{"title":"Number of energy windows for photon counting detectors: is more actually more?","authors":"Katsuyuki Taguchi","doi":"10.1117/1.JMI.11.S1.S12807","DOIUrl":null,"url":null,"abstract":"<p><strong>Purpose: </strong>It has been debated whether photon counting detectors (PCDs) with moderate numbers of energy windows ( <math> <mrow><msub><mi>N</mi> <mi>E</mi></msub> </mrow> </math> ) perform better than PCDs with higher <math> <mrow><msub><mi>N</mi> <mi>E</mi></msub> </mrow> </math> . A higher <math> <mrow><msub><mi>N</mi> <mi>E</mi></msub> </mrow> </math> 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 <math> <mrow><msub><mi>N</mi> <mi>E</mi></msub> </mrow> </math> on the quality of the spectral information in the presence of electronic noise.</p><p><strong>Approach: </strong>We obtained the following three types of PCD data with various <math> <mrow><msub><mi>N</mi> <mi>E</mi></msub> </mrow> </math> (= 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.</p><p><strong>Results: </strong>For both the e-noise-free and realistic PCDs, the CRLB improved monotonically with increasing <math> <mrow><msub><mi>N</mi> <mi>E</mi></msub> </mrow> </math> for both tasks. In contrast, a moderate <math> <mrow><msub><mi>N</mi> <mi>E</mi></msub> </mrow> </math> provided the best CRLB for the hypothetical PCDs, and the optimal <math> <mrow><msub><mi>N</mi> <mi>E</mi></msub> </mrow> </math> was smaller when electronic noise was larger. Adding one energy window to the minimum necessary <math> <mrow><msub><mi>N</mi> <mi>E</mi></msub> </mrow> </math> for a given task gained 66.2% to 68.7% of the improvement <math> <mrow><msub><mi>N</mi> <mi>E</mi></msub> <mo>=</mo> <mn>24</mn></mrow> </math> provided.</p><p><strong>Conclusion: </strong>For realistic PCDs, the quality of the spectral information monotonically improves with increasing <math> <mrow><msub><mi>N</mi> <mi>E</mi></msub> </mrow> </math> .</p>","PeriodicalId":47707,"journal":{"name":"Journal of Medical Imaging","volume":"11 Suppl 1","pages":"S12807"},"PeriodicalIF":1.9000,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11413649/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Medical Imaging","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1117/1.JMI.11.S1.S12807","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/9/20 0:00:00","PubModel":"Epub","JCR":"Q3","JCRName":"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING","Score":null,"Total":0}
引用次数: 0
Abstract
Purpose: It has been debated whether photon counting detectors (PCDs) with moderate numbers of energy windows ( ) perform better than PCDs with higher . A higher 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 on the quality of the spectral information in the presence of electronic noise.
Approach: We obtained the following three types of PCD data with various (= 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.
Results: For both the e-noise-free and realistic PCDs, the CRLB improved monotonically with increasing for both tasks. In contrast, a moderate provided the best CRLB for the hypothetical PCDs, and the optimal was smaller when electronic noise was larger. Adding one energy window to the minimum necessary for a given task gained 66.2% to 68.7% of the improvement provided.
Conclusion: For realistic PCDs, the quality of the spectral information monotonically improves with increasing .
目的:人们一直在争论,具有中等数量能量窗口(N E)的光子计数探测器(PCD)是否比具有较高 N E 的 PCD 性能更好。较高的 N E 会导致每个能量窗口中的光子数量减少,从而降低每个数据的信噪比。与能量积分探测器不同,PCD 对测量计数的电子噪声影响很小;但脉冲序列上存在电子噪声,对其应用多个能量阈值来计数光子。噪声可能会增加能量窗口内计数的不确定性;然而,在光谱成像任务中还没有研究过这种影响。我们旨在研究在存在电子噪声的情况下,N E 对光谱信息质量的影响:我们使用蒙特卡洛模拟法获得了以下三种具有不同 N E(= 2 到 24)和噪声水平的 PCD 数据:(A) 无电子噪声的 PCD;(B) 在脉冲序列中加入电子噪声的现实 PCD;(C) 在每个能量窗口输出中加入电子噪声的假设 PCD,类似于能量积分探测器。我们对以下两项光谱成像任务的估计克拉梅尔-拉奥下限(CRLB)进行了评估:(a)水骨材料分解和(b)K 边成像:对于无电子噪声和现实的 PCD,这两项任务的 CRLB 都随着 N E 的增加而单调提高。相比之下,适中的 N E 为假定 PCD 提供了最佳 CRLB,当电子噪声较大时,最佳 N E 更小。在特定任务所需的最小 N E 的基础上增加一个能量窗口,可获得 N E = 24 所带来的 66.2% 至 68.7% 的改进:结论:对于现实的 PCD,光谱信息的质量随着 N E 的增加而单调改善。
期刊介绍:
JMI covers fundamental and translational research, as well as applications, focused on medical imaging, which continue to yield physical and biomedical advancements in the early detection, diagnostics, and therapy of disease as well as in the understanding of normal. The scope of JMI includes: Imaging physics, Tomographic reconstruction algorithms (such as those in CT and MRI), Image processing and deep learning, Computer-aided diagnosis and quantitative image analysis, Visualization and modeling, Picture archiving and communications systems (PACS), Image perception and observer performance, Technology assessment, Ultrasonic imaging, Image-guided procedures, Digital pathology, Biomedical applications of biomedical imaging. JMI allows for the peer-reviewed communication and archiving of scientific developments, translational and clinical applications, reviews, and recommendations for the field.