Jiangbo Chen 1†Yachao Zhang 1†Xiaozhen Li 2†Jingyi Zhu 1[ ... ]Lidai Wang 1,3,5,*
Author Affiliations
Abstract
1 Department of Biomedical Engineering, City University of Hong Kong, 999077 Hong Kong SAR, China
2 Center of Super-Diamond and Advanced Films (COSDAF) and Department of Chemistry, City University of Hong Kong, 999077 Hong Kong SAR, China
3 City University of Hong Kong Shenzhen Research Institute, Shenzhen 518057, China
4 e-mail: apcslee@cityu.edu.hk
5 e-mail: lidawang@cityu.edu.hk
Distinguishing early-stage tumors from normal tissues is of great importance in cancer diagnosis. We report fiber-based confocal visible/near-infrared (NIR) optical-resolution photoacoustic microscopy that can image tumor microvasculature, oxygen saturation, and nanoprobes in a single scanning. We develop a cost-efficient single laser source that provides 532, 558, and 1064 nm pulsed light with sub-microseconds wavelength switching time. Via dual-fiber illumination, we can focus the three beams to the same point. The optical and acoustic foci are confocally aligned to optimize the sensitivity. The visible and NIR wavelengths enable simultaneous tumor imaging with three different contrast modes. Results show obvious angiogenesis, significantly elevated oxygen saturation, and accumulated nanoparticles in the tumor regions, which offer comprehensive information to detect the tumor. This approach also allows us to identify feeding and draining vessels of the tumor and thus to determine local oxygen extraction fraction. In the tumor region, the oxygen extraction fraction significantly decreases along with tumor growth, which can also assist in tumor detection and staging. Fiber-based confocal visible/NIR photoacoustic microscopy offers a new tool for early detection of cancer.
Photonics Research
2020, 8(12): 12001875
作者单位
摘要
江西农业大学生物光电技术及应用重点实验室, 江西 南昌 330045
为打击山茶油掺假,保障消费者的合法利益,利用近红外光谱和子窗口重排分析(SPA)对山茶油的复杂掺假(掺入大豆油、菜籽油、花生油及混合油)进行检测。采集85 个纯山茶油和315 个掺假山茶油样本的近红外光谱,利用SPA 变量选择方法对样本光谱的波长变量进行筛选,再由偏最小二乘-线性判别分析(PLS-LDA)建立山茶油掺假检测模型,并与竞争性自适应重加权算法(CARS)和无信息变量消除(UVE)变量选择方法的结果进行比较。研究结果表明,近红外光谱联合SPA 方法可以用于山茶油的复杂掺假检测,预测集样本的分类错误率、灵敏度及特异性分别为0、1和1。SPA 方法优于UVE 方法,与CARS方法相当,是一种有效的变量选择方法,能简化模型并提高模型的预测精度和稳定性。
光谱学 掺假检测 近红外 子窗口重排分析 山茶油 
光学学报
2015, 35(6): 0630005
作者单位
摘要
1 西安电子科技大学技术物理学院, 陕西 西安 710071
2 西安电子科技大学雷达信号处理国家重点实验室, 陕西 西安 710071
合成孔径激光雷达(SAL)由于信号波长短,造成波束光斑脚印较小,限制了成像场景的幅宽。针对该问题,将合成孔径雷达(SAR)中常用的宽场景测绘TOPS模式推广应用到SAL中,并针对SAL的信号特性,提出了一种可行的成像算法:采用基于谱分析的方位预滤波方法,消除由于波束转动导致的方位信号模糊,获得信号无模糊的二维频谱;利用改进的频率变标算法(FSA)完成距离压缩及距离徙动校正,并校正平台连续运动引入的多普勒频移;结合去斜技术将信号聚焦在方位频域,获得无模糊的SAL图像。仿真结果验证了该算法的有效性。
遥感 激光雷达 合成孔径 宽场景成像 频率变标算法 方位预滤波 
光学学报
2013, 33(12): 1228004

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