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首页> 外文期刊>Computers in Biology and Medicine >Wavelet energy-guided level set-based active contour: a segmentation method to segment highly similar regions.
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Wavelet energy-guided level set-based active contour: a segmentation method to segment highly similar regions.

机译:基于小波能量引导的水平集的活动轮廓线:一种用于分割高度相似区域的分割方法。

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摘要

This paper introduces an approach to perform segmentation of regions in computed tomography (CT) images that exhibit intra-region intensity variations and at the same time have similar intensity distributions with surrounding/adjacent regions. In this work, we adapt a feature computed from wavelet transform called wavelet energy to represent the region information. The wavelet energy is embedded into a level set model to formulate the segmentation model called wavelet energy-guided level set-based active contour (WELSAC). The WELSAC model is evaluated using several synthetic and CT images focusing on tumour cases, which contain regions demonstrating the characteristics of intra-region intensity variations and having high similarity in intensity distributions with the adjacent regions. The obtained results show that the proposed WELSAC model is able to segment regions of interest in close correspondence with the manual delineation provided by the medical experts and to provide a solution for tumour detection.
机译:本文介绍了一种在计算机断层扫描(CT)图像中执行区域分割的方法,这些图像表现出区域内的强度变化,同时具有与周围/相邻区域相似的强度分布。在这项工作中,我们采用从小波变换计算出的称为小波能量的特征来表示区域信息。将小波能量嵌入到水平集模型中,以制定称为小波能量引导的基于水平集的活动轮廓线(WELSAC)的分割模型。使用聚焦于肿瘤病例的几个合成图像和CT图像评估WELSAC模型,这些图像包含显示区域内强度变化特征的区域,并且强度分布与相邻区域高度相似。获得的结果表明,所提出的WELSAC模型能够与医学专家提供的手动描述非常接近地分割感兴趣区域,并为肿瘤检测提供解决方案。

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