Because the original signal is digitized accurately in the detection module, the all digital pet system can accurately extract the energy, location and time information of a single event, and the coincidence system can use the energy window screening, location exclusion and time window selection to make the coincidence judgment, obtain the coincidence event, and obtain the projection data (P = h · f). Generally, in a time window, there are two pulses whose energy is in the energy window range, and the line of crystal bar on the detector that captures two pulses passes through the field of view (FOV for short), then these two pulses are recorded as a coincidence event. There are three types of coincidence events: true coincidence event, random coincidence event and scatter coincidence event. In the following figure, a is scattering coincidence event, B is random coincidence event, and C is true coincidence event. After a period of scanning, the detector detects a large number of events from all directions, which are collected and recorded by the PET data acquisition system after being qualified and screened.
Image reconstruction needs to do a series of data processing, transforming the time and energy information of each single photon event collected by PET detector into images for doctors to see. The quality of this series of processing will directly affect the quality of the final reconstruction image, and then affect the accuracy of the doctor's diagnosis of patients, which is a crucial step in PET imaging. PET image reconstruction needs to consider all kinds of physical factors in PET imaging process, and then establish appropriate mathematical model to model the system response. In the reconstruction algorithm, the influence of data noise on the reconstruction results should be considered.
Compared with mixed modulus PET, all data processing of all digital pet can be done in software, so the data processing method of all digital pet has the flexibility of software. With the convenience of all digital pet in data processing, we can make full use of the information detected by pet, and then provide the possibility for quantitative reconstruction of pet. We hope to make full use of the advantages of all digital pet in this field to realize pet quantitative imaging. If pet quantitative imaging can be realized, it will bring a qualitative leap to the accuracy of doctors' diagnosis.
The work of image processing after obtaining the reconstructed image is as follows:
1. Research the architecture of medical image processing system based on cloud service, and realize rayplus medical image processing cloud service platform (website: www.rayplus. Top). The platform "cloud" medical image processing algorithm, using centralized, in the cloud server, users can directly through the computer or mobile device browser to complete their processing operations, without the need to build workstations or install processing software, greatly reducing costs, improving efficiency, and making medical image processing no longer limited by time and place It provides a powerful tool for telemedicine, mobile medicine and digital medicine.
Visualization and Processing Interface of RayPlus Medical Image Processing System
2. On this basis, we continue to study the system architecture of a cloud service medical imaging software platform, aiming to achieve an inclusive and open medical imaging software platform, and get a broader application scenario in clinical. At present, through the modular system data and communication design, we provide a simple algorithm access interface and software tool development package, which provides a very simplified algorithm cloud method and system for algorithm developers, so that algorithm developers can quickly cloud the local version of software. Next, we hope to continue to study more scalable, stable and secure fast cloud based methods and system architecture, analyze many algorithms and complex data, abstract data expression and processing methods, so as to be able to carry out efficient and accurate processing in a unified framework.
3. In the aspect of medical image processing algorithm development, we develop a new medical image processing algorithm or other application platform under the framework of this system in combination with specific clinical application scenarios, especially PET imaging application, and further improve and enrich rayplus cloud service medical image software platform.
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