Image reconstruction involves a series of data processes that convert the time and energy of each single photon event picked up by the PET detector into the image. These processes directly affect the quality of the final image and the accuracy of the doctor's diagnosis. PET image reconstruction requires a good reconstruction algorithm, accuracy system response function and data corrections. A good image reconstruction algorithm can improve the image quality by using the prior information of the image. The system response function needs to consider various physical factors to improve the image signal-to-ratio and spatial resolution. The data corrections contain random correction, scatter correction, attenuation correction, normalization correction and sometimes motion correction. Data correction can improve the accuracy of quantitative imaging.
Compared with modular mixed PET, all data processing of all-digital PET can be carried out from the hardware into the software so the data processing methods of all-digital PET are more variable. We hope to make full use of the information detected by PET and put it into reconstruction to explore the new limit of image reconstruction performance.