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Method for the generation and visualization of cross-sectional images of three-dimensional point spread functions for rotationally symmetric intraocular lenses

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BIOMEDICAL OPTICS EXPRESS 2022年第2期13卷 1087-1101页

作者： Sievers, Jan Elsner, Ricardo Bohn, Sebastian Schuenemann, Melanie Stolz, Heinrich Guthoff, Rudolf F. Stachs, Oliver Sperlich, Karsten Rostock Univ Dept Ophthalmol Med Ctr D-18057 Rostock Germany Univ Rostock Dept Life Light & Matter D-18055 Rostock Germany Martin Luther Univ Halle Wittenberg Inst Phys D-06120 Halle Germany Univ Rostock Inst Phys D-18055 Rostock Germany

Cross-sectional images of three-dimensional point spread functions of intraocular lenses are used to study their image formation. To obtain those, light sheet-based methods are established. Due to the non-negligible thicknesses of the light sheets, the image quality of the cross-sectional images is constrained. To overcome this hurdle, we present a dedicated evaluation algorithm to increase image quality in the post-processing step. Additionally, we compare the developed-with the light sheet method based on our own investigations of a multifocal diffractive intraocular lens conducted in an in-house designed optical bench. The comparative study showed the clear superiority of the newly developed method in terms of image quality, fine structure visibility, and signal-to-noise ratio compared to the light sheet based method. However, since the algorithm assumes a rotationally symmetrical point spread function, it is only suitable for all rotationally symmetrical lenses.

关键词： Diffractive lenses image processing algorithms image quality Modulation transfer function Point spread function Three dimensional imaging

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Interactive optical 3D-touch user interface using a holographic light-field display and color information

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OPTICS EXPRESS 2020年第24期28卷 36740-36755页

作者： Chavarria, Ivan A. Sanchez Salazar Nakamura, Tomoya Yamaguchi, Masahiro Tokyo Inst Technol Sch Engn Midori Ku 4259 Nagatsuta Yokohama Kanagawa 2268503 Japan Osaka Univ Inst Sci & Ind Res 8-1 Mihogaoka Ibaraki Osaka 5670047 Japan

We propose an interactive optical 3D-touch user interface (UI) by using a holographic light-field (LF) 3D display and a color detection system of the scattered light from the touched 3D image. In the proposed system, color information embedded in the LF is used to realize the 3D position identification and movement detection of the interaction point in 3D space only with a single RGB camera. We demonstrate the real-time interactive implementation of the interface working at 12 frames per second, which verifies the feasibility of our proposed concept. (C) 2020 Optical Society of America under the terms of the OSA Open Access Publishing Agreement

关键词： Diffraction efficiency Heads up displays Holographic displays image processing algorithms Light fields Real time implementation

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Advanced image analysis verifies geometry performance of micro-milling systems

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APPLIED OPTICS 2017年第10期56卷 2912-2921页

作者： Daemi, Bita Ekberg, Peter Mattsson, Lars KTH Royal Inst Technol Ind Metrol & Opt Dept Prod Engn S-10044 Stockholm Sweden

Accurate dimensional measurement of micro-milled items is a challenge and machine specifications do not include operational parameters in the workshop. Therefore, a verification test that shows the machine's overall geometrical performance over its working area would help machine users in the assessment and adjustment of their equipment. In this study, we present an optical technique capable of finding micro-milled features at submicron uncertainty over working areas > 10 cm(2). The technique relies on an ultra-precision measurement microscope combined with advanced image analysis to get the center of gravity of milled cross-shaped features at subpixel levels. Special algorithms had to be developed to handle the disturbing influence of burr and milling marks. The results show repeatability, reproducibility, and axis straightness for three micro-milling facilities and also discovered an unknown 2 mu m amplitude undulation in one of them. (C) 2017 Optical Society of America

关键词： Digital image processing Edge detection image analysis image processing image processing algorithms Laser machining

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Simulation of optical coherence tomography images by Monte Carlo modeling based on polarization vector approach

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OPTICS EXPRESS 2010年第21期18卷 21714-21724页

作者： Kirillin, Mikhail Meglinski, Igor Kuzmin, Vladimir Sergeeva, Ekaterina Myllyla, Risto Inst Appl Phys RAS Nizhnii Novgorod 603950 Russia Univ Otago Dept Phys Jack Dodd Ctr Quantum Technol Dunedin 9054 New Zealand St Petersburg Inst Commerce & Econ St Petersburg 194021 Russia Univ Oulu Optoelect & Measurement Tech Lab Oulu 90014 Finland

Monte Carlo method is applied for simulation of 2D optical coherence tomography (OCT) images of skin-like model. Layer boundaries in skin model feature curved shape which agrees with physiological structure of human skin. The effect of coherence properties of probing radiation on OCT image formation and speckles in the detected OCT signal is considered. The developed model is employed for image simulation both for conventional and polarization dependent time-domain OCT modalities. Simulation of polarized OCT signal is performed using vector approach developed previously for modeling of electromagnetic field transfer in turbid media. (C) 2010 Optical Society of America

关键词： image processing algorithms Multiple scattering Optical coherence tomography Optical imaging Radiative transfer Turbid media

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Parallel deep neural networks for endoscopic OCT image segmentation

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BIOMEDICAL OPTICS EXPRESS 2019年第3期10卷 1126-1135页

作者： Li, Dawei Wu, Jimin He, Yufan Yao, Xinwen Yuan, Wu Chen, Defu Park, Hyeon-Cheol Yu, Shaoyong Prince, Jerry L. Li, Xingde Johns Hopkins Univ Dept Biomed Engn Baltimore MD 21205 USA Johns Hopkins Univ Dept Elect & Comp Engn Baltimore MD 21218 USA Johns Hopkins Univ Sch Med Dept Med Baltimore MD 21205 USA

We report parallel-trained deep neural networks for automated endoscopic OCT image segmentation feasible even with a limited training data set. These U-Net-based deep neural networks were trained using a modified dice loss function and manual segmentations of ultrahigh-resolution cross-sectional images collected by an 800 nm OCT endoscopic system. The method was tested on in vivo guinea pig esophagus images. Results showed its robust layer segmentation capability with a boundary error of 1.4 mu m insensitive to lay topology disorders. To further illustrate its clinical potential, the method was applied to differentiating in vivo OCT esophagus images from an eosinophilic esophagitis (EOE) model and its control group, and the results clearly demonstrated quantitative changes in the top esophageal layers' thickness in the EOE model. (C) 2019 Optical Society of America under the terms of the OSA Open Access Publishing Agreement

关键词： image processing image processing algorithms Medical image processing Neural networks Optical imaging Speckle noise

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Depth measurements through controlled aberrations of projected patterns

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OPTICS EXPRESS 2012年第6期20卷 6561-6574页

作者： Birch, Gabriel C. Tyo, J. Scott Schwiegerling, Jim Univ Arizona Coll Optic Sci Tucson AZ 85719 USA

Three-dimensional displays have become increasingly present in consumer markets. However, the ability to capture three-dimensional images in space confined environments and without major modifications to current cameras is uncommon. Our goal is to create a simple modification to a conventional camera that allows for three dimensional reconstruction. We require such an imaging system have imaging and illumination paths coincident. Furthermore, we require that any three-dimensional modification to a camera also permits full resolution 2D image capture. Here we present a method of extracting depth information with a single camera and aberrated projected pattern. A commercial digital camera is used in conjunction with a projector system with astigmatic focus to capture images of a scene. By using an astigmatic projected pattern we can create two different focus depths for horizontal and vertical features of a projected pattern, thereby encoding depth. By designing an aberrated projected pattern, we are able to exploit this differential focus in post-processing designed to exploit the projected pattern and optical system. We are able to correlate the distance of an object at a particular transverse position from the camera to ratios of particular wavelet coefficients. We present our information regarding construction, calibration, and images produced by this system. The nature of linking a projected pattern design and image processing algorithms will be discussed. (C) 2012 Optical Society of America

关键词： image processing image processing algorithms image quality Imaging systems Three dimensional imaging Three dimensional reconstruction

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High-flexibility and high-accuracy phase delay calibration method for MEMS-based fringe projection systems

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OPTICS EXPRESS 2023年第2期31卷 1049-1066页

作者： Qu, Jiasheng Gao, Hongxin Zhang, Ruihao Cao, Yingchao Zhou, Wenbiao Xie, Huikai Beijing Inst Technol Sch Integrated Circuits & Elect Beijing 100081 Peoples R China BIT Chongqing Inst Microelect & Microsyst Chongqing 400030 Peoples R China

Microelectromechanical system (MEMS) mirror based laser beam scanning (LBS) projectors for fringe projection profilometry (FPP) are becoming increasingly popular attributing to their small size and low cost. However, the initial phase of the scanning MEMS mirror employed in an LBS projector may vary over time, resulting in unstable and distorted fringe patterns. The distorted fringe patterns will largely decrease the accuracy of the three-dimensional (3D) topographic reconstruction. In this paper, an efficient phase delay calibration method based on a unique fringe projection sequence and a corresponding image processing algorithm is proposed. The proposed method can compensate the phase uncertainty and variation with no need to add any extra components. One LBS projector has been constructed using a uniaxial electrostatic MEMS mirror that has a mirror size of 2.5 mm x 2.5 mm and a scanning field of view of 60 degrees at its resonance of 1523 Hz. 3D reconstruction experiments are conducted to study how the 3D reconstruction results are affected by the phase delay. The standard deviation of a sphere reconstruction is improved from 2.05 mm to 0.20 mm after the positive phase delay deviation of 5 mu s is compensated using this new calibration method.(c) 2023 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement

关键词： Deformable mirrors Digital micromirror devices Fringe analysis Fringe projection image processing algorithms Laser scanning

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Elimination of stripe artifacts in light sheet fluorescence microscopy using an attention-based residual neural network

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BIOMEDICAL OPTICS EXPRESS 2022年第3期13卷 1292-1311页

作者： Wei, Zechen Wu, Xiangjun Tong, Wei Zhang, Suhui Yang, Xin Tian, Jie Hui, Hui CAS Key Lab Mol Imaging Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Beijing Key Lab Mol Imaging Beijing 100190 Peoples R China Univ Chinese Acad Sci Sch Artificial Intelligence Beijing 100190 Peoples R China Beihang Univ Sch Med & Engn Beijing Adv Innovat Ctr Big Data Based Precis Med Beijing 100083 Peoples R China Peoples Liberat Army Gen Hosp Med Ctr 6 Dept Cardiol Beijing 100853 Peoples R China Jinan Univ Zhuhai Peoples Hosp Zhuhai Precis Med Ctr Jinan 519000 Zhuhai Peoples R China

Stripe artifacts can deteriorate the quality of light sheet fluorescence microscopy (LSFM) images. Owing to the inhomogeneous, high-absorption, or scattering objects located in the excitation light path, stripe artifacts are generated in LSFM images in various directions and types, such as horizontal, anisotropic, or multidirectional anisotropic. These artifacts severely degrade the quality of LSFM images. To address this issue, we proposed a new deep-learning based approach for the elimination of stripe artifacts. This method utilizes an encoder-decoder structure of UNet integrated with residual blocks and attention modules between successive convolutional layers. Our attention module was implemented in the residual blocks to learn useful features and suppress the residual features. The proposed network was trained and validated by generating three different degradation datasets with different types of stripe artifacts in LSFM images. Our method can effectively remove different stripes in generated and actual LSFM images distorted by stripe artifacts. Besides, quantitative analysis and extensive comparison results demonstrated that our method performs the best compared with classical image-based processing algorithms and other powerful deep-learning-based destriping methods for all three generated datasets. Thus, our method has tremendous application prospects to LSFM, and its use can be easily extended to images reconstructed by other modalities affected by the presence of stripe artifacts. (c) 2022 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement

关键词： Acoustooptical deflectors Fast Fourier transforms image processing algorithms image quality Neural networks Three dimensional imaging

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PCIe-based FPGA- GPU heterogeneous computation for real-time multi-emitter fitting in super-resolution localization microscopy

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BIOMEDICAL OPTICS EXPRESS 2022年第6期13卷 3401-3415页

作者： Gui, Dan Chen, Yunjiu Kuang, Weibing Shang, Mingtao Zhang, Yingjun Huang, Zhen-li Huazhong Univ Sci & Technol Wuhan Natl Lab Optoelect Britton Chance Ctr Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol Wuhan Natl Lab Optoelect MoE Key Lab Biomed Photon Sch Engn Sci Wuhan 430074 Peoples R China Wuhan Vocat Coll Software & Engn Sch Elect Engn Wuhan 430205 Peoples R China Hainan Univ Sch Biomed Engn Key Lab Biomed Engn Hainan Prov Haikou 570228 Hainan Peoples R China

Real-time multi-emitter fitting is a key technology for advancing super-resolution localization microscopy (SRLM), especially when it is necessary to achieve dynamic imaging quality control and/or optimization of experimental conditions. However, with the increase of activation densities, the requirements in the computing resources would increase rapidly due to the complexity of the fitting algorithms, making it difficult to realize real-time multi-emitter fitting for emitter density more than 0.6 mol/mu m(2) in large field of view (FOV), even after acceleration with the popular Graphics processing Unit (GPU) computation. Here we adopt the task parallelism strategy in computer science to construct a Peripheral Component Interconnect Express (PCIe) based all-in-one heterogeneous computing platform (AIO-HCP), where the data between two major parallel computing hardware, Field Programmable Gate Array (FPGA) and GPU, are interacted directly and executed simultaneously. Using simulated and experimental data, we verify that AIO-HCP could achieve a data throughput of up to similar to 1.561 GB/s between FPGA and GPU. With this new platform, we develop a multi-emitter fitting method, called AIO-STORM, under big data stream parallel scheduling. We show that AIO-STORM is capable of providing real-time image processing on raw images with 100 mu mx 100 mu m FOV, 10 ms exposure time and 5.5 mol/mu m(2) structure density, without scarifying image quality. This study overcomes the data throughput limitation of heterogeneous devices, demonstrates the power of the PCIe-based heterogeneous computation platform, and offers opportunities for multi-scale stitching of super-resolution images. (C) 2022 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement

关键词： Capacity limits image display image processing image processing algorithms image quality Point spread function

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Defect extraction method for additive manufactured parts with improved learning-based image super-resolution and the Canny algorithm

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APPLIED OPTICS 2022年第28期61卷 8500-8507页

作者： Peng, Xing Kong, Lingbao Fudan Univ Shanghai Engn Res Ctr Ultraprecis Opt Mfg Sch Informat Sci & Technol Shanghai 200433 Peoples R China

Additive manufacturing (AM) is a highly competitive, low-cost, and high-degree-of-manufacturing technology. However, AMstill has limitations because of some defects. Thus, defect detection technology is essential for quality enhancement in theAMprocess. Super-resolution (SR) technology can be utilized to improve defect image quality and enhance defect extraction performance. This study proposes a defect extraction method for additive manufactured parts with improved learning-based image SR and the Canny algorithm (LSRC), which is based on direct mapping methodology. The LSRCmethod is compared with the bicubic interpolation algorithm and the neighbor embedding (NE) algorithm in SR reconstruction quality and robustness. The experimental results show that the proposed LSRCmethod achieves satisfactory performance in terms of the averaged information entropy (E), standard deviation (SD), peak signal-to-noise ratio (PSNR), and structural similarity (SSIM), which are 7.259, 45.301, 27.723, and 0.822, respectively. The accordingly average improvement rates of the E, SD, PSNR, and SSIM, are 0.45%, 7.15%, 5.85%, and 6.35% in comparison with the bicubic interpolation algorithm, while the comparison data are 0.97%, 13.40%, 10.55%, and 15.35% in terms of the NE algorithm. This indicates that the LSRC method is significantly better than the comparison algorithm in reconstruction quality and robustness, which is of great significance for the extraction and analysis of key defect information of additive manufactured parts. (c) 2022 Optica Publishing Group

关键词： High speed photography image processing algorithms image quality image resolution Thermal imaging X ray microscopy

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