Determination of Radiation Delivery Parameters of Medical Linear Accelerators using Data Analytics Pipeline

H. Zubair, Yi-Fei Tan, A. Basaif, A. Oresegun, H. Zin, David Bradley, H. Azhar, Abdul Rashid
{"title":"Determination of Radiation Delivery Parameters of Medical Linear Accelerators using Data Analytics Pipeline","authors":"H. Zubair, Yi-Fei Tan, A. Basaif, A. Oresegun, H. Zin, David Bradley, H. Azhar, Abdul Rashid","doi":"10.1109/IECBES54088.2022.10079318","DOIUrl":null,"url":null,"abstract":"Radiotherapy treatments involve the delivery of sharp radiation pulses of 2 to 4 microseconds duration over typical total periods of 30 to 300 seconds at a rate of up to 400 pulses per second. Recent developments in optical fiber-based radioluminescence/scintillator systems offer radiation-sensing capabilities that capture signals from individual pulses. Each of these signals has unique characteristics which provide insights into the parameters of radiation delivery. Current data acquisition methods commonly rely on hardware-based charge integration methods for radiation dose calculations and have limited utilization of the acquired data for further insights or applications. In this paper, a data analytics pipeline for the extraction and processing of data from a Ge-doped real-time dosimetry system is presented. The data, as obtained for an Elekta Synergy radiotherapy system, is then analyzed for dose distribution, dose-rates determination, and signal clustering. The gathering and processing of such time-resolved data would enable applications such as fault analysis, auto-calibration, and equipment fault prediction in medical radiation facilities in addition to enhancing the routine QA process.","PeriodicalId":146681,"journal":{"name":"2022 IEEE-EMBS Conference on Biomedical Engineering and Sciences (IECBES)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE-EMBS Conference on Biomedical Engineering and Sciences (IECBES)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IECBES54088.2022.10079318","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Radiotherapy treatments involve the delivery of sharp radiation pulses of 2 to 4 microseconds duration over typical total periods of 30 to 300 seconds at a rate of up to 400 pulses per second. Recent developments in optical fiber-based radioluminescence/scintillator systems offer radiation-sensing capabilities that capture signals from individual pulses. Each of these signals has unique characteristics which provide insights into the parameters of radiation delivery. Current data acquisition methods commonly rely on hardware-based charge integration methods for radiation dose calculations and have limited utilization of the acquired data for further insights or applications. In this paper, a data analytics pipeline for the extraction and processing of data from a Ge-doped real-time dosimetry system is presented. The data, as obtained for an Elekta Synergy radiotherapy system, is then analyzed for dose distribution, dose-rates determination, and signal clustering. The gathering and processing of such time-resolved data would enable applications such as fault analysis, auto-calibration, and equipment fault prediction in medical radiation facilities in addition to enhancing the routine QA process.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
用数据分析管道测定医用直线加速器的辐射输送参数
放射治疗包括在30至300秒的典型总周期内以每秒高达400个脉冲的速率输送持续时间为2至4微秒的尖锐辐射脉冲。基于光纤的辐射发光/闪烁体系统的最新发展提供了从单个脉冲捕获信号的辐射传感能力。这些信号中的每一个都有独特的特征,可以深入了解辐射传递的参数。目前的数据采集方法通常依赖于基于硬件的电荷集成方法进行辐射剂量计算,并且对获取的数据的进一步分析或应用的利用有限。本文提出了一种数据分析管道,用于从掺锗实时剂量测定系统中提取和处理数据。然后对Elekta Synergy放射治疗系统获得的数据进行剂量分布、剂量率确定和信号聚类分析。收集和处理这些时间分辨的数据,除了加强常规的质量保证程序外,还可以在医疗辐射设施中进行故障分析、自动校准和设备故障预测等应用。
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 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Functional Connectivity Based Classification for Autism Spectrum Disorder Using Spearman’s Rank Correlation Vector-Quantized Zero-Delay Deep Autoencoders for the Compression of Electrical Stimulation Patterns of Cochlear Implants using STOI Depression Detection on Malay Dialects Using GPT-3 Mechanical Noise Affects Rambling and Trembling Trajectories During Quiet Standing Effect Of Shoe Cushioning Hardness to Running Biomechanics
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1