Yang C, Zannoni EM, Meng LJ. Joint estimation of interaction position and energy deposition in semiconductor SPECT imaging sensors using fully connected neural network.
Phys Med Biol 2023;
68:10.1088/1361-6560/aca740. [PMID:
36595331 PMCID:
PMC10329845 DOI:
10.1088/1361-6560/aca740]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2022] [Accepted: 11/29/2022] [Indexed: 12/02/2022]
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.
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