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Design and implementation of a computer-aided diagnosis system for brain tumor classification

机译：脑肿瘤分类计算机辅助诊断系统的设计与实现

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Computer-aided diagnosis (CAD) systems have become very important for the medical diagnosis of brain tumors. The systems improve the diagnostic accuracy and reduce the required time. In this paper, a two-stage CAD system has been developed for automatic detection and classification of brain tumor through magnetic resonance images (MRIs). In the first stage, the system classifies brain tumor MRI into normal and abnormal images. In the second stage, the type of tumor is classified as benign (Noncancerous) or malignant (Cancerous) from the abnormal MRIs. The proposed CAD ensembles the following computational methods: MRI image segmentation by K-means clustering, feature extraction using discrete wavelet transform (DWT), feature reduction by applying principal component analysis (PCA). The two-stage classification has been conducted using a support vector machine (SVM). Performance evaluation of the proposed CAD has achieved promising results using a non-standard MRIs database.
机译：计算机辅助诊断（CAD）系统对于脑肿瘤的医学诊断已经变得非常重要。该系统提高了诊断准确性并减少了所需时间。在本文中，已经开发了一种两阶段的CAD系统，用于通过磁共振图像（MRI）自动检测和分类脑肿瘤。在第一阶段，系统将脑肿瘤MRI分为正常图像和异常图像。在第二阶段，根据MRI异常将肿瘤类型分为良性（非癌性）或恶性（癌性）。拟议的CAD集成了以下计算方法：通过K-均值聚类进行MRI图像分割，使用离散小波变换（DWT）进行特征提取，通过应用主成分分析（PCA）进行特征约简。使用支持向量机（SVM）进行了两阶段分类。使用非标准MRIs数据库对拟议的CAD进行性能评估已取得了可喜的结果。

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