The purpose of this study is to establish the simulation model of the gas emboli by analyzing reasons for features of gas emboli Doppler ultrasound signals. It is useful for the further classification of the solid emboli and gas emboli. First, the model of the radiation force and the drag force is used to calculate forces acting on the gas emboli. Second, the acceleration of the gas emboli is calculated in both the radial direction and the axial direction of the vessel, which is used to calculate the trajectory of the gas emboli in the vessel. Finally, the computer simulation model is established for the gas emboli. Doppler ultrasound signals of the gas emboli and the solid emboli are generated in the simulation experiment. Experimental results show that compared with the solid emboli, the gas emboli acted by the radiation force and the drag force will result in the frequency-domain broaden in the Doppler spectrogram. When the gas emboli circulate from the low speed area to the high speed one and then from the high speed area back to the low speed one, a ＂V＂ shape will be shown in the spectrogram of gas emboli signals. When the gas emboli circulate from the low speed area to the high speed one or from the high speed area to the low speed one, a diagonal shape will be shown for gas emboli signals. It is also shown that features of simulated gas emboli signals match with those of gas emboli signals sampled from clinic. All demonstrate that the simulation method of the gas emboli is reasonable.
In view of inherent speckle noise in medical images, a speckle reduction method was proposed based on an expectation-maximization （EM） framework. First, the real component of the in-phase/quadrature （I/Q） ultrasound image is extracted. Then, it is used to blindly estimate the point spread function （PSF） of the imaging system. Finally, based on the EM framework, an iterative algorithm alternating between the Wiener Filter and the anisotropic diffusion （AD） is exploited to produce despeckled images. The comparison experiment is carried out on both simulated and in vivo ultrasound images. It is shown that, with respect to the I/Q image, the proposed method averagely improves the speckle-signal-to-noise ratio （S-SNR） and the edge preservation index （β） of images by the factor of 1.94 and 7.52. Meanwhile, it averagely reduces the normalized mean-squared error （NMSE） by the factor of 3.95. The simulation and in vivo results indicates that the proposed method has a better overall performance than exited ones.
