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Inversion elasticity reconstruction of soft tissue using split-and-merge strategy from strain map of ultrasound image sequence

机译:超声图像序列应变映射的分裂策略反转弹性重建软组织

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Progress in ultrasound elasticity imaging (UEI) shows promise as a new way for early detection of cancers by assessing elastic characteristics of soft tissue. However its diagnostic value is reduced by the inherent limitation of spatial and contrast resolution in ultrasound images. We propose a finite-element based nonlinear scheme to estimate the elasticity distribution of soft tissue. A 3D freehand ultrasound imaging system is used to deform tissue with certain contact forces at the same time as imaging. Image displacements are estimated. A split-and-merge strategy is presented for elasticity reconstruction from an image sequence. The L/sub 2/-error between the target and reconstructed Young's modulus is found to be less than 5% for a single inclusion model even with 20% noise level. This result is significantly better than previously reported work. Experimental results on a gelatine phantom are used to illustrate the properties with this method.
机译:超声弹性成像(UEI)的进展显示了通过评估软组织的弹性特性来早期检测癌症的新方法。然而,由于超声图像中的空间和对比度分辨率的固有限制,其诊断值减少。我们提出了一种基于有限元的非线性方案来估计软组织的弹性分布。 3D写手超声成像系统用于使具有某些接触力的组织与成像同时变形。估计图像位移。从图像序列呈现弹性重建的分离和合并策略。对于单个包含模型的目标和重建的杨氏模量之间的L / SUB 2 / -Error,即使具有20%的噪声水平,单个包含模型也小于5%。该结果明显优于先前报告的工作。使用该方法的明胶幻像上的实验结果用于说明该方法的性质。

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