A new method of depth-of-interaction determination for continuous crystal PET detectors

For continuous crystal based PET detectors, not only the two-dimensional (2D) plane coordinates of the interaction point, but also the depth-of-interaction (DOI) of γ events could be precisely estimated by the single-end readout of the scintillation light. In this paper, we propose a novel, practical method for DOI determination for continuous crystal PET detectors. The novelties of the method include: by self-organizing map (SOM) neural network with unsupervised learning, the perpendicularly irradiated reference events in each reference position is classified into a certain number of groups, which are used for DOI decoding; using reference events obtained in oblique irradiations, the DOI decoding is calibrated. We applied the new method to our experimental data. The test results show that the SOM based DOI estimation could achieve 2.75 mm average resolution over the whole thickness (0-10mm) of the crystal. Combining the new method with the SOM based plane coordinates estimation scheme in our previous work, the high performance real-time 3D position estimation turns to be realistic.