Compressed sensing for the multiplexing of large area silicon photomultiplier PET detectors: Acquisition and calibration

Objectives Potential clinical silicon photomultiplier based PET systems will consist of tens of thousands of individual sensors. Compressed sensing electronics can be used to multiplex a large number of individual readout sensors to significantly reduce the number of readout channels.

Methods Using brute force optimization method, a two level sensing matrix based on a 2-weight constant weight code C1[128:32] followed by a 3 weight constant weight code C2[32:16] was designed. These codes consists of discrete resistor elements either connected or not connected to intermediate or output signals. A PET block detector PCB and electronics were fabricated that can multiplex 128 3.2 mm x 3.2 mm solid-state photomultiplier pixels arranged into a 16 x 8 array. Signals from the detector were acquired by a custom 16 channel simultaneously sampling 12-bit 65 Msps ADC acquisition system. Each of the signals was summed to form a trigger, and the peak value for each event on each channel was captured simultaneously. For calibration, we placed a single 4 x 4 array of 3.2 mm x 3.2 mm x 20 mm LYSO crystals onto one of the populated detectors and collected a uniform flood calibration dataset using a 125μCi Ge source. We used a KNN Density clustering method to calculate the centroids of the calibration flood irradiation that were mapped through the sensing matrix and captured by the 16 ADC channels.

Results All 16 crystals were clearly segmented from the 16 dimensional output data using the new KNN-density clustering method. After correcting for the gain non-uniformities of the SiPM sensor, we measured a preliminary 23.7 +/- 1.2% FWHM energy resolution at 511 keV.

Conclusions We have successfully fabricated, performed data acquisition, developed a new calibration method, and done preliminary calibration for a compressed sensing PET detector.

Research Support This work was funded in part by a Stanford SIGF Bio-X Graduate Fellowship

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Traditional Multiplexing versus Compressed Sensing