Year: 2024
Type: article
Abstract: PurposeIt has been debated whether photon counting detectors (PCDs) with moderate numbers of energy windows (NE) perform better than PCDs with higher NE. A higher NE results in fewer photons in each energy window, which degrades the signal-to-noise ratio of each datum. Unlike energy-integrating detectors, PCDs add very little electronic noise to measured counts; however, there exists electronic noise on the pulse train, to which multiple energy thresholds are applied to count photons. The noise may increase the uncertainty of counts within energy windows; however, this effect has not been studied in the context of spectral imaging tasks. We aim to investigate the effect of NE on the quality of the spectral information in the presence of electronic noise.ApproachWe obtained the following three types of PCD data with various NE (= 2 to 24) and noise levels using a Monte Carlo simulation: (A) A PCD with no electronic noise; (B) realistic PCDs with electronic noise added to the pulse train; and (C) hypothetical PCDs with electronic noise added to each energy window’s output, similar to energy-integrating detectors. We evaluated the Cramér–Rao lower bound (CRLB) of estimation for the following two spectral imaging tasks: (a) water–bone material decomposition and (b) K-edge imaging.ResultsFor both the e-noise-free and realistic PCDs, the CRLB improved monotonically with increasing NE for both tasks. In contrast, a moderate NE provided the best CRLB for the hypothetical PCDs, and the optimal NE was smaller when electronic noise was larger. Adding one energy window to the minimum necessary NE for a given task gained 66.2% to 68.7% of the improvement NE=24 provided.ConclusionFor realistic PCDs, the quality of the spectral information monotonically improves with increasing NE.
Source: Journal of medical imaging
Author: Katsuyuki Taguchi
Institutions: Johns Hopkins University, Johns Hopkins Medicine
Language: English
Subfield: Biomedical Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W4402689032