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
Guang Han , De Li , Jixin Yuan , Jie Lu , Jun Zhang , Huiquan Wang , Ruijuan Chen , Yifan Wu
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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。
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.
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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.
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