What is the advantage of using Ordered Subset Expectation Maximization (OSEM) over traditional iterative reconstruction?

The advantage of using Ordered Subset Expectation Maximization (OSEM) over traditional iterative reconstruction lies in its ability to significantly reduce processing time while maintaining image quality. OSEM achieves this by dividing the data into smaller subsets and updating the image estimate more frequently throughout the iterations. This method allows for less computational load in each iteration since it processes only a portion of the data, which leads to quicker convergence to an acceptable image quality.

The shorter processing time makes OSEM particularly valuable in clinical settings where faster image reconstruction is desired to reduce patient wait times and improve workflow efficiency. In contrast, traditional iterative reconstruction methods may require more computational resources and time to achieve similar results due to processing all data simultaneously in each iteration.

This efficiency in OSEM allows for a good balance between speed and image quality, which is crucial in diagnostic imaging where timely results are essential.