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Brain MR Image Analysis using Discrete wavelet Transform with Fractal Feature Analysis

机译:基于离散小波变换和分形特征分析的脑部MR图像分析

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Magnetic resonance image analysis for detection of some neurodegenerative diseases are investigated and reported in this work. It is based on discrete wavelet transform in combination with different fractal analysis. The proposed action consists of two stages. In the first stage consists of image preprocessing which includes image enhancement, the region of extraction and skull stripping. In the second stage, the preprocessed image is converted to wavelet domain, and the following study is performed for feature extraction using fractal analysis. Finally proposed work has experimented with a publically available dataset of images having the mild cognitive impairment, Alzheimer's and healthy patient. The support vector machine based classifier has achieved the classification accuracy of 89.7 +- 0.6. This work will pave to develop a system for computer-aided diagnosis of some neurological diseases.
机译:在这项工作中研究并报道了用于检测某些神经退行性疾病的磁共振图像分析。它基于离散小波变换并结合不同的分形分析。拟议的行动包括两个阶段。第一阶段包括图像预处理,包括图像增强,提取区域和颅骨剥离。在第二阶段,将预处理后的图像转换为小波域,并使用分形分析对特征进行以下研究。最终提出的工作是对具有轻度认知障碍,阿尔茨海默氏病和健康患者的公众可用图像数据集进行了实验。基于支持向量机的分类器已达到89.7±0.6的分类精度。这项工作将为开发用于某些神经系统疾病的计算机辅助诊断的系统铺平道路。

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