A novel convolutional neural network-based approach for brain tumor classification using magnetic resonance images
Yükleniyor...
Tarih
2023
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Wiley
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
Brain tumor is a disease that seriously threatens human health and can often be treated with risky surgeries. Experts detect brain tumor with high resolution magnetic resonance (MR) images. However, the expected accuracy value could not be reached in the studies carried out so far. The aim of this study is to develop a new approach for detecting brain tumor types using MR images. In the proposed approach, it is designed a CNN-based neural network from scratch. The results of the method were compared with existing networks. The proposed approach detected glioma tumors with 99.64%, meningiomas tumor with 96.53%, pituitary tumors with 98.39% and an average of 98.32% accuracy. The developed CNN based model is also compared with deep CNN models such as ResNet50, VGG19, DensetNet121 and InceptionV3, which are operated by transfer learning method. The results show that the proposed approach outperforms other deep neural networks.
Açıklama
Anahtar Kelimeler
Artificial neural network models, Brain tumor classification, Convolutional neural network, Deep learning
Kaynak
International Journal of Imaging Systems and Technology
WoS Q Değeri
Q2
Scopus Q Değeri
Q1
Cilt
33
Sayı
3
Künye
Çınar, N., Kaya, M. ve Kaya, B. (2023). A novel convolutional neural network-based approach for brain tumor classification using magnetic resonance images. International Journal of Imaging Systems and Technology, 33(3), 895-908.
