An improved nearest neighbor method for the estimation of the gamma photon entry point in monolithic scintillator detectors for PET

F. Beekman, D. Schaart, H. T. van Dam, S. Seifert, R. Vinke, P. Dendooven, H. Lohner
{"title":"An improved nearest neighbor method for the estimation of the gamma photon entry point in monolithic scintillator detectors for PET","authors":"F. Beekman, D. Schaart, H. T. van Dam, S. Seifert, R. Vinke, P. Dendooven, H. Lohner","doi":"10.1109/NSSMIC.2010.5874368","DOIUrl":null,"url":null,"abstract":"Several improvements of the k-nearest neighbor (k-NN) method for the determination of the entry point (x, y) of a gamma photon in a monolithic scintillator PET detector have been investigated with the aim to obtain better spatial resolution and/or to enable faster detector calibration by reducing the amount of required reference data and by allowing for calibrating with a line source. These methods were tested on a dataset measured with a SiPM-array-based monolithic LYSO detector. It appears that ∼10% to ∼25% better spatial resolution can be obtained compared to the standard approach. Moreover, some of the improved methods using two orders of magnitude less reference data, yield essentially the same spatial resolution as the standard method, which reduces the time needed for calibration as well as entry point computation. Finally, line source calibration is shown to be possible with some of the methods, yielding better results than the standard method and allowing much faster and easier collection of the reference data.","PeriodicalId":13048,"journal":{"name":"IEEE Nuclear Science Symposuim & Medical Imaging Conference","volume":"6 1","pages":"3088-3092"},"PeriodicalIF":0.0000,"publicationDate":"2010-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Nuclear Science Symposuim & Medical Imaging Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NSSMIC.2010.5874368","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

Abstract

Several improvements of the k-nearest neighbor (k-NN) method for the determination of the entry point (x, y) of a gamma photon in a monolithic scintillator PET detector have been investigated with the aim to obtain better spatial resolution and/or to enable faster detector calibration by reducing the amount of required reference data and by allowing for calibrating with a line source. These methods were tested on a dataset measured with a SiPM-array-based monolithic LYSO detector. It appears that ∼10% to ∼25% better spatial resolution can be obtained compared to the standard approach. Moreover, some of the improved methods using two orders of magnitude less reference data, yield essentially the same spatial resolution as the standard method, which reduces the time needed for calibration as well as entry point computation. Finally, line source calibration is shown to be possible with some of the methods, yielding better results than the standard method and allowing much faster and easier collection of the reference data.
一种用于PET单片闪烁体探测器伽玛光子入口点估计的改进近邻法
研究了用于确定单片闪烁体PET探测器中伽马光子入口点(x, y)的k-最近邻(k-NN)方法的几个改进,目的是通过减少所需参考数据的数量和允许使用线源校准来获得更好的空间分辨率和/或实现更快的探测器校准。这些方法在基于sipm阵列的单片LYSO探测器测量的数据集上进行了测试。与标准方法相比,似乎可以获得~ 10%至~ 25%的空间分辨率。此外,一些改进的方法使用的参考数据少了两个数量级,产生的空间分辨率与标准方法基本相同,这减少了校准和入口点计算所需的时间。最后,用某些方法可以进行线源校准,产生比标准方法更好的结果,并且可以更快更容易地收集参考数据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信