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Deep learning automated pathology in ex vivo microscopy

BIOMEDICAL OPTICS EXPRESS 2021年第6期12卷 3103-3116页

作者： Combalia, Marc Garcia, Sergio Malvehy, Josep Puig, Susana Mulberger, Alba Guembe Browning, James Garcet, Sandra Krueger, James G. Lish, Samantha R. Lax, Rivka Ren, Jeannie Stevenson, Mary Doudican, Nicole Carucci, John A. Jain, Manu White, Kevin Rakos, Jaroslav Gareau, Daniel S. Univ Barcelona Hosp Clin Barcelona Dept Dermatol Barcelona Spain Rockefeller Univ 1230 York Ave New York NY 10065 USA Mem Sloan Kettering Canc Ctr 1275 York Ave New York NY 10065 USA NYU Ronald O Pearlman Dept Dermatol 550 First Ave New York NY 10016 USA Oregon Hlth & Sci Univ Dept Dermatol 3303 South Bond Ave Portland OR 97239 USA SurgiVance Inc 310 East 67th St New York NY 10065 USA

Standard histopathology is currently the gold standard for assessment of margin status in Mohs surgical removal of skin cancer. Ex vivo confocal microscopy (XVM) is potentially faster, less costly and inherently 3D/digital compared to standard histopathology. Despite these advantages, XVM use is not widespread due, in part, to the need for pathologists to retrain to interpret XVM images. We developed artificial intelligence (AI)-driven XVM pathology by implementing algorithms that render intuitive XVM pathology images identical to standard histopathology and produce automated tumor positivity maps. XVM images have fluorescence labeling of cellular and nuclear biology on the background of endogenous (unstained) reflectance contrast as a grounding counter-contrast. XVM images of 26 surgical excision specimens discarded after Mohs micrographic surgery were used to develop an XVM data pipeline with 4 stages: flattening, colorizing, enhancement and automated diagnosis. The first two stages were novel, deterministic image processing algorithms, and the second two were AI algorithms. Diagnostic sensitivity and specificity were calculated for basal cell carcinoma detection as proof of principal for the XVM image processing pipeline. The resulting diagnostic readouts mimicked the appearance of histopathology and found tumor positivity that required first collapsing the confocal stack to a 2D image optimized for cellular fluorescence contrast, then a dark field-to-bright field colorizing transformation, then either an AI image transformation for visual inspection or an AI diagnostic binary image segmentation of tumor obtaining a diagnostic sensitivity and specificity of 88% and 91% respectively. These results show that video-assisted micrographic XVM pathology could feasibly aid margin status determination in micrographic surgery of skin cancer.

关键词： Biology Confocal microscopy Digital image processing Digital imaging image processing image processing algorithms

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Inclusion extraction from diamond clarity images based on the analysis of diamond optical properties

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OPTICS EXPRESS 2019年第19期27卷 27242-27255页

作者： Wang, Wenjing Cai, Lilong Hong Kong Univ Sci & Technol Dept Mech Engn Kowloon Clear Water Bay Hong Kong Peoples R China

Diamond clarity refers to the absence of tiny, natural inclusions (imperfections) inside a diamond or on its surface. Almost all diamonds contain their own unique inclusions due to their natural formation process. In this paper, a new inclusion extraction approach is developed to accurately separate the regions of interest in a diamond clarity image and then identify the image features of each region. The inclusion regions can be successfully distinguished from other types of signals. The findings of the theoretical optical analysis facilitate the image processing development and also reduce its complexity and operation time. The experimental results verify the effectiveness and robustness of the proposed inclusion extraction approach. The diamond inclusions can be accurately extracted from the captured diamond clarity image. The extracted inclusions can also be converted to their actual size as seen by the naked human eye. The proposed approach is verified to be significantly less sensitive to noise than existing approaches and unaffected by the fluctuations in illumination. (C) 2019 Optical Society of America under the terms of the OSA Open Access Publishing Agreement

关键词： CCD cameras Edge detection Fresnel reflection image processing image processing algorithms image quality

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Full-view imaging on dynamic closed surface by curved-to-flat conversion lens

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OPTICS EXPRESS 2021年第18期29卷 28167-28177页

作者： Chen, Si Sun, Fei Liu, Yichao Yang, Yibiao Chen, Zhihui Taiyuan Univ Technol Coll Phys & Optoelect Minist Educ & Shanxi Prov Key Lab Adv Transducers & Intelligent Control Sys Taiyuan 030024 Peoples R China

Conventional full-view imaging systems, which often need complicated image processing algorithms to reconstruct full-view images captured by motional/multiple cameras from different views, cannot have good real-time imaging capability. We design curved-to-flat conversion lens (CFCL) based on optic-null medium, which can directly project/image optical patterns from closed object surface onto image plane (e.g., the focal plane of microscopy), and shows good real-time full-view imaging performance. To realize the CFCL, the reduced opticnull medium is designed by subwavelength metal channels filled with homogeneous isotropic dielectrics. Numerical simulation results verify the function of the designed CFCL, which can image various dynamic optical patterns from the closed object surface to the finite-view image plane. The designed CFCL may have many applications in real-timely observing dynamic closed surfaces in full view, e.g., living tissue/cell and soft material's surface. (C) 2021 Optical Society of America under the terms of the OSA Open Access Publishing Agreement

关键词： Digital image processing image processing image processing algorithms Imaging systems Optical surfaces Real time imaging

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High-density localization of active molecules using Structured Sparse Model and Bayesian Information Criterion

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OPTICS EXPRESS 2011年第18期19卷 16963-16974页

作者： Quan, Tingwei Zhu, Hongyu Liu, Xiaomao Liu, Yongfeng Ding, Jiuping Zeng, Shaoqun Huang, Zhen-Li Huazhong Univ Sci & Technol Wuhan Natl Lab Optoelect Britton Chance Ctr Biomed Photon Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol Minist Educ Key Lab Biomed Photon Wuhan 430074 Peoples R China Hubei Univ Educ Sch Math & Econ Wuhan 430205 Peoples R China Huazhong Univ Sci & Technol Sch Math & Stat Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol Coll Life Sci & Technol Minist Educ Key Lab Mol Biophys Wuhan 430074 Peoples R China

Localization-based super-resolution microscopy (or called localization microscopy) rely on repeated imaging and localization of active molecules, and the spatial resolution enhancement of localization microscopy is built upon the sacrifice of its temporal resolution. Developing algorithms for high-density localization of active molecules is a promising approach to increase the speed of localization microscopy. Here we present a new algorithm called SSM_BIC for such purpose. The SSM_BIC combines the advantages of the Structured Sparse Model (SSM) and the Bayesian Information Criterion (BIC). Through simulation and experimental studies, we evaluate systematically the performance between the SSM_BIC and the conventional Sparse algorithm in high-density localization of active molecules. We show that the SSM_BIC is superior in processing single molecule images with weak signal embedded in strong background. (C) 2011 Optical Society of America

关键词： Diode pumped lasers image processing algorithms Live cell imaging Spatial resolution Super resolution microscopy Temporal resolution

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Demonstration of long-distance hazard-free wearable EEG monitoring system using mobile phone visible light communication

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OPTICS EXPRESS 2017年第2期25卷 713-719页

作者： Rachim, Vega Pradana Jiang, Yubing Lee, Hyeon-Seok Chung, Wan-Young Pukyong Natl Univ Dept Elect Engn Busan 48513 South Korea

A wearable electroencephalogram (EEG) is a small mobile device used for long-term brain monitoring systems. Applications of these systems include fatigue monitoring, mental/emotional monitoring, and brain-computer interfaces. However, the usage of wireless wearable EEG systems is limited due to the risks posed by the wireless RF communication radiation in a long-term exposure to the human brain. A novel microwave radiation-free system was developed by integrating visible light communication technology into a wearable EEG device. In this work, we investigated the system's performance in transmitting EEG data at different illuminance level and proposed an algorithm that functions at low illuminance levels for increased transmission distance. Using a 30 Hz smartphone camera, the proposed system was able to transmit 2.4 kbps of error-free EEG data up to 4 meter, which is equal to similar to 300 lux using an aspheric focus lens. (C) 2017 Optical Society of America

关键词： Analog to digital converters image processing image processing algorithms Modulation techniques Signal processing Visible light

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Temperature-compensated infrared-based low-cost mobile platform module for mass human temperature screening

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APPLIED OPTICS 2020年第17期59卷 E112-E117页

作者： Somboonkaew, Armote Vuttivong, Sirajit Prempree, Panintorn Amarit, Ratthasart Chanhorm, Sataporn Chaitavon, Kosom Porntheeraphat, Supanit Sumriddetchkajorn, Sarun Spectroscop & Sensing Devices Res Grp Photon Technol Res Team 112 Thailand Sci PkPhahonyothin RdKhlong 1 Khlong Luang 12120 Pathumthani Thailand Natl Sci & Technol Dev Agcy Natl Elect & Comp Technol Ctr 112 Thailand Sci PkPhahonyothin RdKhlong 1 Khlong Luang 12120 Pathumthani Thailand

As fast human temperature screening is needed in large public areas, this paper proposes a low-cost mobile platform module that combines the advantages of analyzing visible and thermal images. In particular, the key idea relies on face detection in the visible image. Then the coordinates of all faces detected are mapped on to the thermal image to determine their corresponding temperatures. Internal temperature compensation and external reference temperature also are employed to reduce the unwanted temperature fluctuation inside the module and in the surrounding environment. Our mobile platform module, called mu Therm, uses a FLIR ONE camera as our visible and thermal imaging cameras. It can simultaneously determine the temperatures of nine people at a speed of 8 frames/second. A field test operation was performed for four days with 1,170 people, with very promising results of 100% sensitivity, 92.6% specificity, and 92.7% accuracy. (C) 2020 Optical Society of America

关键词： Face recognition Flat panel displays Forward looking infrared image processing algorithms Temperature Thermal imaging

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Kinematic and deformation parameter measurement by spatiotemporal analysis of an interferogram sequence

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APPLIED OPTICS 2007年第36期46卷 8645-8655页

作者： Fu, Yu Groves, Roger M. Pedrini, Giancarlo Osten, Wolfgang Univ Stuttgart Inst Tech Opt D-70569 Stuttgart Germany Natl Univ Singapore Dept Mech Engn Singapore 119260 Singapore

In recent years, optical interferometry has been applied to the whole-field, noncontact measurement of vibrating or continuously deforming objects. In many cases, a high resolution measurement of kinematic (displacement, velocity, and acceleration, etc.) and deformation parameters (strain, curvature, and twist, etc.) can give useful information on the dynamic response of the objects concerned. Different signal processing algorithms are applied to two types of interferogram sequences, which were captured by a high-speed camera using different interferometric setups: (1) a speckle or fringe pattern sequence with a temporal carrier and (2) a wrapped phase map sequence. These algorithms include Fourier transform, windowed Fourier transform, wavelet transform, and even a combination of two of these techniques. We will compare these algorithms using the example of a 1D temporal evaluation of interferogram sequences and extend these algorithms to 2D and 3D processing, so that accurate kinematic and deformation parameters of moving objects can be evaluated with different types of optical interferometry. (C) 2007 Optical Society of America.

关键词： image processing algorithms Interferometry Laser interferometry Phase measurement Speckle interferometry Wavelet transforms

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Research on high-resolution imaging technology based on light field manipulation for a lenslet-based plenoptic camera

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APPLIED OPTICS 2018年第33期57卷 9877-9886页

作者： Liu, Xincheng Ma, Haotong Ren, Ge Qi, Bo Xie, Zongliang Chu, Junqiu Bai, Junjie Chinese Acad Sci Key Lab Opt Engn Chengdu 610209 Sichuan Peoples R China Chinese Acad Sci Inst Opt & Elect Chengdu 610209 Sichuan Peoples R China Univ Chinese Acad Sci Beijing 100039 Peoples R China

In this paper, an aberration correction method for an extended target is proposed to solve the problem of the lenslet-based plenoptic camera not imaging clearly under the influence of aberrations. We propose a light field manipulation method to improve performance of the light field imaging system. The principle of this method is that the sub-aperture images extracted from the raw light field image are offset when the light field imaging system is affected by aberrations, and the symmetrical arrangement of the sub-aperture image array is destroyed. By repairing the symmetrical arrangement of the sub-aperture image array, the influence of phase aberrations on the imaging system can be eliminated, and the resolution of the plenoptic camera can be improved. We use an image correlation algorithm to process the sub-aperture images of the plenoptic camera, calculate and compensate each sub-aperture image's displacement caused by aberrations, and restore the symmetrical arrangement of the sub-aperture image array;then, a corrected high-resolution refocused image can be generated. In particular, this method uses only the raw light field information obtained by the plenoptic camera in a single exposure, without adding other hardware devices. Furthermore, it takes the extended target itself as the reference image, so the ideal position need not be calibrated in advance. Also, the parallax information of the sub-aperture images is retained, and the method is simple and easy to use. Numerical simulation and experimental results show that the technology proposed in this paper can work well for high-resolution imaging of a plenoptic camera with phase aberrations. This method can be potentially applied to analyze lens aberration, media-induced image distortion such as water turbulence in underwater imaging, and atmospheric turbulence in remote imaging. It may have important application prospects in the fields of astronomical object detection, remote sensing, etc. (C) 2018 Optical

关键词： Atmospheric turbulence image metrics image processing algorithms Imaging systems Laser guide stars Underwater imaging

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image reconstruction for structured-illumination microscopy with low signal level

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OPTICS EXPRESS 2014年第7期22卷 8687-8702页

作者： Chu, Kaiqin McMillan, Paul J. Smith, Zachary J. Yin, Jie Atkins, Jeniffer Goodwin, Paul Wachsmann-Hogiu, Sebastian Lane, Stephen Univ Calif Davis Ctr Biophoton Sacramento CA 95817 USA Univ Melbourne Melbourne Vic 3010 Australia Appl Precis Issaquah WA 98027 USA Univ Calif Davis Dept Pathol & Lab Med Sacramento CA 95817 USA

We report a new image processing technique for the structured illumination microscopy designed to work with low signals, with the goal of reducing photobleaching and phototoxicity of the sample. Using a pre-filtering process to estimate experimental parameters and total variation as a constraint to reconstruct, we obtain two orders of magnitude of exposure reduction while maintaining the resolution improvement and image quality compared to a standard structured illumination microscopy. The algorithm is validated on both fixed and live cell data with results confirming that we can image more than 15x more time points compared to the standard technique. (C) 2014 Optical Society of America

关键词： Illumination design image processing algorithms image quality image reconstruction Optical transfer functions Spatial light modulators

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Accurate stacked-sheet counting method based on deep learning

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JOURNAL OF THE OPTICAL SOCIETY OF AMERICA A-OPTICS image SCIENCE AND VISION 2020年第7期37卷 1206-1218页

作者： Dieuthuy Pham Minhtuan Ha San, Cao Xiao, Changyan Hunan Univ Coll Elect & Informat Engn Changsha 410208 Peoples R China Saodo Univ Dept Elect Engn Hai Duong 170000 Vietnam

The accurate counting of laminated sheets, such as packing or printing sheets in industry, is extremely important because it greatly affects the economic cost. However, the different thicknesses, adhesion properties, and breakage points and the low contrast of sheets remain challenges to traditional counting methods based on image processing. This paper proposes a new stacked-sheet counting method with a deep learning approach using the U-Net architecture. A specific dataset according to the characteristics of stack side images is collected. The stripe of the center line of each sheet is used for semantic segmentation, and the complete side images of the slices are segmented via training with small image patches and testing with original large images. With this model, each pixel is classified by multi-layer convolution and deconvolution to determine whether it is the target object to be detected. After the model is trained, the test set is used to test the model, and a center region segmentation map based on the pixel points is obtained. By calculating the statistical median value of centerline points across different sections in these segmented images, the number of sheets can be obtained. Compared with traditional image algorithms in real product counting experiments, the proposed method can achieve better performance with higher accuracy and a lower error rate. (C) 2020 Optical Society of America

关键词： image processing image processing algorithms image quality Medical image processing Object detection Three dimensional imaging

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