14 research outputs found

    Characterization of color cross-talk of CCD detectors and its influence in multispectral quantitative phase imaging

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    Multi-spectral quantitative phase imaging (QPI) is an emerging imaging modality for wavelength dependent studies of several biological and industrial specimens. Simultaneous multi-spectral QPI is generally performed with color CCD cameras. However, color CCD cameras are suffered from the color crosstalk issue, which needed to be explored. Here, we present a new approach for accurately measuring the color crosstalk of 2D area detectors, without needing prior information about camera specifications. Color crosstalk of two different cameras commonly used in QPI, single chip CCD (1-CCD) and three chip CCD (3-CCD), is systematically studied and compared using compact interference microscopy. The influence of color crosstalk on the fringe width and the visibility of the monochromatic constituents corresponding to three color channels of white light interferogram are studied both through simulations and experiments. It is observed that presence of color crosstalk changes the fringe width and visibility over the imaging field of view. This leads to an unwanted non-uniform background error in the multi-spectral phase imaging of the specimens. It is demonstrated that the color crosstalk of the detector is the key limiting factor for phase measurement accuracy of simultaneous multi-spectral QPI systems.Comment: 16 pages, 8 figure

    High space-bandwidth in quantitative phase imaging using partially spatially coherent optical coherence microscopy and deep neural network

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    Quantitative phase microscopy (QPM) is a label-free technique that enables to monitor morphological changes at subcellular level. The performance of the QPM system in terms of spatial sensitivity and resolution depends on the coherence properties of the light source and the numerical aperture (NA) of objective lenses. Here, we propose high space-bandwidth QPM using partially spatially coherent optical coherence microscopy (PSC-OCM) assisted with deep neural network. The PSC source synthesized to improve the spatial sensitivity of the reconstructed phase map from the interferometric images. Further, compatible generative adversarial network (GAN) is used and trained with paired low-resolution (LR) and high-resolution (HR) datasets acquired from PSC-OCM system. The training of the network is performed on two different types of samples i.e. mostly homogenous human red blood cells (RBC) and on highly heterogenous macrophages. The performance is evaluated by predicting the HR images from the datasets captured with low NA lens and compared with the actual HR phase images. An improvement of 9 times in space-bandwidth product is demonstrated for both RBC and macrophages datasets. We believe that the PSC-OCM+GAN approach would be applicable in single-shot label free tissue imaging, disease classification and other high-resolution tomography applications by utilizing the longitudinal spatial coherence properties of the light source

    Label-free imaging on waveguide platform with enhanced resolution and contrast

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    Chip-based Evanescent Light Scattering (cELS) utilizes the multiple modes of a high-index contrast optical waveguide for near-field illumination of unlabeled samples, thereby repositioning the highest spatial frequencies of the sample into the far-field. The multiple modes scattering off the sample with different phase differences is engineered to have random spatial distributions within the integration time of the camera, mitigating the coherent speckle noise. This enables label-free superior-contrast imaging of weakly scattering nanosized specimens such as extra-cellular vesicles (EVs) and liposomes, dynamics of living HeLa cells etc. We demonstrate a multi-moded straight waveguide as a partially coherent light source. For isotropic super-resolution, spatially incoherent light engineered via multiple-arms waveguide chip and intensity-fluctuation based algorithms are used. The proof-of-concept results are demonstrated on 100 nm polystyrene beads and resolution improvement of close to 2× is shown. cELS also realizes (2-10)× more contrast as opposed to conventional imaging techniques

    Unbalanced low coherence interference microscopy

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    Low coherence interference microscopy (LCIM) provides high spatial phase sensitivity, i.e., speckle free and coherent noise free quantitative phase images of the test specimens. Due to low temporal coherence (TC) length of the light source, LCIM requires precise adjustment of the optical path difference (OPD) between the object and the reference arm, which is only a few micrometers. Consequently, previously demonstrated LCIM systems are implemented with the use of identical objective lenses in both the arms and also known as balanced interferometric configuration. The use of identical objective lens hinders both the use of high numerical aperture objective lens and also the swift change of the objective lens during imaging. In the present work, LCIM is implemented with non-identical objective lenses in the object and the reference arm also called unbalanced optical configuration. A range of objective lenses 10 × /0.25NA, 20 × /0.45NA and 60 × /1.2NA are employed in the object arm of the system while keeping single objective lens 10 × /0.25NA in the reference arm. To resolve the challenges associated with unbalanced configuration, advanced iterative algorithm (AIA) and principal component analysis (PCA) algorithms are integrated to recover quadratic phase error free phase images of the test specimens. The capabilities of the proposed method are exhibited on various specimens like USAF resolution, step-like test object and for the biological cells, HeLa cells. The proposed approach enables scalable magnification and resolution by simply rotating the imaging objective turret without the need of changing objective lens in the reference arm

    Highly temporal stable, wavelength-independent, and scalable field-of-view common-path quantitative phase microscope

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    Significance: High temporal stability, wavelength independency, and scalable field of view (FOV) are the primary requirements of a quantitative phase microscopy (QPM) system. The high temporal stability of the system provides accurate measurement of minute membrane fluctuations of the biological cells that can be an indicator of disease diagnosis. Aim: The main aim of this work is to develop a high temporal stable technique that can accurately quantify the cell’s dynamics such as membrane fluctuations of human erythrocytes. Further, the technique should be capable of acquiring scalable FOV and resolution at multiple wavelengths to make it viable for various biological applications. Approach: We developed a single-element nearly common path, wavelength-independent, and scalable resolution/FOV QPM system to obtain temporally stable holograms/interferograms of the biological specimens. Results: With the proposed system, the temporal stability is obtained ∼15  mrad without using any vibration isolation table. The capability of the proposed system is first demonstrated on USAF resolution chart and polystyrene spheres (4.5-μm diameter). Further, the system is implemented for single shot, wavelength-independent quantitative phase imaging of human red blood cells (RBCs) with scalable resolution using color CCD camera. The membrane fluctuation of healthy human RBCs is also measured and was found to be around 47 nm. Conclusions: Contrary to its optical counterparts, the present system offers an energy efficient, cost effective, and simple way of generating object and reference beam for the development of common-path QPM. The present system provides the flexibility to the user to acquire multi-wavelength quantitative phase images at scalable FOV and resolution

    Sub-nanometer height sensitivity by phase shifting interference microscopy under environmental fluctuations

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    Phase shifting interferometric (PSI) techniques are among the most sensitive phase measurement methods. Owing to its high sensitivity, any minute phase change caused due to environmental instability results into, inaccurate phase measurement. Consequently, a well calibrated piezo electric transducer (PZT) and highly-stable environment is mandatory for measuring accurate phase map using PSI implementation. Here, we present an inverse approach, which can retrieve phase maps of the samples with negligible errors under environmental fluctuations. The method is implemented by recording a video of continuous temporally phase shifted interferograms and phase shifts were calculated between all the data frames using Fourier transform algorithm with a high accuracy ≤ 5.5 × 10−4 π rad. To demonstrate the robustness of the proposed method, a manual translation of the stage was employed to introduce continuous temporal phase shift between data frames. The developed algorithm is first verified by performing quantitative phase imaging of optical waveguide and red blood cells using uncalibrated PZT under the influence of vibrations/air turbulence and compared with the well calibrated PZT results. Furthermore, we demonstrated the potential of the proposed approach by acquiring the quantitative phase imaging of an optical waveguide with a rib height of only 2 nm and liver sinusoidal endothelial cells (LSECs). By using 12-bit CMOS camera the height of shallow rib waveguide is measured with a height sensitivity of 4 Å without using PZT and in presence of environmental fluctuations

    Deriving high contrast fluorescence microscopy images through low contrast noisy image stacks

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    Contrast in fluorescence microscopy images allows for the differentiation between different structures by their difference in intensities. However, factors such as point-spread function and noise may reduce it, affecting its interpretability. We identified that fluctuation of emitters in a stack of images can be exploited to achieve increased contrast when compared to the average and Richardson-Lucy deconvolution. We tested our methods on four increasingly challenging samples including tissue, in which case results were comparable to the ones obtained by structured illumination microscopy in terms of contrast

    Partially spatially coherent digital holographic microscopy and machine learning for quantitative analysis of human spermatozoa under oxidative stress condition

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    Semen quality assessed by sperm count and sperm cell characteristics such as morphology and motility, is considered to be the main determinant of men’s reproductive health. Therefore, sperm cell selection is vital in assisted reproductive technology (ART) used for the treatment of infertility. Conventional bright field optical microscopy is widely utilized for the imaging and selection of sperm cells based on the qualitative analysis by experienced clinicians. In this study, we report the development of a highly sensitive quantitative phase microscopy (QPM) using partially spatially coherent light source, which is a label-free, non-invasive and high-resolution technique to quantify various biophysical parameters. The partial spatial coherence nature of light source provides a significant improvement in spatial phase sensitivity and hence reconstruction of the phase of the entire sperm cell is demonstrated, which was otherwise not possible using highly spatially coherent light source. High sensitivity of the system enables quantitative phase imaging of the specimens having very low refractive index contrast with respect to the medium like tail of the sperm cells. Further, it also benefits with accurate quantification of 3D-morphological parameters of sperm cells which might be helpful in the infertility treatment. The quantitative analysis of more than 2500 sperm cells under hydrogen peroxide (H2O2) induced oxidative stress condition is demonstrated. It is further correlated with motility of sperm cell to study the effect of oxidative stress on healthy sperm cells. The results exhibit a decrease in the maximum phase values of the sperm head as well as decrease in the sperm cell’s motility with increasing oxidative stress, i.e., H2O2 concentration. Various morphological and texture parameters were extracted from the phase maps and subsequently support vector machine (SVM) based machine learning algorithm is employed for the classification of the control and the stressed sperms cells. The algorithm achieves an area under the receiver operator characteristic (ROC) curve of 89.93% based on the all morphological and texture parameters with a sensitivity of 91.18%. The proposed approach can be implemented for live sperm cells selection in ART procedure for the treatment of infertility

    Rationality of the Capital Market: Capitalistic System vs. Islamic System

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    <p><b>Abstract</b></p> <p>Efficient Market Hypothesis (EMH) is founded on the theory of expected rationality but the theory of behavioural finance concludes that stock market investors are quasi-rational. Therefore, under the capitalistic system, the efficient markets have already failed to protect the rights of investors that have led to chronic capital market crashes and failure to achieve efficiency, justice, fairness, accountability, fair distribution of benefits, and a rational behaviour among investors. However, recently, Islamic financial institutions and markets have been emerging, which stand on the <i>Shariah</i> provision – the guided way to behave rationally or guided rationality. Based on the empirical experiences and evidences of both market systems, this paper discusses and compares the performances of the markets under the theoretical arguments of “rationality”, “quasi-rationality”, and “guided rationality”. This paper suggests that capital market based on guided rationality under the Islamic System can be a better alternative over the conventional market system.</p

    Lulworthinone: In Vitro Mode of Action Investigation of an Antibacterial Dimeric Naphthopyrone Isolated from a Marine Fungus

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    Treatment options for infections caused by antimicrobial-resistant bacteria are rendered ineffective, and drug alternatives are needed—either from new chemical classes or drugs with new modes of action. Historically, natural products have been important contributors to drug discovery. In a recent study, the dimeric naphthopyrone lulworthinone produced by an obligate marine fungus in the family Lulworthiaceae was discovered. The observed potent antibacterial activity against Gram-positive bacteria, including several clinical methicillin-resistant Staphylococcus aureus (MRSA) isolates, prompted this follow-up mode of action investigation. This paper aimed to characterize the antibacterial mode of action (MOA) of lulworthinone by combining in vitro assays, NMR experiments and microscopy. The results point to a MOA targeting the bacterial membrane, leading to improper cell division. Treatment with lulworthinone induced an upregulation of genes responding to cell envelope stress in Bacillus subtilis. Analysis of the membrane integrity and membrane potential indicated that lulworthinone targets the bacterial membrane without destroying it. This was supported by NMR experiments using artificial lipid bilayers. Fluorescence microscopy revealed that lulworthinone affects cell morphology and impedes the localization of the cell division protein FtsZ. Surface plasmon resonance and dynamic light scattering assays showed that this activity is linked with the compound‘s ability to form colloidal aggregates. Antibacterial agents acting at cell membranes are of special interest, as the development of bacterial resistance to such compounds is deemed more difficult to occur
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