In recent years, onion-like carbons (OLCs), as a new type of carbon nanostructure, have emerged as significant in biomedical fields. OLCs are capable of being internalized by cells, interacting with various organelles, and thereby influencing cellular physiological processes. Consequently, there is considerable interest in the rapid, non-invasive detection and statistical analysis of intracellular OLCs. Holographic flow cytometry provides a high-throughput, label-free imaging approach, introducing a new approach for detecting intracellular OLCs. Indeed, cells can act as biological lenses, and the presence of intracellular OLCs alters their refractive index distribution, affecting their optical focusing and lensing features. In this study, we merged the 3D refractive index distribution of cells, obtained through in-flow tomographic experiments, with appropriate numerical simulations. This combination demonstrates that intracellular OLCs can be effectively detected by analyzing 2D quantitative phase maps, without the need for additional manual labeling. The experiments were conducted on colon cancer cells, both with and without intracellular OLCs. The results indicate that the biolens properties of cells can serve as a valuable biomarker for detecting intracellular OLCs. This promotes the research on OLCs-related physiological processes using holographic flow cytometry, enabling high-throughput, non-invasive screening of statistically significant number of cells.
Cancer remains a significant global medical challenge, and the selection of effective treatment modalities is crucial for an optimistic prognosis. Photothermal therapy, being non-invasive and targeted, holds immense potential for future therapeutic developments. Due to their high biocompatibility, carbon nano-onions particles are frequently employed as photothermal materials. The investigation of the dynamic three-dimensional distribution of these nanoparticles within cancer cells is imperative for constructing an accurate photothermal conversion model. In this research, we employed digital holographic tomography to monitor the temporal changes in the three-dimensional distribution of onion-like carbon nanoparticles within colorectal cancer cells. We reconstructed the three-dimensional refractive index distribution of carbon nano-onions particles within cancer cells at different time points. Further, we quantified two morphological parameters, surface area and volume, of these nanoparticles within cancer cells and performed preliminary analysis of their temporal evolution. This methodology introduces a novel perspective to study the interaction between Carbon nano-onions particles and cancer cells, enhancing our understanding of the photothermal therapy mechanism.
For ovarian cancer patients, paclitaxel remains to be primary chemotherapy drug. Once drug resistance is developed, it will lead to tumor progression and metastasis during chemotherapy. Many studies have shown that the development of drug resistance in cancer cells can cause morphological changes. Digital holographic microscopy is an interferometric imaging technique that can obtain 3D quantitative morphological information of label-free cells. Combining with microfluidics enables high-throughput holographic image acquisition of suspended cells. In this work, four kinds of epithelial ovarian cancer cells with different drug sensitivity, SKOV3 cells, SKOV3_Ta_2μM cells, SKOV3_Ta_8μM cells, and SKOV3_Ta_20μM cells were studied. Several machine learning algorithms were used to perform multi-classification on the extracted morphological features of four types of cells. Then, we employ the SHapley Additive exPlanations (SHAP) method to interpret the classification model. The SHAP value of each feature is calculated and sorted to obtain the important morphological features.
Recently, advanced flow cytometry analysis technology based on digital holography has been extensively studied, which can meet various challenges in clinical diagnosis. Especially in liquid biopsy, it has incomparable advantages. Urothelial Holographic Flow Cytometry (HFC) microscopy can provide rich intracellular information by changing the cell’s intrinsic properties with label-free and high throughput. Carcinoma (UC) is the second most common malignancy in men. Urine cytology detection is the most convenient early cancer screening method for UC patients. Here, we developed HFC to identify the cancer cells in urine. Holographic microfluidic imaging was performed to obtain the phase images of different cells in simulation urine, including red blood cells, white blood cells, epithelial cells, and a small number of cancer cells. This study demonstrates that HFC can achieve high accuracy, high throughput, and label-free cancer cell identification in the urine.
We proposed a rapid autofocusing method exploiting holographic polarization microscope, which could determine the refocusing distance without multiple reconstructions and complex network training. The defocus distance of the object is calculated rapidly by identifying the separation distance of the two defocus images of the object and using the linear relation between the defocus distance of the object and the separation distance of the two defocus images of the object. The linear relationship is obtained by numerical propagation and linear fitting. Last, we have demonstrated the effectiveness of the proposed method by reconstructing the in-focus images of flowing cells. We believe that our proposed method could be a powerful tool for dynamic observation and extend the application of holographic polarization microscope.
In bone tissue, osteocytes are embedded within a microfluid-filled network which expose them to high levels of fluid shear stress (FSS). The osteocytes’ sensitivity to different levels of FSS has demonstrated. However, there are few attempts to image 3D cellular deformation under FSS by label-free and quantitative microscopy. Digital holographic (DH) microscopy is a powerful imaging technique that can provide rich intracellular information based on the refractive index (RI) contrast, without exogenous contrast agents. However, in DH image recording process, the recorded wave-front contains not only the object’s information but also the aberrations caused by the microscope objective (MO) and the imperfections of optical components of the system. The fitting-based numerical method removes total aberrations by detecting object-free background as reference surfaces. In this paper, we proposed a convolutional neural network (CNN) for multivariate regression to cope with the phase aberration compensation problem automatically thus allows performing long-term monitoring of bone cells morphological response under FSS. We transformed the problem of estimating the coefficients for fitting a phase aberration map to a regression problem. The aberrated phase images are put into this model which can automatically learns the internal features of phase aberrations. Then the optimal coefficients are estimated as an output of the network. Based on these coefficients, the phase aberration map is built by the polynomial fitting, and the phase aberrations are removed by subtracting the aberration phase image with the phase map. The trainning and validation set contain thousands of phase image of cells. The mean square error (MSE) is used as the loss function. Then, the trained model was used for aberrations compensation in the FFS experiment of osteocytes. The results show that the proposed approach can predict the optimal coefficients and automatically compensating the phase aberrations without detecting background regions and knowing any physical parameters.
Endometrial cancer is one of the most common gynecological malignancies. In endometrial cancer treatment, drug resistance test plays the vital role since different patients have different reactions to chemotherapy. Traditional methods of drug resistance test usually take a few days to obtain results, which will be quite a long time for patients waiting for cancer treatment. In this research, in order to quickly quantify the drug resistance of cancer cells, we managed to find some relationships between the dynamic changing processes and drug resistance of endometrial cancer cells. To accurately obtain and quantitatively analyze the dynamic processes, we utilized digital holographic microscopy (DHM) to retrieve phase maps of living cancer cells. Based on the real-time reconstructed phase maps, we reestablished the dynamic process of both the cisplatin-resistant cell (Ishikawa, ISK) and non-cisplatin-resistant cell (Ishikawa/CisR, ISKC). ISK and ISK-C were separately treated with cisplatin (0ug/ml, control; 5ug/ml, low concentration, LC; and 100ug/ml, high concentration, HC), and holograms of cells in each group were recorded by a DHM setup for 30min before and 150min after cisplatin treatment with a frame rate of one record every five second. Several morphological parameters, including cell height, cell projected area, and cell volume, were calculated from the retrieved phase maps and membrane fluctuations were analyzed both in temporal and spatial domains. Statistically significant differences in the changing processes were found between the two kinds of cells.
Living cells as phase objects require not only non-invasive measurement but also quantitative phase information during dynamic biopsy. Digital Holographic Microscopy (DHM), measuring three-dimensional morphology without changing the active condition of cells and in situ inspection, is becoming excellent tools for biology research. We have described a DHM method for quantitative, unlabeled observation of living cell subjected to fluid shear stress (FSS) in flowing fluid. The holographic recording system combined with the fluid shear system is improved. The numerical reconstruction technique firstly employed deep learning Convolutional Neural Network model filter, which achieved automatically processing large scale the spectrum of holograms immediately. Osteocytes as the experimental samples were observed and their morphological changes under the stimulation of FSS was successfully measured.
Digital holographic micro-tomography (DHMT) is widely used for three-dimensional (3-D) detections in biomedical research, from which the information of refractive indexes (RI) distributions of cells obtained can reflect some pathological states. When measuring cells, a capillary is usually used to contain and rotate them. The accuracy of diffraction tomography methods, which is commonly used, is likely to decrease when the object induces complex scattering effects, especially when measuring cell clusters. The nonlinear algorithm based on multi-slice wave propagation method (WPM) we proposed earlier is preferred in these situations. In this paper, we perform 3-D measurements of cell clusters using the setup-rotating system and the WPM-based nonlinear algorithm. Quantitative 3-D distributions of RI can be obtained accurately to display the structures of the cell clusters. The experimental results demonstrate that the WPM-based nonlinear algorithm can provide high accuracy for cell clusters.
Real-time micro-vibration measurement is widely used in engineering applications. It is very difficult for traditional optical detection methods to achieve real-time need in a relatively high frequency and multi-spot synchronous measurement of a region at the same time,especially at the nanoscale. Based on the method of heterodyne interference, an experimental system of real-time measurement of micro - vibration is constructed to satisfy the demand in engineering applications. The vibration response signal is measured by combing optical heterodyne interferometry and a high-speed CMOS-DVR image acquisition system. Then, by extracting and processing multiple pixels at the same time, four digital demodulation technique are implemented to simultaneously acquire the vibrating velocity of the target from the recorded sequences of images. Different kinds of demodulation algorithms are analyzed and the results show that these four demodulation algorithms are suitable for different interference signals. Both autocorrelation algorithm and cross-correlation algorithm meet the needs of real-time measurements. The autocorrelation algorithm demodulates the frequency more accurately, while the cross-correlation algorithm is more accurate in solving the amplitude.
Heterodyne interferometric vibration metrology is a useful technique for dynamic displacement and velocity measurement as it can provide a synchronous full-field output signal. With the advent of cost effective, high-speed real-time signal processing systems and software, processing of the complex signals encountered in interferometry has become more feasible. However, due to the coherent nature of the laser sources, the sequence of heterodyne interferogram are corrupted by a mixture of coherent speckle and incoherent additive noise, which can severely degrade the accuracy of the demodulated signal and the optical display. In this paper, a new heterodyne interferometric demodulation method by combining auto-correlation analysis and spectral filtering is described leading to an expression for the dynamic displacement and velocity of the object under test that is significantly more accurate in both the amplitude and frequency of the vibrating waveform. We present a mathematical model of the signals obtained from interferograms that contain both vibration information of the measured objects and the noise. A simulation of the signal demodulation process is presented and used to investigate the noise from the system and external factors. The experimental results show excellent agreement with measurements from a commercial Laser Doppler Velocimetry (LDV).
Due to the different purposes of image fusion, fusion approach taken is also different. For target identification, as a result of target feature of infrared and visible light image is different, in order to keep the high spatial resolution and rich texture information of visible light image, At the same time, make the target in the infrared image as prominent as possible. This paper uses a fusion algorithm based on Non-Subsampled Contourlet Transform (NSCT) and wavelet transform. After image NSCT decomposition, use of low frequency coefficient fusion algorithm based on wavelet transform, according to the characteristics of the fusion image the high frequency coefficients using the fusion rule based on region energy. The experimental results show that the fusion algorithm can keep the Spectral information of visible light image and the target information of infrared image better, with more details and clearer edges. The algorithm can obtain an ideal fusion image, which has a guiding effect on the target's interpretation, and its fusion effect is better than the conventional image fusion algorithm.
The image quality of optical diffraction tomography is likely to decline due to some key factors, including limited depth of focus, the rotational error and localized RI discontinuities. This paper describes reconstruction methods to circumvent these three factors for improved image quality. The limited depth of focus and the rotational error are addressed simultaneously with a method based on multiple numerical propagations. The localized RI discontinuities are addressed with a method based on separated tomographic reconstructions. Experimental results are demonstrated to verify the described methods. A four-core optical fiber and a large-mode photonic crystal fiber is measured and processed by the method based on multiple numerical propagations with improved image quality. The depth of field is significantly extended. Samples with different typical RI discontinuities, two kinds of fusion spliced optical fibers, are measured and reconstructed. While reconstructions by existing methods are heavily disturbed, the 3D maps obtained with the described method are free from spreading disturbance and show important structures as well as the positions and estimated shapes of the discontinuities. The described methods are of practical significance and will find important applications in 3D imaging of various objects.
In this paper, we report three-dimensional(3D) measurement results of structural parameters of fusion spliced optical fibers using digital holographic microtomography. A holographic setup in microscopy configuration with the sample-fixed and setup-rotating scheme is established. A series of holograms is recorded from various incident angles. Then the filtered backprojection algorithm is applied to reconstruct the 3D refractive index (RI) distributions of the fusion spliced optical fibers inserted in the index-matching liquid. Experimental results exhibit the internal and external shapes of three kinds of fusion splices between different fibers, including a single-mode fiber(SMF) and a multimode fiber, an SMF and a panda polarization maintaining fiber (Panda PMF), and an SMF and a bow-tie polarization maintaining fiber (Bow-Tie PMF). With 3D maps of RI, it is intuitive to observe internal structural details of fused fibers and evaluate the splicing quality. This paper describes a powerful method for non-invasive microscopic measurement of fiber splicing. Furthermore, it provides the possibility of detecting fiber splicing loss by 3D structures.
The coherent noise degrades the imaging quality and resolution in digital holographic interferometry. A method to reduce coherent noise by the way of slightly rotating object is proposed. Firstly, a series of digital holograms with different coherent noise patterns were recorded by slightly rotating object. Secondly, the different holograms were reconstructed individually, and the differences between the reconstructed complex amplitudes due to the rotation of the object were removed by using phase compensation and image registration algorithms. Thus, multiple identical retrieved images of object with different coherent noise distributions were obtained. Finally, the coherent noise was reduced by a proper averaging process for amplitude and phase images. Moreover, Non-correlation between two speckle patterns can be achieved by rotating very small angle proven by means of computing the correlation between the circle speckle spots. The experimental results and evaluations are given to confirm the proposed method.
An automatic focus determination method in digital holography that utilizes the cosine score (CS) of the inner angle between the vectors that result from adjacent axial reconstructed amplitude images is proposed. This method is based on the fact that the optical field near the focus plane contains more regular features of an object than the defocused region. Further, a modified CS (MCS) autofocusing method is proposed to extend the application range and improve the performance of the proposed method. First, a low-pass filter is designed for the object term holograms in the frequency domain. Second, the standardized Z-scores method is applied along the axis to the amplitude images reconstructed from the filtered hologram. Finally, the MCS of the standardized amplitude images is calculated by an improved cosine-like formula. Next, the focus plane is found at the minimum MCS for different types of objects. This method enables accurate focus determination for all types of objects, as well as for the image region with a slow change or small size, which offers time savings and the precise autofocusing of objects with large longitudinal volumes. The simulations and experimental results on a United States Air Force resolution chart and living cells are presented, illustrating the efficiency and potential of the methods.
We propose a micro-vibration detection method by introducing heterodyne interferometry to time-averaged holography. This method compensates for the deficiency of time-average holography in quantitative measurements and widens its range of application effectively. Acousto-optic modulators are used to modulate the frequencies of the reference beam and the object beam. Accurate detection of the maximum amplitude of each point in the vibration plane is performed by altering the frequency difference of both beams. The range of amplitude detection of plane vibration is extended. In the stable vibration mode, the distribution of the maximum amplitude of each point is measured and the fitted curves are plotted. Hence the plane vibration mode of the object is demonstrated intuitively and detected quantitatively. We analyzed the method in theory and built an experimental system with a sine signal as the excitation source and a typical piezoelectric ceramic plate as the target. The experimental results indicate that, within a certain error range, the detected vibration mode agrees with the intrinsic vibration characteristics of the object, thus proving the validity of this method.
In the development and production process of laser gyros, reflective mirrors have always been a core component, as they are directly related to the performance of laser gyros. Besides, surface profile deviation and surface defects of mirrors may lead to irreversible serious damages to gyros. In order to achieve effective three-dimensional (3D) quantitative measurements of their surface profiles and defects, we adopt digital holographic microscopy (DHM). Using a DHM system with multiple magnifications and the aberration compensation method, we obtained 3D profile images and estimated the precise quantitative sizes of not only a profile with an aperture of 6.41 mm and a curvature radius of 8.39 m, but also a scratch with a line-equivalent width of 0.45μm and an equivalent depth of 137.28 nm and a pit with an equivalent diameter of 0.86μm and an equivalent depth of 42.95 nm. These results demonstrate that the method is feasible and effective to meet the requirements of engineering practice.
This paper presents a synchronous multipoint velocity profile measurement system, which acquires the vibration velocities as well as images of vibrating objects by combining optical heterodyne interferometry and a high-speed CMOS-DVR camera. The high-speed CMOS-DVR camera records a sequence of images of the vibrating object. Then, by extracting and processing multiple pixels at the same time, a digital demodulation technique is implemented to simultaneously acquire the vibrating velocity of the target from the recorded sequences of images. This method is validated with an experiment. A piezoelectric ceramic plate with standard vibration characteristics is used as the vibrating target, which is driven by a standard sinusoidal signal.
An autofocusing method is proposed that utilizes cosine score of inner angle between the vectors resulted from vectoring the axial adjacent reconstructed images in digital holography. It is based on the fact that the images near the focus contain more regular features of object than in the defocused region, therefore, the neighboring reconstructed images are more similar to each other at the focus position than defocused and a cosine score is employed to evaluate such similarity. However, the cosine scores between the axial adjacent amplitude images are so close that it is difficult to distinguish the extremum. Therefore, a modified cosine algorithm is presented to offset such problem on consideration of the correlation of the elements, by subtracting the inner product term from the denominator of the cosine algorithm. The cosine and modified cosine score based autofocusing method procedure is first introduced, and then it is utilized in simulation and real holographic data. In simulation, it precisely judges out the actual recording distance and the focus curve shows good focus function criteria, which verifies the method as an ideal circumstance. In real experiment, it can easily search out the focus distance from the focus curve, and it shows good focus judgement ability than most traditional focus metrics selected. Therefore, the feasibility and validation of the proposed autofocusing method are proved by simulation and experiment results.
An effective method based on the Fresnel transform method and rotational transformation for improving the image
quality on the condition of the arbitrarily tilted recording planes is proposed. As a kind of numerical reconstruction for
digital holography, Fresnel transform method has already been the most commonly used method. Rotational
transformation in Fourier space is an effective technique for simulating optical diffraction between nonparallel planes. In
addition to a FTM, the method requires performing a fast Fourier transform twice and a single Rotational Transformation,
which enables it to have the advantage of fast calculation. The effectiveness of the proposed method is demonstrated by
experiment, in which the distortion caused by the tilting of the object is removed.
A method of digital holography for high-resolution microscopy at long working distance is proposed using a synthetic
aperture. A series of digital holograms covered different spatial frequency ranges of an object optical field are recorded
by using different tilted object illuminations. Subsequently, the intensity images are numerically reconstructed and
magnified respectively. Finally, a synthetic image with the resolution improved and speckle noise suppressed is obtained
by synthesizing these reconstructed images. The results show that the proposed method can be easily used to in-situ
microscope at a long working distance.
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