Intraoperative image localization system and method in cardiovascular medicine based on big data analysis

Abstract

The invention belongs to the field of medical technology and discloses an intraoperative image localization system and a method in cardiovascular medicine based on big data analysis. The localizationsystem comprises an image acquisition module, a central processing module, an image processing module, an image extraction module, an image projection module, a cloud service module and a display module. Also disclosed is an intraoperative image localization method of cardiovascular medicine based on big data analysis. On the basis of keeping the hue value of each pixel unchanged, the image processing module enhances and corrects the color saturation value of the pixel, thereby avoiding the generation of color deviation phenomenon. The system solves the technical problem that the existing image enhancement methods are easy to produce color deviation phenomenon. The shape of ascending aorta and its root aortic sinus can be extracted by image extraction module so that the structure and shapeof aorta can be accurately visualized and the level and ability of medical imaging research to solve clinical problems can be greatly improved.

Description

technical field [0001] The invention belongs to the field of medical technology, and in particular relates to an intraoperative image positioning system and method for cardiovascular surgery based on big data analysis. Background technique [0002] At present, the existing technologies commonly used in the industry are as follows: [0003] Cardiovascular angiography is to quickly inject contrast agent into the heart cavity or blood vessel through the cardiac catheter, so that the heart and blood vessel cavity can be visualized under X-ray irradiation. The development process is photographed, and the blood flow sequence containing the contrast agent and the filling of the heart vessels can be seen from the results of the development, so as to understand the physiological and anatomical changes of the heart and blood vessels. It is a valuable method for diagnosing cardiovascular disease. However, the image acquisition in the existing intraoperative image positioning system ...

AI Technical Summary

Problems solved by technology

[0005] The image acquisition in the existing intraoperative image positioning system of cardiovascular medicine is prone to color shift, and the image is inaccurate; at the same time, the structure and shape of the visualized aorta cannot be accurately extracted, which affects the diagnosis of cardiovascular

[0006] In the prior art cloud server concentrates big data resources to process the collected images, no method of fuzzy neural network is proposed on the basis of fuzzy neural network algorithm; the importance of fuzzy rules cannot be evaluated, and the importance of input variables Can not give a response; can not make the width of the input variable of each rule to implement online real-time adaptive adjustment according to the requirements of system performance; the authenticity of the obtained image data is poor

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