Lihua Ruan 1,4Zhiqin Yin 1,2,3,4Shibing Zhou 1,4Weibo Zheng 1,4,*[ ... ]Shaowei Wang 1,2,3,4,**
Author Affiliations
Abstract
1 Shanghai Institute of Technical Physics, Chinese Academy of Sciences Shanghai 200083, P. R. China
2 State Key Laboratory of Infrared Physics, Shanghai Institute of Technical Physics, Chinese Academy of Sciences, Shanghai 200083, P. R. China
3 Shanghai Engineering Research Center of Energy-Saving Coatings Shanghai 200083, P. R. China
4 University of Chinese Academy of Sciences, Beijing 100049, P. R. China
5 Shanghai Tech University, Shanghai 201210, P. R. China
6 School of Physical Science and Technology, ShanghaiTech University, Shanghai 201210, P. R. China
7 School of Information Science and Technology, ShanghaiTech University, Shanghai 201210, China
Visual near-infrared imaging equipment has broad applications in various fields such as venipuncture, facial injections, and safety verification due to its noncontact, compact, and portable design. Currently, most studies utilize near-infrared single-wavelength for image acquisition of veins. However, many substances in the skin, including water, protein, and melanin can create significant background noise, which hinders accurate detection. In this paper, we developed a dual-wavelength imaging system with phase-locked denoising technology to acquire vein image. The signals in the effective region are compared by using the absorption valley and peak of hemoglobin at 700nm and 940nm, respectively. The phase-locked denoising algorithm is applied to decrease the noise and interference of complex surroundings from the images. The imaging results of the vein are successfully extracted in complex noise environment. It is demonstrated that the denoising effect on hand veins imaging can be improved with 57.3% by using our dual-wavelength phase-locked denoising technology. Consequently, this work proposes a novel approach for venous imaging with dual-wavelengths and phase-locked denoising algorithm to extract venous imaging results in complex noisy environment better.
Dual-wavelength phase-locked denoising vein visualization enhancement Journal of Innovative Optical Health Sciences
2024, 17(3): 2350033
Author Affiliations
Abstract
1 School of Optics and Photonics, Beijing Institute of Technology, Beijing 100081, P. R. China
2 School of Medical Technology, Beijing Institute of Technology, Beijing 100081, P. R. China
3 Department of Laser Medicine, First Medical Center of PLA General Hospital, Beijing 100853, P. R. China
4 Britton Chance Center for Biomedical Photonics – MoE Key Laboratory for Biomedical Photonics, Advanced Biomedical Imaging Facility, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan 430074, Hubei, P. R. China
5 Precision Laser Medical Diagnosis and Treatment Innovation Unit, Chinese Academy of Medical Sciences, Beijing 100000, P. R. China
Vascular-targeted photodynamic therapy (V-PDT) is an effective treatment for port wine stains (PWS). However, repeated treatment is usually needed to achieve optimal treatment outcomes, possibly due to the limited treatment light penetration depth in the PWS lesion. The optical clearing technique can increase light penetration in depth by reducing light scattering. This study aimed to investigate the V-PDT in combination with an optical clearing agent (OCA) for the therapeutic enhancement of V-PDT in the rodent skinfold window chamber model. Vascular responses were closely monitored with laser speckle contrast imaging (LSCI), optical coherence tomography angiography, and stereo microscope before, during, and after the treatment. We further quantitatively demonstrated the effects of V-PDT in combination with OCA on the blood flow and blood vessel size of skin microvasculature. The combination of OCA and V-PDT resulted in significant vascular damage, including vasoconstriction and the reduction of blood flow. Our results indicate the promising potential of OCA for enhancing V-PDT for treating vascular-related diseases, including PWS.
Vascular-targeted photodynamic therapy (V-PDT) optical clearing agent (OCA) treatment efficacy enhancement skin-fold window chamber port wine stains Journal of Innovative Optical Health Sciences
2024, 17(2): 2350023
1 石家庄铁道大学工程力学系，河北 石家庄 050043
2 石家庄铁道大学省部共建交通工程结构力学行为与系统安全国家重点实验室，河北 石家庄 050043
针对长脉冲热波激励后采集到的红外原始热图中缺陷对比度低、缺陷边缘模糊等问题，本文提出了一种基于傅里叶变换、频域相位积分和保边滤波的红外序列图像处理方法，该算法首先对冷却时间段内采集到的红外原始热图进行消背景处理，再利用傅里叶变换将试样表面的红外辐射信息转化为相位信息，频域相位积分处理可以将不同频率下缺陷的相位信息整合至一幅相位积分图中，最后通过保边滤波器及自适应伽马变换对积分图像进行增强和量化。该算法克服了传统方法需要人工从多张频率或成分图中甄别出最优检测结果的缺点，并且可以消除加热不均匀的影响，改善缺陷的可视化。试验结果从定性和定量两个角度验证评估了该算法的有效性，并讨论了采集参数的影响。
长脉冲热像法 傅里叶变换 相位增强 复合材料
Author Affiliations
Abstract
College of Engineering and Applied Sciences and Collaborative Innovation Center of Advanced Microstructures, Nanjing University, Nanjing, China
Optical fiber bundles frequently serve as crucial components in flexible miniature endoscopes, transmitting end-to-end images directly for medical and industrial applications. Each core usually acts as a single pixel, and the resolution of the image is limited by the core size and core spacing. We propose a method that exploits the hidden information embedded in the pattern within each core to break the limitation and obtain high-dimensional light field information and more features of the original image including edges, texture, and color. Intra-core patterns are mainly related to the spatial angle of captured light rays and the shape of the core. A convolutional neural network is used to accelerate the extraction of in-core features containing the light field information of the whole scene, achieve the transformation of in-core features to real details, and enhance invisible texture features and image colorization of fiber bundle images.
fiber bundles image enhancement image colorization mode pattern deep learning Advanced Imaging
2024, 1(1): 011002
1 北方民族大学 计算机科学与工程学院，宁夏银川75002
2 北方民族大学 图像图形智能处理国家民委重点实验室，宁夏银川75001
3 宁夏医科大学 医学信息与工程学院，宁夏银川750004
针对肺部X射线图像的病灶区域较小、形状复杂，与正常组织间的边界模糊，使得肺炎图像中的病灶特征提取不充分的问题，提出了一个面向特征增强的双残差Res-Transformer肺炎识别模型，设计3种不同的特征增强策略对模型特征提取能力进行增强。设计了组注意力双残差模块（GADRM），采用双残差结构进行高效的特征融合，将双残差结构与通道混洗、通道注意力、空间注意力结合，增强模型对于病灶区域特征的提取能力；在网络的高层采用全局局部特征提取模块（GLFEM），结合CNN和Transformer的优势使网络充分提取图像的全局和局部特征，获得高层语义信息的全局特征，进一步增强网络的语义特征提取能力；设计了跨层双注意力特征融合模块（CDAFFM），融合浅层网络的空间信息以及深层网络的通道信息，对网络提取到的跨层特征进行增强。为了验证本文模型的有效性，分别在COVID-19 CHEST X-RAY数据集上进行消融实验和对比实验。实验结果表明，本文所提出网络的准确率、精确率、召回率，F1值和AUC值分别为98.41%，94.42%，94.20%，94.26%和99.65%。DRT Net能够帮助放射科医生使用胸部X光片对肺炎进行诊断，具有重要的临床作用。
肺炎识别 X射线图像 特征增强 双残差结构 Transformer pneumonia recognition X-ray image feature enhancement dual residual model Transformer
中国人民解放军63870部队，陕西渭南714299
在可见光红外跟踪（RGB and Thermal Infrared Tracking，RGB-T）的研究中，为了在常规跟踪算法的基础上实现两个模态的有效融合，基于注意力机制提出了一种基于注意力交互的RGB-T跟踪算法。该算法引入注意力机制对可见光和红外两种模态的图像特征进行增强和融合，设计了自特征增强编码器对单一模态的特征进行增强，设计了互特征解码器对两个模态增强后的特征进行交互融合。编码器和解码器均采用两层注意力模块。为了减小算法模型的复杂度，对传统注意力模块进行简化，将全连接层改为1
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1卷积。此外，该算法对多个卷积层的特征均进行分层融合，以充分挖掘各层卷积特征中的细节和语义信息。在GTOT，RGBT234和LasHeR三个数据集上进行对比测试。实验结果表明，所提算法性能优异，特别是在RGBT234和LasHeR这两个大规模数据集上取得了最优的跟踪结果，验证了注意力机制在RGB-T跟踪中的有效性。
1 中国科学院光电技术研究所，四川 成都 610209
2 中国科学院光场调控科学技术全国重点实验室，四川 成都 610209
3 中国科学院大学电子电气与通信工程学院，北京 100049
4 中国科学院大学光电学院，北京 100049
针对水下图像因成像环境造成的色彩失真、对比度下降、模糊等问题，提出一种自适应水下图像增强算法。首先，基于Lab色彩空间的局部色偏和全局色偏对衰减颜色进行色彩补偿，再利用灰度世界算法恢复水下图像的色彩平衡。其次，使用自动色阶和伽马校正方法调整各通道信息，以获得高动态范围、高照度的图像。最后，通过反锐化掩膜方法获得高频信息并增强图像细节，从而获得清晰的水下图像。所提算法利用图像的色偏、均方差等统计信息，实现了自适应处理。实验结果表明，所提算法能有效去除水下图像色偏，提高图像对比度与清晰度，提升视觉效果。较之其他算法，其在处理效果及时间上均有优势。
图像处理 水下图像增强 色彩校正 对比度提升 细节增强 激光与光电子学进展
2024, 61(8): 0837001
1 华东师范大学精密光谱科学与技术国家重点实验室，上海 200241
2 华东师范大学重庆研究院精密光学重庆市重点实验室，重庆 401121
超短强激光脉冲与物质相互作用产生的高次谐波辐射是一种相干的极紫外或软X射线光源，并且在时间上还是阿秒脉冲串。在不同介质中探寻更有效的高次谐波产生方案一直是研究热点。利用飞秒激光烧蚀低密度等离子体羽可将高次谐波扩展到几乎任何固体材料，极大地丰富了媒介的选择性。由于某些材料的等离子体内低电离态离子共振跃迁频率与谐波波长存在匹配，使得在极紫外波段特定阶次谐波表现出明显的共振增强效应，从而能够获得强单色的高次谐波辐射。结合纳米颗粒的近场增强效应和较大的电子回撞截面，极紫外波段的高次谐波转换效率可以进一步得到提高。激光等离子体高次谐波有望产生高脉冲能量、增强阶次可调和高重复频率的相干极紫外辐射。综述单阶谐波共振增强效应的产生原理和研究进展，分析各种优化方法和光场调控手段，并对未来的发展趋势进行展望。
非线性光学 高次谐波 低密度等离子体 共振增强 极紫外波段
