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A novel medical image enhancement method based on wavelet multi-resolution analysis

机译:一种基于小波多分辨率分析的新型医学图像增强方法

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Aimed to resolve the problem of visual effect to the medical image in clinic practice and offer more important diagnostic information for surgery, the paper using wavelet multi-level analysis theory designed a novel medical image enhancement algorithm. Firstly, the traditional wavelet transform is performed to original medical images; consequently, the wavelet transform coefficients are extracted using wavelet transformation. Secondly, coefficients are divided into two groups according to the contribution to the original medical image. The soft threshold is introduced and reprocessed to reconstruct the image information. At last, the inverse of wavelet transform (IWT) is made in order to generate the result image. The wavelet transform can render the details of feature with the scale of different separation, so the different resolutions of detail feature in the original image are enhanced. Compared with the original medical images, the results images have better results of vision effect, it can offered more accurate and detailed information to doctor, so it can be used in medical diagnose in our life. Many valuable experiments are made to validate the feasibility and efficiency.
机译:旨在解决临床实践中医学形象的视觉效应问题,为手术提供更重要的诊断信息,采用小波多级分析理论设计了一种新型医学图像增强算法。首先,传统的小波变换进行原始医学图像;因此,使用小波变换提取小波变换系数。其次,根据对原始医学图像的贡献,将系数分成两组。引入软阈值并重新加工以重建图像信息。最后,进行小波变换(IWT)的逆,以便生成结果图像。小波变换可以通过不同分离的比例呈现特征的细节,因此提高了原始图像中的详细功能的不同分辨率。与原始医学图像相比,结果图像具有更好的视觉效果的结果,它可以向医生提供更准确和详细的信息,因此它可以在我们生命中的医学诊断中使用。许多有价值的实验是为了验证可行性和效率。

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