{"id":"https://openalex.org/W4415004072","doi":"https://doi.org/10.1109/acit65614.2025.11185838","title":"Multimodal Deep Learning Based Brain Tumor Segmentation Using CT And MRI Scans","display_name":"Multimodal Deep Learning Based Brain Tumor Segmentation Using CT And MRI Scans","publication_year":2025,"publication_date":"2025-09-17","ids":{"openalex":"https://openalex.org/W4415004072","doi":"https://doi.org/10.1109/acit65614.2025.11185838"},"language":"en","primary_location":{"id":"doi:10.1109/acit65614.2025.11185838","is_oa":false,"landing_page_url":"https://doi.org/10.1109/acit65614.2025.11185838","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 15th International Conference on Advanced Computer Information Technologies (ACIT)","raw_type":"proceedings-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/A5119925192","display_name":"Di\u011fdem Orhan","orcid":null},"institutions":[{"id":"https://openalex.org/I2799978770","display_name":"X-Fab (Germany)","ror":"https://ror.org/030bh9196","country_code":"DE","type":"company","lineage":["https://openalex.org/I2799978770"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Di\u011fdem Orhan","raw_affiliation_strings":["F&#x0131;rat University Elaz&#x0131;&#x011F;,Department of Computer Engineering,T&#x00FC;rkiye"],"affiliations":[{"raw_affiliation_string":"F&#x0131;rat University Elaz&#x0131;&#x011F;,Department of Computer Engineering,T&#x00FC;rkiye","institution_ids":["https://openalex.org/I2799978770"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5066713639","display_name":"Mehmet Kaya","orcid":"https://orcid.org/0000-0002-8116-0123"},"institutions":[{"id":"https://openalex.org/I2799978770","display_name":"X-Fab (Germany)","ror":"https://ror.org/030bh9196","country_code":"DE","type":"company","lineage":["https://openalex.org/I2799978770"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Mehmet Kaya","raw_affiliation_strings":["F&#x0131;rat University Elaz&#x0131;&#x011F;,Department of Computer Engineering,T&#x00FC;rkiye"],"affiliations":[{"raw_affiliation_string":"F&#x0131;rat University Elaz&#x0131;&#x011F;,Department of Computer Engineering,T&#x00FC;rkiye","institution_ids":["https://openalex.org/I2799978770"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5119925192"],"corresponding_institution_ids":["https://openalex.org/I2799978770"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.37251857,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"807","last_page":"810"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12702","display_name":"Brain Tumor Detection and Classification","score":0.9847999811172485,"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":0.9847999811172485,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7357000112533569},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.7239000201225281},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6412000060081482},{"id":"https://openalex.org/keywords/modality","display_name":"Modality (human\u2013computer interaction)","score":0.5167999863624573},{"id":"https://openalex.org/keywords/medical-imaging","display_name":"Medical imaging","score":0.5066999793052673},{"id":"https://openalex.org/keywords/magnetic-resonance-imaging","display_name":"Magnetic resonance imaging","score":0.48910000920295715},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.453900009393692},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.43790000677108765},{"id":"https://openalex.org/keywords/neuroimaging","display_name":"Neuroimaging","score":0.43529999256134033}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7577000260353088},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7357000112533569},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.7239000201225281},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6412000060081482},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6126999855041504},{"id":"https://openalex.org/C2780226545","wikidata":"https://www.wikidata.org/wiki/Q6888030","display_name":"Modality (human\u2013computer interaction)","level":2,"score":0.5167999863624573},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.5066999793052673},{"id":"https://openalex.org/C143409427","wikidata":"https://www.wikidata.org/wiki/Q161238","display_name":"Magnetic resonance imaging","level":2,"score":0.48910000920295715},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.453900009393692},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.43790000677108765},{"id":"https://openalex.org/C58693492","wikidata":"https://www.wikidata.org/wiki/Q551875","display_name":"Neuroimaging","level":2,"score":0.43529999256134033},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4147999882698059},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.3952000141143799},{"id":"https://openalex.org/C544519230","wikidata":"https://www.wikidata.org/wiki/Q32566","display_name":"Computed tomography","level":2,"score":0.3882000148296356},{"id":"https://openalex.org/C2779130545","wikidata":"https://www.wikidata.org/wiki/Q233309","display_name":"Brain tumor","level":2,"score":0.3813000023365021},{"id":"https://openalex.org/C136886441","wikidata":"https://www.wikidata.org/wiki/Q926129","display_name":"Normalization (sociology)","level":2,"score":0.3619999885559082},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.36160001158714294},{"id":"https://openalex.org/C78201319","wikidata":"https://www.wikidata.org/wiki/Q685727","display_name":"Grayscale","level":3,"score":0.34599998593330383},{"id":"https://openalex.org/C54170458","wikidata":"https://www.wikidata.org/wiki/Q663554","display_name":"Voxel","level":2,"score":0.3431999981403351},{"id":"https://openalex.org/C2781140086","wikidata":"https://www.wikidata.org/wiki/Q557945","display_name":"Confusion","level":2,"score":0.3262999951839447},{"id":"https://openalex.org/C116580362","wikidata":"https://www.wikidata.org/wiki/Q3878457","display_name":"Spatial normalization","level":3,"score":0.28790000081062317},{"id":"https://openalex.org/C157787499","wikidata":"https://www.wikidata.org/wiki/Q13479657","display_name":"Real-time MRI","level":3,"score":0.28780001401901245},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.2761000096797943},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.26820001006126404},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.25540000200271606}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/acit65614.2025.11185838","is_oa":false,"landing_page_url":"https://doi.org/10.1109/acit65614.2025.11185838","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 15th International Conference on Advanced Computer Information Technologies (ACIT)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W3094156580","https://openalex.org/W4220672396","https://openalex.org/W4225674602","https://openalex.org/W4293152672","https://openalex.org/W4295938041","https://openalex.org/W4389429244","https://openalex.org/W4402479051","https://openalex.org/W4402632143","https://openalex.org/W4404937753","https://openalex.org/W4406639900","https://openalex.org/W4409262410"],"related_works":[],"abstract_inverted_index":{"Brain":[0],"tumor":[1,21,152],"segmentation":[2,22],"is":[3,60],"crucial":[4],"in":[5,147,155],"medical":[6,149,159],"imaging":[7,31],"for":[8,19,39],"early":[9],"diagnosis":[10],"and":[11,28,50,68,90,113,133,143],"treatment.":[12],"This":[13],"paper":[14],"introduces":[15],"a":[16,54,137],"multimodal":[17,117,138],"architecture":[18,59],"brain":[20],"that":[23,75,130],"merges":[24],"computed":[25],"tomography":[26],"(CT)":[27],"magnetic":[29],"resonance":[30],"(MRI)":[32],"data.":[33,70],"Initially,":[34],"models":[35],"are":[36],"trained":[37],"independently":[38],"each":[40],"image":[41],"modality":[42],"by":[43],"completing":[44],"preprocessing":[45],"processes":[46],"such":[47],"as":[48],"normalization":[49],"grayscale":[51],"conversion.":[52],"Subsequently,":[53],"Convolutional":[55],"Neural":[56],"Network":[57],"(CNN)-based":[58],"designed":[61],"to":[62,123],"effectively":[63],"combine":[64],"the":[65,76,83,91,100,107,116,124,156],"processed":[66],"CT":[67,77,132],"MRI":[69,84,134],"Our":[71],"training":[72],"results":[73],"show":[74],"unimodal":[78,85,125],"model":[79,86,93,103,118,139],"achieved":[80,87,94],"92%":[81],"accuracy,":[82,89,110],"73%":[88],"multi-modal":[92],"an":[95],"outstanding":[96],"95%":[97],"accuracy.":[98],"In":[99],"evaluation":[101],"of":[102,158],"performance":[104,142],"based":[105],"on":[106],"confusion":[108],"matrix,":[109],"recall,":[111],"precision,":[112],"F1":[114],"score,":[115],"exhibited":[119],"greater":[120],"efficacy":[121],"compared":[122],"models.":[126],"These":[127],"findings":[128],"indicate":[129],"integrating":[131],"scans":[135],"into":[136],"substantially":[140],"boosts":[141],"yields":[144],"significant":[145],"benefits":[146],"important":[148],"tasks":[150],"like":[151],"segmentation,":[153],"particularly":[154],"field":[157],"imaging.":[160]},"counts_by_year":[],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2025-10-10T00:00:00"}
