Maximum-Likelihood Event Parameter Estimation from Digital Waveform Capture

A preclinical Single Photon Emission Computed Tomography (SPECT) system design is presented, that will be used in rabbit myocardial perfusion and related cardiac studies. The system includes digital-waveform capture of all PMT signals, which allows for optimal maximum-likelihood estimation in the gamma-ray event parameter estimation and tomographic reconstruction processes. In a typical gamma ray camera, only the integrated signal of a gamma ray event is recorded. Here, because the entire waveform is recorded, it is possible to incorporate information from the waveform shape into the maximum-likelihood estimation. A likelihood model for incorporating waveforms in estimating event parameters (x, y, z, energy, and time) is explored. The detector, a full-size clinical SPECT camera with 61 PMTs, was retrofitted with an array of active buffers that tap into raw low-level signals before they reach the Anger-logic network. Methods for system calibration and integration are discussed, along with predictions and measurements of system performance.