/I70971781"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5065781653","display_name":"Aman Kamboj","orcid":"https://orcid.org/0000-0002-2229-0454"},"institutions":[{"id":"https://openalex.org/I70971781","display_name":"Dr. B. R. Ambedkar National Institute of Technology Jalandhar","ror":"https://ror.org/03xt0bg88","country_code":"IN","type":"education","lineage":["https://openalex.org/I70971781"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Aman Kamboj","raw_affiliation_strings":["Dr BR Ambedkar National Institute of Technology, Jalandhar, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dr BR Ambedkar National Institute of Technology, Jalandhar, India","institution_ids":["https://openalex.org/I70971781"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I70971781"],"apc_list":null,"apc_paid":null,"fwci":0.4598,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.64452867,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"13","issue":"4","first_page":"389","last_page":"406"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12702","display_name":"Brain Tumor Detection and Classification","score":1.0,"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":1.0,"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":0.9987000226974487,"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":0.9975000023841858,"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/computer-science","display_name":"Computer science","score":0.832461953163147},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.7611234188079834},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6889551877975464},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6280307173728943},{"id":"https://openalex.org/keywords/normalization","display_name":"Normalization (sociology)","score":0.5247205495834351},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.46391621232032776},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.45613840222358704},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.45049795508384705},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.44652700424194336},{"id":"https://openalex.org/keywords/magnetic-resonance-imaging","display_name":"Magnetic resonance imaging","score":0.44145432114601135},{"id":"https://openalex.org/keywords/glioma","display_name":"Glioma","score":0.4326024055480957},{"id":"https://openalex.org/keywords/radiology","display_name":"Radiology","score":0.13573157787322998},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.10084521770477295}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.832461953163147},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7611234188079834},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6889551877975464},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6280307173728943},{"id":"https://openalex.org/C136886441","wikidata":"https://www.wikidata.org/wiki/Q926129","display_name":"Normalization (sociology)","level":2,"score":0.5247205495834351},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.46391621232032776},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.45613840222358704},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.45049795508384705},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.44652700424194336},{"id":"https://openalex.org/C143409427","wikidata":"https://www.wikidata.org/wiki/Q161238","display_name":"Magnetic resonance imaging","level":2,"score":0.44145432114601135},{"id":"https://openalex.org/C2778227246","wikidata":"https://www.wikidata.org/wiki/Q1365309","display_name":"Glioma","level":2,"score":0.4326024055480957},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.13573157787322998},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.10084521770477295},{"id":"https://openalex.org/C502942594","wikidata":"https://www.wikidata.org/wiki/Q3421914","display_name":"Cancer research","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"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},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1108/ijicc-02-2020-0013","is_oa":false,"landing_page_url":"https://doi.org/10.1108/ijicc-02-2020-0013","pdf_url":null,"source":{"id":"https://openalex.org/S124503262","display_name":"International Journal of Intelligent Computing and Cybernetics","issn_l":"1756-378X","issn":["1756-378X","1756-3798"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319811","host_organization_name":"Emerald Publishing Limited","host_organization_lineage":["https://openalex.org/P4310319811"],"host_organization_lineage_names":["Emerald Publishing Limited"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Intelligent Computing and Cybernetics","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W1641498739","https://openalex.org/W1797360365","https://openalex.org/W1815337875","https://openalex.org/W1884191083","https://openalex.org/W1901129140","https://openalex.org/W1910109443","https://openalex.org/W2301358467","https://openalex.org/W2310992461","https://openalex.org/W2477630714","https://openalex.org/W2512906422","https://openalex.org/W2529926598","https://openalex.org/W2566689671","https://openalex.org/W2587828787","https://openalex.org/W2595668780","https://openalex.org/W2597573836","https://openalex.org/W2605503882","https://openalex.org/W2605717159","https://openalex.org/W2613456556","https://openalex.org/W2788491273","https://openalex.org/W2884065486","https://openalex.org/W2891118631","https://openalex.org/W3006341025"],"related_works":["https://openalex.org/W2790662084","https://openalex.org/W3104734424","https://openalex.org/W4226289457","https://openalex.org/W2016839265","https://openalex.org/W2954384599","https://openalex.org/W1991269640","https://openalex.org/W3209779739","https://openalex.org/W4288040045","https://openalex.org/W2960184797","https://openalex.org/W4285827401"],"abstract_inverted_index":{"Purpose":[0],"Brain":[1],"tumor":[2,36,70,89,125],"is":[3,40,48,109,135,165,188,223],"one":[4],"of":[5,18,30,35,45,123,161,192,215,239,265],"the":[6,16,26,31,69,79,104,128,144,146,162,174,212,216,227,244,249,263,270,281],"most":[7],"dangerous":[8],"and":[9,24,51,94,153,187,235,258],"life-threatening":[10],"disease.":[11],"In":[12,76],"order":[13],"to":[14,53,59,210,226,243,251,279],"decide":[15],"type":[17],"tumor,":[19],"devising":[20],"a":[21,61,82,198,236],"treatment":[22],"plan":[23],"estimating":[25],"overall":[27],"survival":[28],"time":[29],"patient,":[32],"accurate":[33],"segmentation":[34,47,191],"region":[37,71],"from":[38,72],"images":[39,257],"extremely":[41],"important.":[42],"The":[43,106,118,132,158,177,203,220,230],"process":[44],"manual":[46],"very":[49,169],"time-consuming":[50],"prone":[52],"errors;":[54],"therefore,":[55],"this":[56,77],"paper":[57],"aims":[58],"provide":[60],"deep":[62,83],"learning":[63],"based":[64],"method,":[65],"that":[66,180],"automatically":[67],"segment":[68],"MR":[73],"images.":[74,105,117,130],"Design/methodology/approach":[75],"paper,":[78],"authors":[80,147],"propose":[81],"neural":[84],"network":[85,250,271],"for":[86,103,190],"automatic":[87],"brain":[88,124],"(Glioma)":[90],"segmentation.":[91],"Intensity":[92],"normalization":[93],"data":[95],"augmentation":[96],"have":[97,148],"been":[98,273],"incorporated":[99],"as":[100],"pre-processing":[101],"steps":[102],"proposed":[107,133,163,181,221],"model":[108,119,134,164,172,182,204,222,231],"trained":[110],"on":[111,137],"multichannel":[112],"magnetic":[113],"resonance":[114],"imaging":[115],"(MRI)":[116],"outputs":[120],"high-resolution":[121],"segmentations":[122],"regions":[126,194],"in":[127,173,195,241],"input":[129],"Findings":[131],"evaluated":[136],"benchmark":[138],"BRATS":[139],"2013":[140],"dataset.":[141],"To":[142],"evaluate":[143],"performance,":[145],"used":[149,207],"Dice":[150],"score,":[151],"sensitivity":[152],"positive":[154],"predictive":[155],"value":[156],"(PPV).":[157],"superior":[159,260],"performance":[160],"validated":[166],"by":[167,208,269],"training":[168],"popular":[170],"UNet":[171,228,245],"similar":[175],"conditions.":[176],"results":[178,186],"indicate":[179],"has":[183,232,272],"obtained":[184],"promising":[185],"effective":[189],"Glioma":[193],"MRI":[196],"at":[197],"clinical":[199],"level.":[200],"Practical":[201],"implications":[202],"can":[205],"be":[206],"doctors":[209],"identify":[211],"exact":[213],"location":[214],"tumorous":[217],"region.":[218],"Originality/value":[219],"an":[224],"improvement":[225],"model.":[229,246],"fewer":[233,256],"layers":[234],"smaller":[237],"number":[238],"parameters":[240],"comparison":[242],"This":[247],"helps":[248],"train":[252],"over":[253],"databases":[254],"with":[255,275],"gives":[259],"results.":[261],"Moreover,":[262],"information":[264],"bottleneck":[266],"feature":[267,282],"learned":[268],"fused":[274],"skip":[276],"connection":[277],"path":[278],"enrich":[280],"map.":[283]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":3}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
