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Coherence enhancing diffusion filtering based on the Phase Congruency Tensor

机译:基于相干张量的相干增强扩散滤波

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Many biomedical applications require the enhancement of coherent flow-like curvilinear structures in images. This can be accomplished in a natural way by adopting anisotropic diffusion filtering to local texture analysis by means of the structure tensor. Here we propose a contrast independent anisotropic diffusion filtering of curvilinear structures based on a novel concept: the Phase Congruency Tensor (PCT). The phase angle of the PCT determines the preferred diffusion direction and the diffusity is controlled by PCT-based vesselness measure. We show that the proposed method is largely insensitive to intensity variations along the curve, and provides successful enhancement within noisy regions. The performance of the proposed approach was evaluated by comparing it with a state-of-the-art intensity-based approach on both synthetic and real biological images.
机译:许多生物医学应用要求增强图像中相干的流状曲线结构。这可以通过结构张量将各向异性扩散滤波应用于局部纹理分析以自然方式完成。在这里,我们提出了一种基于新概念的曲线独立的,各向异性的各向异性扩散滤波:相一致张量(PCT)。 PCT的相角确定了首选的扩散方向,扩散度由基于PCT的容器度测量控制。我们表明,所提出的方法对沿曲线的强度变化不敏感,并在嘈杂的区域内提供了成功的增强效果。通过与合成和真实生物图像上基于强度的最新方法进行比较,评估了该方法的性能。

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