A comparative study for glioma classification using deep convolutional neural networks

DOI10.3934/mbe.2021080zbMath1471.92184OpenAlexW3128418774MaRDI QIDQ1981082

Hakan Özcan, Tahsin Saygı, Hakan Sabuncuoğlu, Bülent Gürsel Emiroğlu, Ahmet Soyer, Selçuk Özdoğan

Publication date: 9 September 2021

Published in: Mathematical Biosciences and Engineering (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.3934/mbe.2021080

zbMATH Keywords

classificationmagnetic resonance imagingtransfer learninggliomaretrospective studyclinical scansdeep convolutional neural networks

Mathematics Subject Classification ID

Artificial neural networks and deep learning (68T07) Biomedical imaging and signal processing (92C55) Machine vision and scene understanding (68T45)

Uses Software

• ImageNet
• Augmentor
• SqueezeNet

Cites Work

• Neocognition: A self-organizing neural network model for a mechanism of pattern recognition unaffected by shift in position
• Convolutional neural networks for computer-aided detection or diagnosis in medical image analysis: an overview
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