{"id":"https://openalex.org/W4406321820","doi":"https://doi.org/10.1109/access.2025.3528654","title":"An Attention-Based Residual U-Net for Tumour Segmentation Using Multi-Modal MRI Brain Images","display_name":"An Attention-Based Residual U-Net for Tumour Segmentation Using Multi-Modal MRI Brain Images","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4406321820","doi":"https://doi.org/10.1109/access.2025.3528654"},"language":"en","primary_location":{"id":"doi:10.1109/access.2025.3528654","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3528654","pdf_url":null,"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://doi.org/10.1109/access.2025.3528654","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5046815946","display_name":"Najme Zehra Naqvi","orcid":"https://orcid.org/0000-0002-2312-0342"},"institutions":[{"id":"https://openalex.org/I4210143260","display_name":"Indira Gandhi Delhi Technical University for Women","ror":"https://ror.org/057c5p638","country_code":"IN","type":"education","lineage":["https://openalex.org/I4210143260"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Najme Zehra Naqvi","raw_affiliation_strings":["Department of Computer Science and Engineering, Indira Gandhi Delhi Technical University for Women, New Delhi, India","Department of Computer Science and Engineering, Indira Gandhi Delhi Technical University for Women, Delhi, India"],"raw_orcid":"https://orcid.org/0000-0002-2312-0342","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Indira Gandhi Delhi Technical University for Women, New Delhi, India","institution_ids":["https://openalex.org/I4210143260"]},{"raw_affiliation_string":"Department of Computer Science and Engineering, Indira Gandhi Delhi Technical University for Women, Delhi, India","institution_ids":["https://openalex.org/I4210143260"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5028500039","display_name":"K. R. Seeja","orcid":null},"institutions":[{"id":"https://openalex.org/I4210143260","display_name":"Indira Gandhi Delhi Technical University for Women","ror":"https://ror.org/057c5p638","country_code":"IN","type":"education","lineage":["https://openalex.org/I4210143260"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"K. R. Seeja","raw_affiliation_strings":["Department of Computer Science and Engineering, Indira Gandhi Delhi Technical University for Women, New Delhi, India","Department of Computer Science and Engineering, Indira Gandhi Delhi Technical University for Women, Delhi, India"],"raw_orcid":"https://orcid.org/0000-0001-6618-6758","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Indira Gandhi Delhi Technical University for Women, New Delhi, India","institution_ids":["https://openalex.org/I4210143260"]},{"raw_affiliation_string":"Department of Computer Science and Engineering, Indira Gandhi Delhi Technical University for Women, Delhi, India","institution_ids":["https://openalex.org/I4210143260"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210143260"],"apc_list":{"value":2075,"currency":"USD","value_usd":2075},"apc_paid":{"value":2075,"currency":"USD","value_usd":2075},"fwci":4.4699,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.94552934,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"13","issue":null,"first_page":"10240","last_page":"10251"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12702","display_name":"Brain Tumor Detection and Classification","score":0.98580002784729,"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":0.98580002784729,"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.972100019454956,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9067999720573425,"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/residual","display_name":"Residual","score":0.7061981558799744},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6724295616149902},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6375157833099365},{"id":"https://openalex.org/keywords/modal","display_name":"Modal","score":0.6013109683990479},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.5678507089614868},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5622168779373169},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.48040297627449036},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.41904211044311523},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.17336905002593994},{"id":"https://openalex.org/keywords/materials-science","display_name":"Materials science","score":0.11271676421165466}],"concepts":[{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.7061981558799744},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6724295616149902},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6375157833099365},{"id":"https://openalex.org/C71139939","wikidata":"https://www.wikidata.org/wiki/Q910194","display_name":"Modal","level":2,"score":0.6013109683990479},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5678507089614868},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5622168779373169},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.48040297627449036},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.41904211044311523},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.17336905002593994},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.11271676421165466},{"id":"https://openalex.org/C188027245","wikidata":"https://www.wikidata.org/wiki/Q750446","display_name":"Polymer chemistry","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2025.3528654","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3528654","pdf_url":null,"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:bc4f33c906ac4f5fb395649757800ae9","is_oa":true,"landing_page_url":"https://doaj.org/article/bc4f33c906ac4f5fb395649757800ae9","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"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 13, Pp 10240-10251 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2025.3528654","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3528654","pdf_url":null,"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":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":51,"referenced_works":["https://openalex.org/W1624148257","https://openalex.org/W1641498739","https://openalex.org/W1901129140","https://openalex.org/W1970203323","https://openalex.org/W2090856639","https://openalex.org/W2153169644","https://openalex.org/W2744574265","https://openalex.org/W2751069891","https://openalex.org/W2752782242","https://openalex.org/W2766356798","https://openalex.org/W2797000728","https://openalex.org/W2913720416","https://openalex.org/W2914617358","https://openalex.org/W2921595773","https://openalex.org/W2963276418","https://openalex.org/W2964980777","https://openalex.org/W2988529604","https://openalex.org/W2994050370","https://openalex.org/W3000903946","https://openalex.org/W3013480351","https://openalex.org/W3014164192","https://openalex.org/W3015596228","https://openalex.org/W3022950738","https://openalex.org/W3026947018","https://openalex.org/W3028279406","https://openalex.org/W3036182153","https://openalex.org/W3091362271","https://openalex.org/W3094156580","https://openalex.org/W3114333203","https://openalex.org/W3134696621","https://openalex.org/W3201430889","https://openalex.org/W4221095777","https://openalex.org/W4224248334","https://openalex.org/W4226478598","https://openalex.org/W4281640569","https://openalex.org/W4281777492","https://openalex.org/W4284973149","https://openalex.org/W4287225447","https://openalex.org/W4291511624","https://openalex.org/W4292405814","https://openalex.org/W4312501527","https://openalex.org/W4382138563","https://openalex.org/W4383751079","https://openalex.org/W4385701057","https://openalex.org/W4388814369","https://openalex.org/W6622244052","https://openalex.org/W6687044894","https://openalex.org/W6714871008","https://openalex.org/W6753038380","https://openalex.org/W6755891590","https://openalex.org/W6790891933"],"related_works":["https://openalex.org/W2560215812","https://openalex.org/W2949601986","https://openalex.org/W2788972299","https://openalex.org/W2521347458","https://openalex.org/W2498789492","https://openalex.org/W2729981612","https://openalex.org/W4233449973","https://openalex.org/W2925692864","https://openalex.org/W3209312100","https://openalex.org/W1522196789"],"abstract_inverted_index":{"Detecting":[0],"brain":[1,9,27,36,215],"tumours":[2,28],"is":[3,29,88,192],"challenging":[4],"due":[5],"to":[6,51,93,113,151,165],"the":[7,32,40,53,98,122,149,163,182,209],"complex":[8],"anatomy":[10],"and":[11,18,25,62,115,132,135,145,159,170,185,199,233,242,247,257,266],"wide":[12],"range":[13],"of":[14,43,174,189,230],"tumour":[15,33,44,216],"sizes,":[16],"shapes,":[17],"locations.":[19],"A":[20],"crucial":[21],"stage":[22],"in":[23,97],"diagnosing":[24],"treating":[26],"automatically":[30],"segmenting":[31,81],"area":[34],"from":[35,121,181],"MRI.":[37],"It":[38],"involves":[39],"precise":[41],"delineation":[42],"boundaries":[45],"within":[46],"MRI":[47,214],"scans,":[48],"which":[49,177],"helps":[50],"understand":[52],"tumour\u2019s":[54],"extent,":[55],"monitor":[56],"its":[57,95],"growth,":[58],"plan":[59],"treatment":[60,64],"strategies,":[61],"assess":[63],"response":[65],"over":[66],"time.":[67],"Hence,":[68],"this":[69],"research":[70],"proposes":[71],"a":[72,130,171],"novel":[73],"automated":[74],"deep-learning":[75],"approach":[76],"based":[77],"on":[78,194,204,219],"U-Net":[79,86],"for":[80,235,248,259],"Glioma":[82],"tumours.":[83],"The":[84,101,125,138,157,187,202],"basic":[85],"model":[87,150,164,191],"enhanced":[89],"with":[90],"several":[91],"components":[92],"improve":[94],"performance":[96,188,218],"proposed":[99,126,190,210],"model.":[100],"U-Net\u2019s":[102,127],"encoder":[103,183],"has":[104],"an":[105],"improved":[106],"MCA":[107],"(Multi-scale":[108],"Context":[109],"Attention)":[110],"module":[111,134,161,184],"designed":[112],"extract":[114],"collect":[116],"rich":[117],"spatial":[118,175],"contextual":[119],"information":[120,154],"input":[123],"image.":[124],"decoder":[128],"uses":[129],"Squeeze":[131,158],"Excitation":[133,160],"residual":[136,139],"blocks.":[137],"blocks":[140],"help":[141],"reduce":[142],"network":[143],"degradation":[144],"gradient":[146],"disappearance,":[147],"enabling":[148],"retain":[152],"important":[153],"during":[155],"decoding.":[156],"allows":[162],"retrieve":[166],"high-level":[167],"semantic":[168],"properties":[169],"high":[172],"level":[173],"context,":[176],"have":[178],"been":[179],"collected":[180],"IMCA-Block.":[186],"evaluated":[193],"two":[195],"datasets":[196,206],"BraTS":[197,200,224,249],"2020":[198,225],"2018.":[201],"experiments":[203],"both":[205],"demonstrate":[207],"that":[208],"framework":[211],"enhances":[212],"multi-modal":[213],"segmentation":[217],"all":[220],"metrics":[221],"evaluated.":[222],"For":[223],"it":[226,251],"achieved":[227,252],"Dice":[228,253],"Coefficient":[229,254],"0.9978,":[231],"0.9378":[232],"0.9478":[234],"WT":[236,260],"(Whole":[237,261],"tumour),":[238,262],"TC":[239,263],"(Tumour":[240,264],"core),":[241,265],"ET":[243,267],"(Enhancing":[244,268],"Tumour)":[245,269],"respectively":[246],"2018":[250],"98.32,":[255],"93.32":[256],"92.32":[258],"respectively.":[270]},"counts_by_year":[{"year":2026,"cited_by_count":6},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":1}],"updated_date":"2026-08-26T07:47:46.906454","created_date":"2025-10-10T00:00:00"}