Joint estimation of interaction position and energy deposition in semiconductor SPECT imaging sensors using fully connected neural network

Abstract

Objective. Pixelated semiconductor detectors such as CdTe and CZT sensors suffer spatial resolution and spectral performance degradation induced by charge-sharing effects. It is critical to enhance the detector property through recovering the energy-deposition and position estimation. Approach. In this work, we proposed a fully-connected-neural-network-based charge-sharing reconstruction algorithm to correct the charge-loss and estimate the sub-pixel position for every multi-pixel charge-sharing event. Main results. Evident energy resolution improvement can be observed by comparing the spectrum produced by a simple charge-sharing addition method and the proposed energy correction methods. We also demonstrate that sub-pixel resolution can be achieved in projections obtained with a small pinhole collimator and an innovative micro-ring collimator. Significance. These achievements are crucial for multiple-tracer SPECT imaging applications, and for other semiconductor detector-based imaging modalities.