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Wavelet transform in biomedical image segmentation and classification

机译:小波变换在生物医学图像分割与分类中的应用

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The contribution is devoted to the study of image segmentation and texture analysis to find image features invariant to image components rotation and translation. The main part of the paper presents the principle of Radon transform and its use in combination with the wavelet transform to find features minimizing their variance due to image components rotation. Proposed methods have been verified for simulated structures and then used for analysis of biomedical images including magnetic resonance images of the brain and orthodontic images. The goal of image processing included in all cases (i) segmentation of selected biomedical objects and (ii) detection of their features.
机译:该贡献致力于图像分割和纹理分析的研究,以发现不变于图像分量旋转和平移的图像特征。本文的主要部分介绍了Radon变换的原理及其与小波变换的结合使用,以找到使图像分量旋转引起的方差最小的特征。已经针对模拟结构验证了所提出的方法,然后将其用于生物医学图像的分析,包括大脑的磁共振图像和正畸图像。在所有情况下,图像处理的目标都包括(i)分割选定的生物医学对象和(ii)检测其特征。

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