Brain Tumor Classification Using Deep Learning Algorithms; [Derin Ogrenme Algoritmalan ile Beyin Tiimoru Siniflandirma]

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Özet

Brain tumor classification categorizes brain tumors based on their various characteristics. It aids in determining suitable treatment strategies and predicting patient outcomes. Therefore, the objective of this study is to identify the optimal tumor classification model by utilizing various Convolutional Neural Network (CNN)-based deep learning models (including combined models) on a recently published tumor classification dataset. Furthermore, diverse image manipulation and augmentation techniques were applied and their impact on model performance was evaluated. The experimental results prove that the combined deep learning models outperform other approaches in terms of performance in multi-class brain tumor classification.

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AlanDeğerDil
dc.contributor.authorPehlivanoglu, Meltem Kurt
dc.contributor.authorEker, Ayse Gul
dc.contributor.authorInce, Ibrahim
dc.contributor.authorKarhan, Deniz
dc.contributor.authorDuru, Nevcihan
dc.date.accessioned2026-10-27T20:41:05.637091940Z
dc.date.available2026-10-27T20:41:05.637091940Z
dc.date.issued2023
dc.description.abstractBrain tumor classification categorizes brain tumors based on their various characteristics. It aids in determining suitable treatment strategies and predicting patient outcomes. Therefore, the objective of this study is to identify the optimal tumor classification model by utilizing various Convolutional Neural Network (CNN)-based deep learning models (including combined models) on a recently published tumor classification dataset. Furthermore, diverse image manipulation and augmentation techniques were applied and their impact on model performance was evaluated. The experimental results prove that the combined deep learning models outperform other approaches in terms of performance in multi-class brain tumor classification.
dc.identifier.doi10.1109/ubmk59864.2023.10286764
dc.identifier.endpage392
dc.identifier.isbn979-835034081-5
dc.identifier.scopus2-s2.0-85177560250
dc.identifier.startpage387
dc.identifier.urihttps://rdlopen.rawdatalibrary.net/r/kostu/10208
dc.language.isotr
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.relation.conference8th International Conference on Computer Science and Engineering, UBMK 2023
dc.relation.ispartofUBMK 2023 - Proceedings: 8th International Conference on Computer Science and Engineering
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectbrain tumor
dc.subjectdeep learning
dc.subjectmachine learning
dc.subjecttumor classification
dc.subject.otherClassification (of information)
dc.subject.otherConvolutional neural networks
dc.subject.otherDeep learning
dc.subject.otherLearning systems
dc.subject.otherPatient treatment
dc.subject.otherTumors
dc.subject.otherBrain tumor classifications
dc.subject.otherBrain tumors
dc.subject.otherClassification models
dc.subject.otherCombined modeling
dc.subject.otherConvolutional neural network
dc.subject.otherLearning models
dc.subject.otherMachine-learning
dc.subject.otherNetwork-based
dc.subject.otherTumor classification
dc.subject.otherBrain
dc.titleBrain Tumor Classification Using Deep Learning Algorithms; [Derin Ogrenme Algoritmalan ile Beyin Tiimoru Siniflandirma]
dc.typeConference Object
rdl.citation.scopus3
rdl.conference.date13 September 2023 through 15 September 2023
rdl.conference.placeBurdur
rdl.oa.statusclosed
rdl.source.indexSCOPUS