The Construction Of Shifang City People’s Hospital Medical Image 3D Visualization System

In the information era of big data, standardization and digitization of medical imaging has become an inevitable trend, Medical Imaging Information Systems(PACS) has become an important tool for doctors to medical imaging analysis and processing of information and then give diagnostic information and building digital hospital The basic elements. Massive PACS system PACS medical image data so that a core component of the system image processing module is particularly important to study and implement high-performance image processing module can enhance the effect of PACS image processing system, improve work efficiency and improve medical diagnosis doctor level, To contribute to the building of hospital information. At the same time domestic and foreign experts have been attached great importance to the medical image image processing technology, so the PACS system image processing technology research and achieve greater practical significance and academic value.This paper studies and implements the PACS system image processing module, including traditional images and DICOM image processing. Firstly, introduces the PACS system, used in traditional and digital image processing technology standard DICOM PACS system detailed format and interpretation methods, and then completed the two functional modules on the basis of: 1) Based on GDI + conventional image processing module, image sharpening, change brightness, contrast, image anti-color, pseudo-color, insert an object, selection operations, geometry and measurement, and transform using the command mode to achieve the above action of undo and redo functions, while improving the electoral district judge algorithm to improve In constituencies sharpening, anti-color image processing operations, such as speed; 2) Leadtools of DICOM-based image processing, including DICOM image zoom, window width and position adjustment, anti-color images, image synthesis, and three-dimensional reconstruction and other functions. By running in the actual test PACS system, the results show that the proposed image processing module implemented with high operating efficiency and good open scalability.