Detection of Brain Tumor Using Image Processing

D. Suresha, N. Jagadisha, H. Shrisha, K. Kaushik
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引用次数: 17

Abstract

Brain tumor is an accumulation of anomalous tissue in the brain. Tumors are primarily classified into malignant and benign when they develop. It can be life threatening hence it is important to recognize and identify the presence of tumors in brain image. This paper proposes a system to decide whether the brain has tumor or is it tumor-free from the MR image using combined technique of K-Means and support vector machine. In the first stage the input image is converted to grey scale using binary thresholding and the spots are detected. The recognized spots are represented in terms of their intensities to distinguish between the normal and tumor brain. The set of feature extracted are later characterized by using K-Means algorithm, then the tumor recognition is done using support vector machine.
利用图像处理技术检测脑肿瘤
脑肿瘤是脑内异常组织的堆积。肿瘤在发生时主要分为恶性和良性。它可能危及生命,因此在脑图像中识别和识别肿瘤的存在是很重要的。本文提出了一种基于k -均值和支持向量机相结合的脑磁共振图像肿瘤诊断系统。在第一阶段使用二值阈值将输入图像转换为灰度并检测斑点。识别的斑点以其强度表示,以区分正常和肿瘤脑。对提取的特征集使用K-Means算法进行特征化,然后使用支持向量机进行肿瘤识别。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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