How to improve the resolution of ultrasonic image

In recent years, with the development of science and the popularization of digital technology, medical imaging technology, as an important auxiliary means for doctors' diagnosis and treatment, plays an increasingly important role in diagnosis, preoperative planning, treatment and postoperative monitoring. Among them, ultrasonic medical imaging technology has become an irreplaceable pillar of modern medical imaging technology with its unique advantages, and has been widely used. In the process of obtaining ultrasonic medical images, the images become blurred and distorted due to the random interference of electronic devices in ultrasonic imaging equipment and the movement of human tissues and organs; In addition, speckle noise widely exists in ultrasonic images because of the coherent characteristics of ultrasonic imaging, the uneven structure of imaging organs and tissues and the roughness of the surface. Noise seriously affects the image quality, especially conceals some details of the image, which brings difficulties to medical diagnosis and automatic recognition, and also increases the difficulty of subsequent image processing. Therefore, suppressing noise and improving image resolution are important links in ultrasonic image processing. Variational method and partial differential equation filtering technology based on regularization method are emerging ultrasonic medical image filtering technologies in recent years, which are adaptive nonlinear denoising technologies. They simplify the data in a certain way, so as to keep only those noteworthy image features, and they can remove noise while retaining image features such as edges, lines and textures, so they have attracted more and more attention. Firstly, this paper systematically analyzes the background, development history and principle of medical ultrasonic image processing, and explains the importance of studying ultrasonic image processing and the practical significance of this topic. Then, the ultrasonic image processing and anisotropic diffusion filtering methods based on global variational model are studied, and the application of global variational and anisotropic diffusion in ultrasonic image processing is emphatically studied. In this paper, the principle, advantages and disadvantages of denoising based on global variation and anisotropic diffusion algorithm are analyzed and expounded, and an improved model suitable for ultrasonic image analysis is proposed. These models and algorithms are applied to ultrasonic image denoising. Through MATLAB simulation experiments, the denoising effects of different algorithms are compared, and the results show the effectiveness of the improved algorithm.