Method for lowering noise of medical sonogram anisotropic diffusion

Abstract

The invention provides a method for reducing noise by anisotropic diffusion of medical ultrasonic images. First calculate the edge reliability of each pixel, and then determine the value of the diffusion parameter of each pixel; then perform anisotropic diffusion algorithm to reduce noise, that is, determine the degree of diffusion according to the gradient of the pixel and the diffusion parameter, and update the gray value of the pixel at the same time Degree value; finally calculate the non-linear correlation coefficient between the image diffusion denoising result and the image before diffusion, if the coefficient is lower than the specified value, the image denoising process ends, otherwise return to the previous step, that is, according to the new gradient of the pixel and The diffusion parameter determines the degree of diffusion, and updates the gray value of the pixel until the nonlinear correlation coefficient of two adjacent images is lower than the specified value. The invention significantly improves the adaptability of the diffusion algorithm for image noise reduction, and has wide application prospects.

Description

(1) Technical field [0001] The invention belongs to the technical field of image processing, and in particular relates to a medical ultrasonic image processing technology. (2) Background technology [0002] In medical ultrasound imaging, the speckle noise caused by superposition of coherent waves has a serious impact on ultrasound images, which reduces the ability of the ultrasound imaging system to distinguish objects, affects people's understanding of images and the detection and extraction of automatic features, and limits medical imaging. Further application of ultrasound images in clinical diagnosis. Noise reduction processing for ultrasound images is an important part of medical ultrasound image processing. Ultrasound image noise reduction algorithm should effectively suppress speckle noise while retaining image detail information useful for later analysis and diagnosis. [0003] Image noise reduction techniques are generally divided into two categories: spatial doma...

AI Technical Summary

Problems solved by technology

The method based on median filtering automatically selects the weights of each point in the filtering window and the size and shape of the window according to the local statistical characteristics of the image. The choice of is very sensitive, which limits the processing effect

The method based on wavelet transform transforms the ultrasonic image into the wavelet domain, uses wavelet thresholding to discard some coefficients, and then inversely transforms them to remove noise, but it is difficult to choose a suitable scale in this method

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