Noise reduction method, system, electronic device and storage medium for intravascular ultrasound images

Abstract

The invention discloses a noise reduction method, system, electronic equipment and storage medium for intravascular ultrasound images. The method includes acquiring multiple frames of continuous intravascular ultrasound image signals; Preset the noise threshold value, first compare the data of each sampling point with the noise threshold, record the data greater than the noise threshold as logic 1, and record the value less than the noise threshold as logic 0. The judgment value is logically ANDed, and the real data of the sampling point is output if the operation result is 1. If it is 0, the black background is output. The comparison of each sampling point of the current frame and the noise determines the logical result and records it for the logical judgment of the next frame. , adopt the method of combining the preset noise threshold value and adjacent frame logic operation to filter out the actual noise and random noise generated by the image signal, and realize the noise reduction processing of the image.

Description

technical field [0001] The invention relates to the technical field of intravascular ultrasound, in particular to a noise reduction method system, electronic equipment and storage medium for intravascular ultrasound images. Background technique [0002] Vascular ultrasound uses a transducer to convert the excitation signal generated by the excitation source into a sound wave signal. After encountering tissue obstacles in the blood vessel, the sound wave signal is reflected back and then received by the transducer and converted back to an electrical signal. The strength of the echo waves is different, so the returned signal strengths are different. Such signals are processed by the later algorithm and finally the image is presented through the display device. The visual effect formed can be diagnosed by the doctor. disease treatment facilitates better planning. Therefore, the authenticity of the signal returned by the transducer is very important. However, in the actual oper...

AI Technical Summary

Problems solved by technology

[0009] 2. The multi-image average noise reduction method requires the image to be absolutely still, and requires multiple images. Obviously, it cannot achieve an obvious noise reduction effect for continuous dynamic images, and it will also cause serious loss of useful information;

[0010] 3. The implementation of the algorithm is too complicated. For example, the wavelet soft threshold noise reduction method requires a lot of mathematical theory, and it is difficult for an algorithm engineer without many years of experience to understand its principle and implement it;

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