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A segmentation technique to detect the Alzheimer's disease using image processing

机译:一种使用图像处理技术检测阿尔茨海默氏病的分割技术

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Alzheimer's disease is a neurological disorder in which the death of brain cells causes memory loss and cognitive decline. A neurodegenerative type of dementia, the disease starts mild and gets progressively worse. An important area under medical research is Brain image analysis, results to detect brain diseases. The main causes for Alzheimer's diseases is low brain activity and blood flow. In general Segmentation technique is using for the medical images. One of the important component of the brain is Hippocampus. The normal behavior of human beings is depends on the functionality of Hippocampus. Manual Segmentation by a specialist on the Hippocampus takes many hours. In image processing there are various techniques available for segmentation process. In this paper a modified approach based on the watershed algorithm is used for segmenting the hippocampus region. The brain images converted into binary form using two approaches. The first approach is block mean, mask and labeling concepts and in the second approach top hat, mask and labeling concepts. However it is found that some part of the image contains holes which interrupt the segmentation process. To overcome this problem image hole filling techniques are implemented and related components are grouped into connected components. The shape analysis of hippocampus structure will result in classifying the Alzheimer's disease.
机译:阿尔茨海默氏病是一种神经系统疾病,其中脑细胞的死亡导致记忆力减退和认知能力下降。这是一种神经退行性痴呆,这种疾病从轻度开始逐渐恶化。医学研究的重要领域是脑图像分析,这是检测脑部疾病的结果。阿尔茨海默氏病的主要原因是大脑活动和血流不足。通常,分割技术用于医学图像。大脑的重要组成部分之一是海马体。人类的正常行为取决于海马的功能。由海马专家进行的手动分段需要花费多个小时。在图像处理中,有多种技术可用于分割过程。本文采用了一种基于分水岭算法的改进方法对海马区域进行分割。使用两种方法将大脑图像转换为二进制形式。第一种方法是块均值,掩膜和标签概念,第二种方法是礼帽,掩膜和标签概念。然而,发现图像的某些部分包含孔,这些孔打断了分割过程。为了克服该问题,实现了图像孔填充技术,并且将相关组件分组为连接的组件。海马结构的形状分析将导致阿尔茨海默氏病的分类。

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