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Application of Support Vector Machine Classifier for Computer Aided Diagnosis of Brain Tumor from MRI

机译:支持向量机分类器在MRI脑肿瘤计算机辅助诊断中的应用

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In this paper a computerized scheme for automatic detection of tumors in brain is examined. Diagnosis of these lesions at the early stage is a very difficult task in normal brain images. The algorithm incorporates steps for preprocessing, feature extraction and classification using brain tumor detection. This paper proposes a supervised machine learning algorithm for detection of tumor. A feature extraction methodology is used to extract the Gabor texture features of the abnormal brain tissues and normal brain tissues prior to classification. Then support vector machine classifier is applied at the end to determine whether the given input data is tumor or non tumor. The detection performance is evaluated using Receiver Operating Characteristic curves. The result shows significantly improves the classification accuracy.
机译:本文研究了一种用于自动检测脑部肿瘤的计算机化方案。在正常的脑部图像中,早期诊断这些病变是一项非常困难的任务。该算法结合了使用脑肿瘤检测进行预处理,特征提取和分类的步骤。本文提出了一种监督性的机器学习算法来检测肿瘤。特征提取方法用于在分类之前提取异常脑组织和正常脑组织的Gabor纹理特征。然后在最后应用支持向量机分类器来确定给定的输入数据是肿瘤还是非肿瘤。使用接收器工作特性曲线评估检测性能。结果表明,显着提高了分类精度。

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