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Wavelet Energy Embedded into a Level Set Method for Medical Images Segmentation in the Presence of Highly Similar Regions

机译:小波能量嵌入高度相似区域中医学图像分割的水平集方法

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This paper is motivated by present a new segmentation method that integrates a novel feature, which is able to enhance the dissimilarity between regions. This feature is integrated to formulate a new level set based active contour model, which addresses the segmentation of regions with highly similar intensities, which do not have clear boundaries between them. The power of wavelet transform is adapted to formulate the new feature, named as wavelet energy. In this formulation, the two terms that guide the contour are the wavelet energy incorporated region term and the contour smoothness term. With this formulation, the equations for evolving the contour are derived and implemented in MATLAB. This segmentation method is named Wavelet energy Embedded into a level set method. The experimental results show that the proposed method is able to segment the region of interest that have high similarity in intensities with their background.
机译:本文通过现有的一种新的分段方法,该方法集成了一种新颖特征,该方法能够增强地区之间的异化性。集成了此功能以制定基于新的基于级别的活动轮廓模型,该模型与具有高度相似强度的区域的分段地址,它们之间没有明确的边界。小波变换的力量适于制定新功能,命名为小波能量。在该制剂中,指导轮廓的两种术语是小波能量掺入的区域项和轮廓平滑度术语。利用这种配方,在MATLAB中导出和实现了用于发展轮廓的方程。该分段方法被命名为嵌入到级别设置方法中的小波能量。实验结果表明,该方法能够在其背景下分割具有高度相似性的感兴趣区域。

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