基于卷积神经网络对磁共振图像进行深度学习的脑肿瘤类型分类

Hasan Ucuzal, Şeyma Yaşar, C. Colak
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引用次数: 19

摘要

利用深度学习算法开发的自动机器学习(AutoML)算法是近年来许多研究的热点。本研究旨在开发基于深度学习的免费网络软件,用于t1加权磁共振成像对脑肿瘤(胶质瘤/脑膜瘤/垂体)的诊断和检测。本软件中深度学习算法的构建使用了Python编程语言的Keras库。实验结果表明,该软件可用于三种脑肿瘤的检测和诊断。这个开发的基于网络的软件可以在http://biostatapps.inonu.edu.tr/BTSY/上公开提供英语和土耳其语版本。
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Classification of brain tumor types by deep learning with convolutional neural network on magnetic resonance images using a developed web-based interface
Automated machine learning (AutoML) algorithms developed using deep learning algorithms have been the focus of interest in many studies recently. This study aims to develop a free web-based software based on deep learning that can be utilized in the diagnosis and detection of brain tumors (Glioma/Meningioma/Pituitary) on T1-weighted magnetic resonance imaging. The Keras library, which is used in Python programming language, is utilized in the construction of the deep learning algorithm in this software. The experimental results show that this software can be used for the detection and diagnosis of three types of brain tumors. This developed web-based software can be publicly available at http://biostatapps.inonu.edu.tr/BTSY/ in both English and Turkish.
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