MRI-based brain tumor detection through an explainable EfficientNetV2 and MLP-mixer attention architecture
 
Yazarlar (2)
Arş. Gör. Mustafa Yurdakul Kirikkale Üniversitesi, Türkiye
Prof. Dr. Şakir TAŞDEMİR Sinop Üniversitesi, Türkiye
Makale Türü Özgün Makale (SSCI, AHCI, SCI, SCI-Exp dergilerinde yayınlanan tam makale)
Dergi Adı Physical and Engineering Sciences in Medicine (Q2)
Dergi ISSN 2662-4729 Dergi Bilgileri (2026)
Makale Dili İngilizce Basım Tarihi 01-2026
Kabul Tarihi 18-03-2026 Yayınlanma Tarihi 07-04-2026
Cilt / Sayı / Sayfa 0 / 1 / – DOI 10.1007/s13246-026-01728-0
Makale Linki https://arxiv.org/abs/2509.06713
UAK Araştırma Alanları
Mühendislik
Özet
Brain tumors present significant health challenges and necessitate early diagnosis due to their high mortality rates. Diagnosis through Magnetic Resonance Imaging (MRI) requires specialized expertise and remains susceptible to error. Consequently, the demand for automated diagnostic systems continues to grow. In response, this study proposes a nove...
Anahtar Kelimeler
Attention | Brain tumor | Classification | EfficientNetV2 | Explainable artificial ıntelligence | Magnetic resonance ımaging | MLP-mixer
BM Sürdürülebilir Kalkınma Amaçları
Atıf Sayıları
Web of Science 2
Scopus 2
Google Scholar 7
MRI-based brain tumor detection through an explainable EfficientNetV2 and MLP-mixer attention architecture

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