利用自适应窗口空间方向对比算法对透射和反射模式下的激光斑点对比成像进行比较研究

IF 4.9 2区 医学 Q1 ENGINEERING, BIOMEDICAL Biomedical Signal Processing and Control Pub Date : 2024-10-28 DOI:10.1016/j.bspc.2024.107091
Guang Han , De Li , Jixin Yuan , Jie Lu , Jun Zhang , Huiquan Wang , Ruijuan Chen , Yifan Wu
{"title":"利用自适应窗口空间方向对比算法对透射和反射模式下的激光斑点对比成像进行比较研究","authors":"Guang Han ,&nbsp;De Li ,&nbsp;Jixin Yuan ,&nbsp;Jie Lu ,&nbsp;Jun Zhang ,&nbsp;Huiquan Wang ,&nbsp;Ruijuan Chen ,&nbsp;Yifan Wu","doi":"10.1016/j.bspc.2024.107091","DOIUrl":null,"url":null,"abstract":"<div><div>Blood flow visualization is of paramount importance in diagnosing and treating vascular diseases. Laser speckle contrast imaging (LSCI) is a widely utilized technique for visualizing blood flow. However, Reflect-laser speckle contrast imaging (R-LSCI) systems are limited in their imaging depth and primarily suitable for shallow blood flow imaging. In this study, we conducted a comparative analysis of Transmissive-laser speckle contrast imaging (T-LSCI) and R-LSCI using four spatial domain imaging methods: spatial contrast (sK), adaptive window contrast (awK), space-directional contrast (sdK), and adaptive window space direction contrast (awsdK), for deep blood flow imaging. Experimental results show that T-LSCI is superior to R-LSCI in imaging deep blood flow within a certain thickness of tissue. T-LSCI can be used for continuous non-invasive blood flow monitoring. Particularly, the utilization of the awsdK method in T-LSCI substantially improves the visualization of deep blood flow and enhances the ability to monitor blood flow variations.</div></div>","PeriodicalId":55362,"journal":{"name":"Biomedical Signal Processing and Control","volume":null,"pages":null},"PeriodicalIF":4.9000,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A comparative study between laser speckle contrast imaging in transmission and reflection modes by adaptive window space direction contrast algorithm\",\"authors\":\"Guang Han ,&nbsp;De Li ,&nbsp;Jixin Yuan ,&nbsp;Jie Lu ,&nbsp;Jun Zhang ,&nbsp;Huiquan Wang ,&nbsp;Ruijuan Chen ,&nbsp;Yifan Wu\",\"doi\":\"10.1016/j.bspc.2024.107091\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Blood flow visualization is of paramount importance in diagnosing and treating vascular diseases. Laser speckle contrast imaging (LSCI) is a widely utilized technique for visualizing blood flow. However, Reflect-laser speckle contrast imaging (R-LSCI) systems are limited in their imaging depth and primarily suitable for shallow blood flow imaging. In this study, we conducted a comparative analysis of Transmissive-laser speckle contrast imaging (T-LSCI) and R-LSCI using four spatial domain imaging methods: spatial contrast (sK), adaptive window contrast (awK), space-directional contrast (sdK), and adaptive window space direction contrast (awsdK), for deep blood flow imaging. Experimental results show that T-LSCI is superior to R-LSCI in imaging deep blood flow within a certain thickness of tissue. T-LSCI can be used for continuous non-invasive blood flow monitoring. Particularly, the utilization of the awsdK method in T-LSCI substantially improves the visualization of deep blood flow and enhances the ability to monitor blood flow variations.</div></div>\",\"PeriodicalId\":55362,\"journal\":{\"name\":\"Biomedical Signal Processing and Control\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":4.9000,\"publicationDate\":\"2024-10-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Biomedical Signal Processing and Control\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1746809424011492\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, BIOMEDICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Biomedical Signal Processing and Control","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1746809424011492","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, BIOMEDICAL","Score":null,"Total":0}
引用次数: 0

摘要

血流可视化对诊断和治疗血管疾病至关重要。激光斑点对比成像(LSCI)是一种广泛应用的血流可视化技术。然而,反射激光斑点对比成像(R-LSCI)系统的成像深度有限,主要适用于浅层血流成像。在这项研究中,我们使用四种空间域成像方法:空间对比度(sK)、自适应窗口对比度(awK)、空间方向对比度(sdK)和自适应窗口空间方向对比度(awsdK),对透射激光斑点对比成像(T-LSCI)和 R-LSCI 进行了对比分析,以用于深层血流成像。实验结果表明,T-LSCI 在一定厚度组织内的深部血流成像方面优于 R-LSCI。T-LSCI 可用于连续无创血流监测。特别是在 T-LSCI 中使用 awsdK 方法,大大改善了深部血流的可视化,提高了监测血流变化的能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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
A comparative study between laser speckle contrast imaging in transmission and reflection modes by adaptive window space direction contrast algorithm
Blood flow visualization is of paramount importance in diagnosing and treating vascular diseases. Laser speckle contrast imaging (LSCI) is a widely utilized technique for visualizing blood flow. However, Reflect-laser speckle contrast imaging (R-LSCI) systems are limited in their imaging depth and primarily suitable for shallow blood flow imaging. In this study, we conducted a comparative analysis of Transmissive-laser speckle contrast imaging (T-LSCI) and R-LSCI using four spatial domain imaging methods: spatial contrast (sK), adaptive window contrast (awK), space-directional contrast (sdK), and adaptive window space direction contrast (awsdK), for deep blood flow imaging. Experimental results show that T-LSCI is superior to R-LSCI in imaging deep blood flow within a certain thickness of tissue. T-LSCI can be used for continuous non-invasive blood flow monitoring. Particularly, the utilization of the awsdK method in T-LSCI substantially improves the visualization of deep blood flow and enhances the ability to monitor blood flow variations.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Biomedical Signal Processing and Control
Biomedical Signal Processing and Control 工程技术-工程:生物医学
CiteScore
9.80
自引率
13.70%
发文量
822
审稿时长
4 months
期刊介绍: Biomedical Signal Processing and Control aims to provide a cross-disciplinary international forum for the interchange of information on research in the measurement and analysis of signals and images in clinical medicine and the biological sciences. Emphasis is placed on contributions dealing with the practical, applications-led research on the use of methods and devices in clinical diagnosis, patient monitoring and management. Biomedical Signal Processing and Control reflects the main areas in which these methods are being used and developed at the interface of both engineering and clinical science. The scope of the journal is defined to include relevant review papers, technical notes, short communications and letters. Tutorial papers and special issues will also be published.
期刊最新文献
Automated pericardium segmentation and epicardial adipose tissue quantification from computed tomography images A design of computational stochastic framework for the mathematical severe acute respiratory syndrome coronavirus model Topological feature search method for multichannel EEG: Application in ADHD classification ROPRNet: Deep learning-assisted recurrence prediction for retinopathy of prematurity Editorial Board
×
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:481959085
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