Wall filtering method and system for realizing ultrasound color Doppler blood flow imaging

Abstract

The wall filtering method and system for ultrasonic color Doppler blood flow imaging provided by the present invention, the method includes: obtaining an input signal; obtaining the filter coefficient matrix of each order of the regression filter according to the data length of the input signal; The second filter coefficient matrix is ​​linearly combined to construct a new filter coefficient matrix; the input signal is filtered according to the new filter coefficient matrix to obtain an output signal. The wall filtering method and system for ultrasonic color Doppler blood flow imaging of the present invention have the advantages of smooth and monotonous frequency response, large stop band attenuation, narrow transition band, no transient response, and no loss of data points, and can simultaneously By changing the weight coefficients of the linear combination to construct a wall filter with an arbitrary cut-off frequency, a better ultrasound color Doppler blood flow imaging effect can be obtained.

Description

technical field [0001] The invention belongs to the field of ultrasonic diagnostic imaging, and relates to a wall filtering method and system for realizing ultrasonic color Doppler blood flow imaging. Background technique [0002] Ultrasound imaging has become one of the most widely used clinical diagnostic tools because of its non-invasive, real-time, convenient operation, and low price. The two main functional modes of ultrasound imaging are tissue black-and-white (B) mode and color flow (CF) mode. The B mode performs imaging according to the reflection signal intensity at different depths of the tissue. The greater the reflection signal intensity, the higher the gray value of the image. Conversely, the gray value of the image is smaller; the CF mode calculates the frequency shift of the ultrasonic signal caused by the Doppler effect, and obtains the blood flow velocity through the frequency shift and expresses it in different colors (red, blue) and depth, thereby obtainin...

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Problems solved by technology

[0010] However, traditional FIR / IIR filters are represented by sine waves of different frequencies based on different frequency components of the signal, so filters with any different cut-off frequencies can be designed, but the basic principle and filtering method of the regression filter determine that it is impossible to design any cut-off For frequency regression filters, when the data length is small, the cutoff frequency of adjacent order regression filters jumps too much, and the wall filter with the optimal cutoff frequency cannot be obtained. For example, the corresponding cutoff frequency of the first-order regression filter is 100Hz , the 2nd-order regression filter corresponds to a cutoff frequency of 200HZ, so it is difficult for the regression filter to obtain a cutoff frequency between 100 and 200HZ, which is a major defect of the regression filter

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