The correction of zero-counts is essential to enable high-quality and accurate low-dose photon counting detector CT (PCD-CT) imaging. Prior to logarithmic normalization, it is necessary to correct for zero-counts in the raw output of PCDs to prevent division-by-zero in the conventional CT reconstruction pipeline. The probability of registering a count of zero for a given detector element is significantly higher for PCDs compared with conventional detectors due to the increased spatial resolution of PCDs and the allocation of counts to multiple energy bins for spectral CT imaging applications. This concern becomes further amplified when considering low-dose PCD-CT applications, large patient imaging, and the presence of metallic structures. However, current methods to correct for zero-counts introduce CT number bias, degrade spatial resolution, or violate the conditional independence assumption. The objective of this work is to develop a zero-correction framework that effectively addresses zero-counts while minimizing bias, preserving conditional independence, and maintaining spatial resolution. Experimental validation studies are performed on a benchtop PCD-CT system to demonstrate the efficacy and generalizability of the proposed correction framework. The results of these studies indicate that the proposed zero-count correction scheme can minimize bias and preserve spatial resolution for both single-energy bin and dual-energy bin PCD-CT imaging acquisitions at low doses.
|