{"id":"https://openalex.org/W7104250165","doi":"https://doi.org/10.48550/arxiv.2511.02893","title":"Optimizing the nnU-Net model for brain tumor (Glioma) segmentation Using a BraTS Sub-Saharan Africa (SSA) dataset","display_name":"Optimizing the nnU-Net model for brain tumor (Glioma) segmentation Using a BraTS Sub-Saharan Africa (SSA) dataset","publication_year":2025,"publication_date":"2025-11-04","ids":{"openalex":"https://openalex.org/W7104250165","doi":"https://doi.org/10.48550/arxiv.2511.02893"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2511.02893","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2511.02893","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2511.02893","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Kalu, Chukwuemeka Arua","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kalu, Chukwuemeka Arua","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Emegoakor, Adaobi Chiazor","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Emegoakor, Adaobi Chiazor","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Okafor, Fortune","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Okafor, Fortune","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Uchenna, Augustine Okoh","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Uchenna, Augustine Okoh","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Ukpai, Chijioke Kelvin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ukpai, Chijioke Kelvin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":null,"display_name":"Onyeugbo, Godsent Erere","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Onyeugbo, Godsent Erere","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12702","display_name":"Brain Tumor Detection and Classification","score":0.6507999897003174,"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":0.6507999897003174,"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":0.16179999709129333,"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/T10862","display_name":"AI in cancer detection","score":0.03099999949336052,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/segmentation","display_name":"Segmentation","score":0.7354000210762024},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4918000102043152},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.43860000371932983},{"id":"https://openalex.org/keywords/medical-imaging","display_name":"Medical imaging","score":0.42239999771118164},{"id":"https://openalex.org/keywords/dice","display_name":"Dice","score":0.3652999997138977},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.3643999993801117},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.33880001306533813},{"id":"https://openalex.org/keywords/s\u00f8rensen\u2013dice-coefficient","display_name":"S\u00f8rensen\u2013Dice coefficient","score":0.3246999979019165}],"concepts":[{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7354000210762024},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7317000031471252},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6428999900817871},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4918000102043152},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.43860000371932983},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.42239999771118164},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.36570000648498535},{"id":"https://openalex.org/C22029948","wikidata":"https://www.wikidata.org/wiki/Q45089","display_name":"Dice","level":2,"score":0.3652999997138977},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.3643999993801117},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.34790000319480896},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.33880001306533813},{"id":"https://openalex.org/C163892561","wikidata":"https://www.wikidata.org/wiki/Q2613728","display_name":"S\u00f8rensen\u2013Dice coefficient","level":4,"score":0.3246999979019165},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3237999975681305},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.3203999996185303},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3050999939441681},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.2971000075340271},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.28619998693466187},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.28360000252723694},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.2734000086784363},{"id":"https://openalex.org/C58693492","wikidata":"https://www.wikidata.org/wiki/Q551875","display_name":"Neuroimaging","level":2,"score":0.266400009393692}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2511.02893","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2511.02893","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2511.02893","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2511.02893","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Medical":[0],"image":[1,64],"segmentation":[2,180],"is":[3],"a":[4,75,153],"critical":[5],"achievement":[6],"in":[7,27,174],"modern":[8],"medical":[9,178],"science,":[10],"developed":[11],"over":[12],"decades":[13],"of":[14,22,45,78,113,156,167],"research.":[15],"It":[16],"allows":[17],"for":[18,158,183],"the":[19,43,70,79,93,99,106,117,131,165],"exact":[20],"delineation":[21],"anatomical":[23,40,122],"and":[24,39,49,56,146,170],"pathological":[25],"features":[26],"two-":[28],"or":[29,124],"three-dimensional":[30],"pictures":[31],"by":[32],"utilizing":[33],"notions":[34],"like":[35],"pixel":[36],"intensity,":[37],"texture,":[38],"context.":[41],"With":[42],"advent":[44],"automated":[46],"segmentation,":[47],"physicians":[48],"radiologists":[50],"may":[51],"now":[52],"concentrate":[53],"on":[54,98,109],"diagnosis":[55],"treatment":[57],"planning":[58],"while":[59],"intelligent":[60],"computers":[61],"perform":[62],"routine":[63],"processing":[65],"tasks.":[66],"This":[67],"study":[68,151],"used":[69],"BraTS":[71,80],"Sub-Saharan":[72],"Africa":[73],"dataset,":[74,133],"selected":[76],"subset":[77],"dataset":[81,112],"that":[82],"included":[83],"60":[84,101],"multimodal":[85],"MRI":[86],"cases":[87],"from":[88],"patients":[89],"with":[90,136],"glioma.":[91],"Surprisingly,":[92],"nnU":[94,137],"Net":[95],"model":[96],"trained":[97,108],"initial":[100],"instances":[102],"performed":[103],"better":[104,148],"than":[105],"network":[107],"an":[110],"offline-augmented":[111],"360":[114],"cases.":[115],"Hypothetically,":[116],"offline":[118],"augmentations":[119],"introduced":[120],"artificial":[121],"variances":[123],"intensity":[125],"distributions,":[126],"reducing":[127],"generalization.":[128],"In":[129],"contrast,":[130],"original":[132],"when":[134],"paired":[135],"Net's":[138],"robust":[139],"online":[140],"augmentation":[141,172],"procedures,":[142],"maintained":[143],"realistic":[144],"variability":[145],"produced":[147],"results.":[149],"The":[150],"achieved":[152],"Dice":[154],"score":[155],"0.84":[157],"whole":[159],"tumor":[160],"segmentation.":[161],"These":[162],"findings":[163],"highlight":[164],"significance":[166],"data":[168],"quality":[169],"proper":[171],"approaches":[173],"constructing":[175],"accurate,":[176],"generalizable":[177],"picture":[179],"models,":[181],"particularly":[182],"under-represented":[184],"locations.":[185]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2025-11-07T00:00:00"}
