Abstract
Monolithic PET detector design is promising for low cost, high packing fraction, intrinsic depth-of-interaction (DOI) capability as well as potentially better energy and timing resolution compared to the conventional segmented crystal-based detector design. In this work, we developed a monolithic detector with 3D positioning capability and readout channel number compression. The detector contains a monolithic LYSO crystal (size: 25 mm × 25 mm × 14 mm) coupled to a 6 × 6 SiPM array (SensL FC30035). Two 3D positioning algorithms including statistical-based positioning (SBP) and artificial neural network (ANN) were developed to estimate gamma ray interaction positions inside the crystal. To simplify detector electronics design, two readout channel number compression strategies respectively based on Anger and principal component analysis (PCA) were proposed. With Anger, the readout channel number was compressed from 36 to 12 while with PCA the readout channel number was respectively compressed to 12 (PCA12), 6 (PCA6) and 4 (PCA4) corresponding to using different number of principal component vectors. The results demonstrate that 3D positioning capability is achievable with both SBP and ANN and the positioning resolution in x, y and z direction are respectively 2.58 mm, 2.56 mm and 4.79 mm with SBP, and 2.02 mm, 2.03 mm and 3.96 mm with ANN. Both strategies can effectively reduce the readout channel number without inducing degradations in detector positioning performance. With Anger and PCA12, almost no degradation is observed in positioning performance compared to no compression. With PCA6 or PCA4, deteriorations in positioning performance in z direction are observed, especially with PCA4, although there is no significant degradation in × or y direction. We conclude that the developed monolithic detector is promising for its 3D positioning capability as well as engineering application value with compressed readout channel number in PET system designs.
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