Speckle decorrelation algorithm is a method using decorrelation curves to estimate the distance between two neighbor- ing ultrasound images. In this paper, we propose a new method to obtain specific decorrelation curv...Speckle decorrelation algorithm is a method using decorrelation curves to estimate the distance between two neighbor- ing ultrasound images. In this paper, we propose a new method to obtain specific decorrelation curves for distance estimation. First, several datasets of synthetic ultrasound （US） images are obtained by scanning different scatters. Second, based on the US datasets, we compute low-order moments and the elevational decorrelation curves. Finally, low-order moments are used to classify different scattering conditions. The suitable decorrelation curves can be acquired when the scattering style has been determined. With these steps, the relationship between low order moments and the decor- relation curves is established by the scattering conditions. This relationship proves to be efficient and applicable in the experiment section. The decorrelation curves chosen according to the rela- tionship also perform well in the distance estimation test.展开更多
基金Supported by the National Basic Research Program of China(2011CB707900)
文摘Speckle decorrelation algorithm is a method using decorrelation curves to estimate the distance between two neighbor- ing ultrasound images. In this paper, we propose a new method to obtain specific decorrelation curves for distance estimation. First, several datasets of synthetic ultrasound （US） images are obtained by scanning different scatters. Second, based on the US datasets, we compute low-order moments and the elevational decorrelation curves. Finally, low-order moments are used to classify different scattering conditions. The suitable decorrelation curves can be acquired when the scattering style has been determined. With these steps, the relationship between low order moments and the decor- relation curves is established by the scattering conditions. This relationship proves to be efficient and applicable in the experiment section. The decorrelation curves chosen according to the rela- tionship also perform well in the distance estimation test.
