摘要
基于近红外光谱法对组织内的异质体进行无创检测时,光源-探测器(S-D)相对于异质体的位置对检测效果有着重要影响。为实现对组织内异质体的快速定位,该研究基于一源多探的检测结构针对不同水平位置、不同深度和不同直径的异质体进行光密度分布有限元分析,计算各探测器之间的差分光密度差异。仿真实验结果表明,根据多探测器形成的差分光密度差异曲线可快速定位组织内异质体的水平位置。曲线的高斯拟合特征量与异质体的水平位置、深度和直径有着强相关性。基于差分光密度差异曲线可以实现组织内感兴趣区域的快速定位,对采用近红外光谱法的组织肿瘤检测、光学脑功能成像等领域的源-探位置放置提供重要参考,提高其检测精度。
The position of the source-detector(S-D)relative to the anomaly had an important influence on the detection effect when the detection of the anomaly in tissues was non-invasive based on near-infrared spectroscopy.In this study,a Single-Source Multi-Detectors structure was designed in order to realize the rapid localization of anomaly within the organization.This method was for finite element analysis of optical density distribution for different horizontal positions,depths and diameters of anomaly.Then calculated the difference in optical density between the detectors.The simulation results showed that the horizontal position of the anomaly in the tissue could be quickly located according to the differential optical density difference curves formed by the multiple detectors.The Gaussian fitting feature of these curves has a strong correlation with the horizontal positions,depths and diameters of the anomaly.Through the differential optical density difference curves,rapid localization could be achieved within the region of interest in the organization.It provides an important reference for the sources and detectors location in terms of tumor detection,brain function optical imaging and other fields using near infrared spectroscopy,which can improve its detection accuracy.
作者
王慧泉
任丽娜
赵喆
王金海
陈洪丽
WANG Hui-quan;REN Li-na;ZHAO Zhe;WANG Jin-hai;CHEN Hong-li(School of Electronics and Information Engineering,Tianjin Polytechnic University,Tianjin 300387,China;Tianjin Photoelectric Detection Technology and Systems Key Laboratory,Tianjin 300387,China)
出处
《光谱学与光谱分析》
SCIE
EI
CAS
CSCD
北大核心
2018年第11期3362-3367,共6页
Spectroscopy and Spectral Analysis
基金
国家自然科学青年基金项目(61705164)资助
关键词
近红外光谱
异质体检测
差分光密度差异
高斯拟合
Near infrared spectroscopy
Anomaly detection
Differential optical density difference
Gaussian fitting
