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1.
Opt Express ; 27(19): 26355-26368, 2019 Sep 16.
Artigo em Inglês | MEDLINE | ID: mdl-31674519

RESUMO

Imaging in poorly illuminated environments using three-dimensional (3D) imaging with passive imaging sensors that operate in the visible spectrum is a formidable task due to the low number of photons detected. 3D integral imaging, which integrates multiple two-dimensional perspectives, is expected to perform well in the presence of noise, as well as statistical fluctuation in the detected number of photons. In this paper, we present an investigation of 3D integral imaging in low-light-level conditions, where as low as a few photons and as high as several tens of photons are detected on average per pixel. In the experimental verification, we use an electron multiplying charge-coupled device (EM-CCD) and a scientific complementary metal-oxide-semiconductor (sCMOS) camera. For the EM-CCD, a theoretical model for the probability distribution of the pixel values is derived, then fitted with the experimental data to determine the camera parameters. Likewise, pixelwise calibration is performed on the sCMOS to determine the camera parameters for further analysis. Theoretical derivation of the expected signal-to-noise-ratio is provided for each image sensor and corroborated by the experimental findings. Further comparison between the cameras includes analysis of the contrast-to-noise ratio (CNR) as well as the perception-based image quality estimator (PIQE). Improvement of image quality metrics in the 3D reconstructed images is successfully confirmed compared with those of the 2D images. To the best of our knowledge, this is the first experimental report of low-light-level 3D integral imaging with as little as a few photons detected per pixel on average to improve scene visualization including occlusion removal from the scene.

2.
Biomed Opt Express ; 10(8): 4276-4289, 2019 Aug 01.
Artigo em Inglês | MEDLINE | ID: mdl-31453010

RESUMO

Digital propagation of an off-axis hologram can provide the quantitative phase-contrast image if the exact distance between the sensor plane (such as CCD) and the reconstruction plane is correctly provided. In this paper, we present a deep-learning convolutional neural network with a regression layer as the top layer to estimate the best reconstruction distance. The experimental results obtained using microsphere beads and red blood cells show that the proposed method can accurately predict the propagation distance from a filtered hologram. The result is compared with the conventional automatic focus-evaluation function. Additionally, our approach can be utilized at the single-cell level, which is useful for cell-to-cell depth measurement and cell adherent studies.

3.
Opt Lett ; 44(13): 3230-3233, 2019 Jul 01.
Artigo em Inglês | MEDLINE | ID: mdl-31259928

RESUMO

Conventional polarimetric imaging may perform poorly in photon-starved environments. In this Letter, we demonstrate the potential of integral imaging and dedicated algorithms for extracting three-dimensional (3D) polarimetric information in low light, and reducing the effects of measurement uncertainty. In our approach, the Stokes polarization parameters are measured and statistically analyzed in low illumination conditions through 3D-reconstructed polarimetric images with dedicated algorithms to improve the signal-to-noise ratio (SNR). The 3D volumetric degree of polarization (DoP) of the scene is calculated by statistical algorithms. We show that the 3D polarimetric information of the object can be statistically extracted from the Stokes parameters and 3D DoP images. Experimental results along with a novel statistical analysis verify the feasibility of the proposed approach for polarimetric 3D imaging in photon-starved environments and show that it outperforms its two-dimensional counterpart in terms of SNR. To the best of our knowledge, this is the first report of novel optical experiments along with novel statistical analysis and dedicated algorithms to recover 3D polarimetric imaging signatures in low light.

4.
Opt Express ; 27(8): 11525-11536, 2019 Apr 15.
Artigo em Inglês | MEDLINE | ID: mdl-31052996

RESUMO

In this paper, we introduce the Mueller matrix imaging concepts for 3D Integral Imaging Polarimetry. The Mueller matrix of a complex scene is measured and estimated with 3D integral imaging. This information can be used to analyze the complex polarimetric behavior of any 3D scene. In particular, we show that the degree of polarization can be estimated at any selected plane for any arbitrary synthetic illumination source which may be difficult to produce in practice. This tool might open new perspectives for polarimetric analysis in the 3D domain. Also, we illustrate that 2D polarimetric images are noisier than 3D reconstructed polarimetric integral imaging. To the best of our knowledge, this is the first report on Mueller matrix polarimetry in 3D Integral Imaging.

5.
Opt Lett ; 44(9): 2326-2329, 2019 May 01.
Artigo em Inglês | MEDLINE | ID: mdl-31042221

RESUMO

A compact and field-portable three-dimensional (3D)-printed structured illumination (SI) digital holographic microscope based on shearing geometry is presented. By illuminating the sample using a SI pattern, the lateral resolution in both reconstructed phase and amplitude images can be improved up to twice the resolution provided by conventional illumination. The use of a 3D-printed system and shearing geometry reduces the complexity of the system, while providing high temporal stability. The experimental results for the USAF resolution target show a resolution improvement of a factor of two which corroborates the theoretical prediction. Resolution enhancement in phase imaging is also demonstrated by imaging a biological sample. To the best of our knowledge, this is the first report of a compact and field-portable SI digital holographic system based on shearing geometry.

6.
Biomed Opt Express ; 9(10): 4714-4729, 2018 Oct 01.
Artigo em Inglês | MEDLINE | ID: mdl-30319898

RESUMO

We propose methods to quantitatively calculate the fluctuation rate of red blood cells with nanometric axial and millisecond temporal sensitivity at the single-cell level by using time-lapse holographic cell imaging. For this quantitative analysis, cell membrane fluctuations (CMFs) were measured for RBCs stored at different storage times. Measurements were taken over the whole membrane for both the ring and dimple sections separately. The measurements show that healthy RBCs that maintain their discocyte shape become stiffer with storage time. The correlation analysis demonstrates a significant negative correlation between CMFs and the sphericity coefficient, which characterizes the morphological type of erythrocyte. In addition, we show the correlation results between CMFs and other morphological properties such as projected surface area, surface area, mean corpuscular volume, and mean corpuscular hemoglobin.

7.
Biomed Opt Express ; 9(6): 2779-2784, 2018 Jun 01.
Artigo em Inglês | MEDLINE | ID: mdl-30258690

RESUMO

Digital holographic microscopy is the state of the art quantitative phase imaging of micro-objects including living cells. It is an ideal tool to image and quantify cell thickness profiles with nanometer thickness resolution. Digital holographic techniques usually are implemented using a two-beam setup that may be bulky and may not be field portable. Self-referencing techniques provide compact geometry but suffer from a reduction of the field of view. Here, we discuss the development of a wavefront division digital holographic microscope providing the full field of view with a compact system. The proposed approach uses a wavefront division module consisting of two lenses. The developed microscope is tested experimentally by measuring the physical and mechanical properties of red blood cells.

8.
J Biophotonics ; 11(12): e201800116, 2018 12.
Artigo em Inglês | MEDLINE | ID: mdl-30027630

RESUMO

Cardiomyocytes derived from human pluripotent stem cells are a promising tool for disease modeling, drug compound testing, and cardiac toxicity screening. Bio-image segmentation is a prerequisite step in cardiomyocyte image analysis by digital holography (DH) in microscopic configuration and has provided satisfactory results. In this study, we quantified multiple cardiac cells from segmented 3-dimensional DH images at the single-cell level and measured multiple parameters describing the beating profile of each individual cell. The beating profile is extracted by monitoring dry-mass distribution during the mechanical contraction-relaxation activity caused by cardiac action potential. We present a robust two-step segmentation method for cardiomyocyte low-contrast image segmentation based on region and edge information. The segmented single-cell contains mostly the nucleus of the cell since it is the best part of the cardiac cell, which can be perfectly segmented. Clustering accuracy was assessed by a silhouette index evaluation for k-means clustering and the Dice similarity coefficient (DSC) of the final segmented image. 3D representation of single of cardiomyocytes. The cell contains mostly the nucleus section and a small area of cytoplasm.


Assuntos
Holografia/métodos , Informática/métodos , Miócitos Cardíacos/citologia , Análise de Célula Única , Razão Sinal-Ruído
9.
Opt Lett ; 43(14): 3261-3264, 2018 Jul 15.
Artigo em Inglês | MEDLINE | ID: mdl-30004481

RESUMO

We present an approach for optical sensing and detection in turbid water using multidimensional spatial-temporal domain integral imaging and dedicated signal processing algorithms. An optical signal is encoded using pseudorandom sequences, and an image sensor array is used to capture elemental image video sequences of light propagating through turbid water. Using the captured information, multidimensional image reconstruction followed by multi-dimensional correlation to detect the source signal is performed. We experimentally demonstrate scenarios in which turbidity causes conventional signal detection to fail, while our proposed multidimensional approach enables successful detection under the same turbidity conditions. Statistical analysis is provided to support the experimental results. To the best of our knowledge, this is the first report of using multidimensional integral imaging signal detection in turbid water conditions.

10.
Opt Express ; 26(11): 13938-13951, 2018 May 28.
Artigo em Inglês | MEDLINE | ID: mdl-29877439

RESUMO

We present spatial-temporal human gesture recognition in degraded conditions including low light levels and occlusions using passive sensing three-dimensional (3D) integral imaging (InIm) system and 3D correlation filters. The 4D (lateral, longitudinal, and temporal) reconstructed data is processed using a variety of algorithms including linear and non-linear distortion-invariant filters; and compared with previously reported space-time interest points (STIP) feature detector, 3D histogram of oriented gradients (3D HOG) feature descriptor, with a standard bag-of-features support vector machine (SVM) framework, etc. The gesture recognition results with different classification algorithms are compared using a variety of performance metrics such as receiver operating characteristic (ROC) curves, area under the curve (AUC), SNR, the probability of classification errors, and confusion matrix. Integral imaging video sequences of human gestures are captured under degraded conditions such as low light illumination and in the presence of partial occlusions. A four-dimensional (4D) reconstructed video sequence is computed that provides lateral and depth information of a scene over time i.e. (x, y, z, t). The total-variation denoising algorithm is applied to the signal to further reduce noise and preserve data in the video frames. We show that the 4D signal consists of decreased scene noise, partial occlusion removal, and improved SNR due to the computational InIm and/or denoising algorithms. Finally, gesture recognition is processed with classification algorithms, such as distortion-invariant correlation filters; and STIP, 3D HOG with SVM, which are applied to the reconstructed 4D gesture signal to classify the human gesture. Experiments are conducted using a synthetic aperture InIm system in ambient light. Our experiments indicate that the proposed approach is promising in detection of human gestures in degraded conditions such as low illumination conditions with partial occlusion. To the best of our knowledge, this is the first report on spatial-temporal human gesture recognition in degraded conditions using passive sensing 4D integral imaging with nonlinear correlation filters.


Assuntos
Gestos , Interpretação de Imagem Assistida por Computador/métodos , Imagem Tridimensional/métodos , Luz , Reconhecimento Automatizado de Padrão/métodos , Algoritmos , Humanos , Curva ROC , Análise Espaço-Temporal , Máquina de Vetores de Suporte
11.
Opt Express ; 26(8): 10981-10996, 2018 Apr 16.
Artigo em Inglês | MEDLINE | ID: mdl-29716026

RESUMO

The light field microscope has the potential of recording the 3D information of biological specimens in real time with a conventional light source. To further extend the depth of field to broaden its applications, in this paper, we proposed a multifocal high-resistance liquid crystal microlens array instead of the fixed microlens array. The developed multifocal liquid crystal microlens array can provide high quality point spread function in multiple focal lengths. By adjusting the focal length of the liquid crystal microlens array sequentially, the total working range of the light field microscope can be much extended. Furthermore, in our proposed system, the intermediate image was placed in the virtual image space of the microlens array, where the condition of the lenslets numerical aperture was considerably smaller. Consequently, a thin-cell-gap liquid crystal microlens array with fast response time can be implemented for time-multiplexed scanning.

12.
Opt Express ; 26(10): 13614-13627, 2018 May 14.
Artigo em Inglês | MEDLINE | ID: mdl-29801384

RESUMO

We present a spatio-temporal analysis of cell membrane fluctuations to distinguish healthy patients from patients with sickle cell disease. A video hologram containing either healthy red blood cells (h-RBCs) or sickle cell disease red blood cells (SCD-RBCs) was recorded using a low-cost, compact, 3D printed shearing interferometer. Reconstructions were created for each hologram frame (time steps), forming a spatio-temporal data cube. Features were extracted by computing the standard deviations and the mean of the height fluctuations over time and for every location on the cell membrane, resulting in two-dimensional standard deviation and mean maps, followed by taking the standard deviations of these maps. The optical flow algorithm was used to estimate the apparent motion fields between subsequent frames (reconstructions). The standard deviation of the magnitude of the optical flow vectors across all frames was then computed. In addition, seven morphological cell (spatial) features based on optical path length were extracted from the cells to further improve the classification accuracy. A random forest classifier was trained to perform cell identification to distinguish between SCD-RBCs and h-RBCs. To the best of our knowledge, this is the first report of machine learning assisted cell identification and diagnosis of sickle cell disease based on cell membrane fluctuations and morphology using both spatio-temporal and spatial analysis.


Assuntos
Anemia Falciforme/diagnóstico , Eritrócitos Anormais/patologia , Holografia/métodos , Imagem Tridimensional/métodos , Microscopia/métodos , Reconhecimento Automatizado de Padrão/métodos , Contagem de Eritrócitos , Membrana Eritrocítica/patologia , Humanos , Análise Espaço-Temporal
13.
Appl Opt ; 57(7): B184-B189, 2018 Mar 01.
Artigo em Inglês | MEDLINE | ID: mdl-29521988

RESUMO

We have developed a three-dimensional (3D) dynamic integral-imaging (InIm)-system-based optical see-through augmented reality display with enhanced depth range of a 3D augmented image. A focus-tunable lens is adopted in the 3D display unit to relay the elemental images with various positions to the micro lens array. Based on resolution priority integral imaging, multiple lenslet image planes are generated to enhance the depth range of the 3D image. The depth range is further increased by utilizing both the real and virtual 3D imaging fields. The 3D reconstructed image and the real-world scene are overlaid using an optical see-through display for augmented reality. The proposed system can significantly enhance the depth range of a 3D reconstructed image with high image quality in the micro InIm unit. This approach provides enhanced functionality for augmented information and adjusts the vergence-accommodation conflict of a traditional augmented reality display.

14.
Appl Opt ; 57(7): B190-B196, 2018 Mar 01.
Artigo em Inglês | MEDLINE | ID: mdl-29522009

RESUMO

We investigate the use of compact, lensless, single random phase encoding (SRPE) and double random phase encoding (DRPE) systems for automatic cell identification when multiple cells, either of the same or mixed classes, are in the field of view. A microscope glass slide containing the sample is inputted into the single or double random phase encoding system, which is then illuminated by a coherent or partially coherent light source generating a unique opto-biological signature (OBS) that is captured by an image sensor. Statistical features such as mean, standard deviation, skewness, kurtosis, entropy, and Pearson's correlation coefficient are extracted from the OBSs and used for cell identification with the random forest classifier. With the exception of the correlation coefficient, all features were extracted in both the spatial and frequency domains. Experiments are performed with single random phase encoding and double random phase encoding, and system analysis is presented to show the robustness and classification accuracy of the random phase encoding cell identification systems. The proposed systems are compact, as they are lensless and do not have spatial frequency bandwidth limitations due to the numerical aperture of a microscope objective lens. We demonstrate that cell identification is possible using both the SRPE and DRPE systems. While DRPE systems have been extensively used for image encryption, to the best of our knowledge, this is the first report on using DRPE for automated cell identification.

15.
Appl Opt ; 57(7): B197-B204, 2018 Mar 01.
Artigo em Inglês | MEDLINE | ID: mdl-29522021

RESUMO

We propose a compact imaging system that integrates an augmented reality head mounted device with digital holographic microscopy for automated cell identification and visualization. A shearing interferometer is used to produce holograms of biological cells, which are recorded using customized smart glasses containing an external camera. After image acquisition, segmentation is performed to isolate regions of interest containing biological cells in the field-of-view, followed by digital reconstruction of the cells, which is used to generate a three-dimensional (3D) pseudocolor optical path length profile. Morphological features are extracted from the cell's optical path length map, including mean optical path length, coefficient of variation, optical volume, projected area, projected area to optical volume ratio, cell skewness, and cell kurtosis. Classification is performed using the random forest classifier, support vector machines, and K-nearest neighbor, and the results are compared. Finally, the augmented reality device displays the cell's pseudocolor 3D rendering of its optical path length profile, extracted features, and the identified cell's type or class. The proposed system could allow a healthcare worker to quickly visualize cells using augmented reality smart glasses and extract the relevant information for rapid diagnosis. To the best of our knowledge, this is the first report on the integration of digital holographic microscopy with augmented reality devices for automated cell identification and visualization.


Assuntos
Diatomáceas/citologia , Holografia/métodos , Microscopia/instrumentação , Reconhecimento Automatizado de Padrão/métodos , Fitoplâncton/citologia , Dispositivos Eletrônicos Vestíveis , Desenho de Equipamento , Humanos , Imagem Tridimensional/métodos , Dispositivos Ópticos
16.
Appl Opt ; 57(7): IAO1-IAO2, 2018 Mar 01.
Artigo em Inglês | MEDLINE | ID: mdl-29522028

RESUMO

This special issue of Applied Optics contains selected papers from OSA's Imaging Congress with particular emphasis on work from mathematics in imaging, computational optical sensing and imaging, imaging systems and applications, and 3D image acquisition and display.

17.
Light Sci Appl ; 7: 48, 2018.
Artigo em Inglês | MEDLINE | ID: mdl-30839600

RESUMO

Digital holography (DH) has emerged as one of the most effective coherent imaging technologies. The technological developments of digital sensors and optical elements have made DH the primary approach in several research fields, from quantitative phase imaging to optical metrology and 3D display technologies, to name a few. Like many other digital imaging techniques, DH must cope with the issue of speckle artifacts, due to the coherent nature of the required light sources. Despite the complexity of the recently proposed de-speckling methods, many have not yet attained the required level of effectiveness. That is, a universal denoising strategy for completely suppressing holographic noise has not yet been established. Thus the removal of speckle noise from holographic images represents a bottleneck for the entire optics and photonics scientific community. This review article provides a broad discussion about the noise issue in DH, with the aim of covering the best-performing noise reduction approaches that have been proposed so far. Quantitative comparisons among these approaches will be presented.

18.
J Biomed Opt ; 22(12): 1-11, 2017 Dec.
Artigo em Inglês | MEDLINE | ID: mdl-29235271

RESUMO

Quantitative three-dimensional (3-D) imaging of living cells provides important information about the cell morphology and its time variation. Off-axis, digital holographic interference microscopy is an ideal tool for 3-D imaging, parameter extraction, and classification of living cells. Two-beam digital holographic microscopes, which are usually employed, provide high-quality 3-D images of micro-objects, albeit with lower temporal stability. Common-path digital holographic geometries, in which the reference beam is derived from the object beam, provide higher temporal stability along with high-quality 3-D images. Self-referencing geometry is the simplest of the common-path techniques, in which a portion of the object beam itself acts as the reference, leading to compact setups using fewer optical elements. However, it has reduced field of view, and the reference may contain object information. Here, we describe the development of a common-path digital holographic microscope, employing a shearing plate and converting one of the beams into a separate reference by employing a pin-hole. The setup is as compact as self-referencing geometry, while providing field of view as wide as that of a two-beam microscope. The microscope is tested by imaging and quantifying the morphology and dynamics of human erythrocytes.


Assuntos
Eritrócitos/citologia , Holografia , Microscopia de Interferência , Humanos
19.
Biomed Opt Express ; 8(10): 4466-4479, 2017 Oct 01.
Artigo em Inglês | MEDLINE | ID: mdl-29082078

RESUMO

In this paper, we present two models for automatically extracting red blood cells (RBCs) from RBCs holographic images based on a deep learning fully convolutional neural network (FCN) algorithm. The first model, called FCN-1, only uses the FCN algorithm to carry out RBCs prediction, whereas the second model, called FCN-2, combines the FCN approach with the marker-controlled watershed transform segmentation scheme to achieve RBCs extraction. Both models achieve good segmentation accuracy. In addition, the second model has much better performance in terms of cell separation than traditional segmentation methods. In the proposed methods, the RBCs phase images are first numerically reconstructed from RBCs holograms recorded with off-axis digital holographic microscopy. Then, some RBCs phase images are manually segmented and used as training data to fine-tune the FCN. Finally, each pixel in new input RBCs phase images is predicted into either foreground or background using the trained FCN models. The RBCs prediction result from the first model is the final segmentation result, whereas the result from the second model is used as the internal markers of the marker-controlled transform algorithm for further segmentation. Experimental results show that the given schemes can automatically extract RBCs from RBCs phase images and much better RBCs separation results are obtained when the FCN technique is combined with the marker-controlled watershed segmentation algorithm.

20.
J Opt Soc Am A Opt Image Sci Vis ; 34(10): 1776-1786, 2017 Oct 01.
Artigo em Inglês | MEDLINE | ID: mdl-29036047

RESUMO

In this work, a 3D reconstruction approach for flexible sensing inspired by integral imaging techniques is proposed. This method allows the application of different integral imaging techniques, such as generating a depth map or the reconstruction of images on a certain 3D plane of the scene that were taken with a set of cameras located at unknown and arbitrary positions and orientations. By means of a photo-consistency measure proposed in this work, all-in-focus images can also be generated by projecting the points of the 3D plane into the sensor planes of the cameras and thereby capturing the associated RGB values. The proposed method obtains consistent results in real scenes with different surfaces of objects as well as changes in texture and lighting.

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