Currently, in order to increase the speed of preparation of the ultrasound control protocol and reduce the influence of the human factor, reflector recognition (classification) systems based on artificial neural networks are being actively developed. For more efficient operation of neural networks, it is advisable to process images of reflectors in order to increase the signal-to-noise ratio of the image and its segmentation (clustering). The article proposes a segmentation method based on the construction of a binary mask that hides the glare of reflectors. The mask is created from the condition of obtaining the closest possible view of the image histogram to the Rayleigh distribution. A genetic algorithm is used to solve the problem of finding the minimum. In model experiments, the effectiveness of using this approach for segmentation of images of reflectors reconstructed from echo signals measured using antenna arrays has been demonstrated. To determine the type of reflector, a method based on the analysis of the glare amplitudes of images reconstructed using different acoustic schemes was used.
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