What is one typical parameter for OSEM regarding subsets?

In the context of Ordered Subset Expectation Maximization (OSEM) used in Positron Emission Tomography (PET), subsets refer to the division of the total number of projection data into smaller groups that can be processed iteratively. This technique allows for improvements in image reconstruction speed and quality while maintaining reasonable computational demands.

The choice of subsets is critical, as it influences the convergence and statistical noise characteristics of the imaging process. Using subsets like 2, 4, or 8 allows for balancing the computational efficiency and image quality. With these values, the system can iteratively update the image more frequently without having to process the entire dataset at once, thus speeding up the reconstruction process while still capturing the key features of the image.

In practice, 2, 4, or 8 subsets are commonly used in various clinical systems and studies, making this choice a typical parameter for OSEM. It helps optimize the overall performance of PET imaging by enhancing the signal-to-noise ratio and facilitating faster image reconstructions while still allowing for adequate data fidelity.