Fully three-dimensional image reconstruction for compton imaging using ordered subsets of conical projection data

The Compton camera has recently been recognized as a promising three-dimensional imaging modality with higher sensitivity and unlimited field-of-view. Due to computational limitations, however, it has been of a difficult problem to develop reconstruction algorithms with good. In this study, we propose efficient methods for implementing the OSEM (ordered-subsets expectation-maximization) algorithm for Compton camera reconstruction, and investigate three different schemes for grouping Compton scattered data into ordered subsets. The first is to group the data according to a pre-set order of scattering angles, the second is to group the possible combinations of detected position pairs in the scatterer and the absorber, and the third is to combine the first and second methods. According to our experimental results, all of the three grouping schemes exhibit similar performance in terms of the quantitative accuracy and computational efficiency. Our results show that the OSEM algorithm applied to the Compton camera provides an order improvement in speed of execution while retaining overall quality of the image reconstructed by the standard EM algorithm.