The veterinary B-ultrasound imaging system with constant value filter meets the requirements for near-field resolution, but has poor performance in far-field. The full detection depth is 140mm, and the small signal detection depth is 100mm. The far-field noise is relatively large, which makes it difficult to display the depth target echo signal of the decent model due to noise masking; The use of dynamic filter systems has achieved good imaging results in both near-field and far-field.

The full detection depth is ≥ 180mm, the lateral resolution is ≤ 4 mm, the axial resolution is ≤ 1 mm, the small signal detection depth is 120 mm, and the far-field noise is suppressed. For the actual detection of animal liver tissue, the near-field dorsal membrane and far-field diaphragm are clearly visible on animal B-ultrasound, the images of liver tissue are delicate, and the edges of blood vessels and soft tissues are obvious.

Designed and implemented a FIR type dynamic filter. From the images captured by the fully digital veterinary ultrasound imaging system using this dynamic filter, it can be seen that good resolution and signal-to-noise ratio have been achieved in both the far-field and near-field. The dynamic filter designed in this study can automatically select frequency components with diagnostic value in the echo signal based on the detection depth, and filter out strong echo signals with low frequency as the main component on the body surface and interference with high frequency as the main component in the far-field, thereby improving the near-field resolution and far-field signal-to-noise ratio, and improving the quality of ultrasound echo images for animal use.

The variation function of the center frequency of the dynamic filter is a linear empirical formula, which may not match the center frequency of the actual echo signal well in the actual echo signal, leading to a decrease in the sensitivity of veterinary ultrasound imaging. Further research will consider adopting a design method that automatically adjusts the dynamic filter coefficients based on the spectral characteristics of actual echo signals, in order to improve the signal-to-noise ratio and enhance the sensitivity of veterinary ultrasound images.

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