Investigation of Depth of Interaction Decoding for a Continuous Crystal Detector

We present a clustering method to exact depth of interaction (DOI) information from a thick crystal version (i.e., ~8 mm) of our cMiCE small animal PET detector. This clustering method, based on the maximum-likelihood (ML) method, can effectively build look-up tables (LUT) for different DOI regions. Thus the position of interaction and DOI can be estimated simultaneously using our statistics based positioning (SBP) method. SBP is a LUT searching algorithm based on the ML method that uses 2-dimensional mean-variance LUTs of the light responses from each photomultiplier channel with respect to different gamma ray interaction locations. DETECT2000 simulated data was used to help validate our approach. 2 and 4 DOI region clustering were applied on the simulated data. The misclassification rate is about 5% for 2 DOI regions and 14% for 4 DOI regions. Using multi-DOI LUTs also improved the spatial resolution of the detector. These results show that our ML clustering method is a consistent and reliable way to characterize DOI in a continuous crystal detector without additional treatment to the crystal or additional electronic circuitry. The ability to characterize the depth dependent light response function from empirical data is a major step forward in developing practical detectors with DOI positioning capability.