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Level Set Diffusion for MRE Image Enhancement

机译:MRE图像增强的级别集扩散

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摘要

Magnetic resonance elastography (MRE) is an emerging technique for noninvasive imaging of tissue elasticity. Proprietary algorithms are used to reconstruct tissue elasticity from the images of wave propagation within soft tissue. Elasticity reconstruction suffers from interfering noise and outliers. The interference causes biased elasticity and undesired artifacts in the reconstructed elasticity map, Anisotropic geometric diffusion is able to suppress image noise while enhance inherent features. Therefore we integrate anisotropic diffusion with level set methods for numerical enhancement of MRE wave images. Performance evaluation of the proposed level set diffusion (LSD) approach was conducted on both synthetic and real MRE datasets. Experimental results confirm the effectiveness of LSD for MRE image enhancement and direct inversion.
机译:磁共振弹性术(MRE)是一种用于组织弹性的非侵入性成像的新兴技术。专有算法用于从软组织内的波传播图像重建组织弹性。弹性重建受到干扰的噪音和异常值。干扰导致重建弹性图中的偏置弹性和不期望的伪像,各向异性几何扩散能够抑制图像噪声,同时增强固有的特征。因此,我们将各向异性扩散与水平集合进行了全面的分组,以便对MRE波图像的数值增强进行了数值增强。在合成和真实的MRE数据集上进行了所提出的水平集扩散(LSD)方法的性能评估。实验结果证实了LSD对MRE图像增强和直接反演的有效性。

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