Characterizing the consistency of motion of spermatozoa through nanoscale motion tracing.

OBJECTIVE: To demonstrate nanoscale motion tracing of spermatozoa and present analysis of the motion traces to characterize the consistency of motion of spermatozoa as a complement to progressive motility analysis. DESIGN: Anonymized sperm samples videographed under quantitative phase microscope, followed by generating and analyzing super-resolution motion traces of individual spermatozoa. SUBJECTS: Centrifuged human sperm samples. MAIN OUTCOME MEASURES: Precision of motion trace of individual sperms, presence of helical pattern in the motion trace, and mean and standard deviations of helical periods and radii of sperm motion traces, speed of progression. RESULTS: Spatially sensitive quantitative phase imaging with a super-resolution computational technique MUltiple SIgnal Classification ALgorithm (MUSICAL) allowed achieving motion precision of 340 nm using 10×, 0.25 NA lens whereas the diffraction limited resolution at this setting was 1320 nm. The motion traces thus derived facilitated new kinematic features of sperm, namely the statistics of helix period and radii per sperm. Through the analysis, 47 sperms with speed >25 µm/sec randomly selected from the same healthy donor's semen sample, it is seen that the kinematic features did not correlate with the speed of the sperms. Also, it is noted that spermatozoa may experience changes in the periodicity and radius of the helical path over time. Further, some very fast sperms (for example >70 µm/sec) may demonstrate irregular motion, needs further investigation. Presented computational analysis can be used directly for sperm samples from both fertility patients with normal and abnormal sperm cell conditions. We note that MUSICAL is an image analysis technique which may vaguely fall under machine learning category, but the conventional metrics for reporting found in EQUATOR do not apply. Alternative suitable metrics are reported, and bias is avoided through random selection of regions for analysis. Detailed methods are included for reproducibility. CONCLUSION: Kinematic features derived from nanoscale motion traces of spermatozoa contain information complementary to the speed of the sperms, allowing further distinction among the progressively motile sperms. Some highly progressive spermatozoa may have irregular motion pattern, and whether irregularity of motion indicate poor quality regarding artificial insemination needs further investigation. Presented technique can be generalized for sperm analysis for a variety of fertility conditions.

Compact Linnik-type hyperspectral quantitative phase microscope for advanced classification of cellular components.

Hyperspectral quantitative phase microscopy (HS-QPM) involves the acquisition of phase images across narrow spectral bands, which enables wavelength-dependent study of different biological samples. In the present work, a compact Linnik-type HS-QPM system is developed to reduce the instability and complexity associated with conventional HS-QPM techniques. The use of a single objective lens for both reference and sample arms makes the setup compact. The capabilities of the system are demonstrated by evaluating the HS phase map of both industrial and biological specimens. Phase maps of exfoliated cheek cells at different wavelengths are stacked to form a HS phase cube, adding spectral dimensionality to spatial phase distribution. Analysis of wavelength response of different cellular components are performed using principal component analysis to identify dominant spectral features present in the HS phase dataset. Findings of the study emphasize on the efficiency and effectiveness of HS-QPM for advancing cellular characterization in biomedical research and clinical applications.

Plasmonic nano-bowls for monitoring intra-membrane changes in liposomes, and DNA-based nanocarriers in suspension.

Programmable nanoscale carriers, such as liposomes and DNA, are readily being explored for personalized medicine or disease prediction and diagnostics. The characterization of these nanocarriers is limited and challenging due to their complex chemical composition. Here, we demonstrate the utilization of surface-enhanced Raman spectroscopy (SERS), which provides a unique molecular fingerprint of the analytes while reducing the detection limit. In this paper, we utilize a silver coated nano-bowl shaped polydimethylsiloxane (PDMS) SERS substrate. The utilization of nano-bowl surface topology enabled the passive trapping of particles by reducing mobility, which results in reproducible SERS signal enhancement. The biological nanoparticles' dwell time in the nano-trap was in the order of minutes, thus allowing SERS spectra to remain in their natural aqueous medium without the need for drying. First, the geometry of the nano-traps was designed considering nanosized bioparticles of 50-150 nm diameter. Further, the systematic investigation of maximum SERS activity was performed using rhodamine 6 G as a probe molecule. The potential of the optimized SERS nano-bowl is shown through distinct spectral features following surface- (polyethylene glycol) and bilayer- (cholesterol) modification of empty liposomes of around 140 nm diameter. Apart from liposomes, the characterization of the highly crosslinked DNA specimens of only 60 nm in diameter was performed. The modification of DNA gel by liposome coating exhibited unique signatures for nitrogenous bases, sugar, and phosphate groups. Further, the unique sensitivity of the proposed SERS substrate displayed distinct spectral signatures for DNA micelles and drug-loaded DNA micelles, carrying valuable information to monitor drug release. In conclusion, the findings of the spectral signatures of a wide range of molecular complexes and chemical morphology of intra-membranes in their natural state highlight the possibilities of using SERS as a sensitive and instantaneous characterization alternative.

Birefringence mapping of biological tissues based on polarization sensitive non-interferometric quantitative phase imaging technique.

OBJECTIVE: Oral cancer is a leading cause of mortality globally, particularly affecting developing regions where oral hygiene is often overlooked. The optical properties of tissues are vital for diagnostics, with polarization imaging emerging as a label-free, contrast-enhancing technique widely employed in medical and scientific research over past few decades. MATERIALS AND METHODS: We present a novel polarization sensitive quantitative phase imaging of biological tissues by incorporating the conventional polarization microscope and transport of intensity equation-based phase retrieval algorithm. This integration provides access to the birefringence mapping of biological tissues. The inherent optical anisotropy in biological tissues induces the polarization dependent refractive index variations which can provide the detailed insights into the birefringence characteristics of their extracellular constituents. Experimental investigations were conducted on both normal and cancerous oral tissue samples by recording a set of three polarization intensity images for each case with a step size of 2 µm. RESULTS: A noteworthy increment in birefringence quantification was observed in cancerous as compared to the normal tissues, attributed to the proliferation of abnormal cells during cancer progression. The mean birefringence values were calculated for both normal and cancerous tissues, revealing a significant increase in birefringence of cancerous tissues (2.1 ± 0.2) × 10-2 compared to normal tissues (0.8 ± 0.2) × 10-2. Data were collected from 8 patients in each group under identical experimental conditions. CONCLUSION: This polarization sensitive non-interferometric optical approach demonstrated effective discrimination between cancerous and normal tissues, with various parameters indicating elevated values in cancerous tissues.

High-resolution cell imaging using white light phase shifting interferometry and iterative phase deconvolution.

An optimization algorithm is presented for the deconvolution of a complex field to improve the resolution and accuracy of quantitative phase imaging (QPI). A high-resolution phase map can be recovered by solving a constrained optimization problem of deconvolution using a complex gradient operator. The method is demonstrated on phase measurements of samples using a white light based phase shifting interferometry (WLPSI) method. The application of the algorithm on real and simulated objects shows a significant resolution and contrast improvement. Experiments performed on Escherichia coli bacterium have revealed its sub-cellular structures that were not visible in the raw WLPSI images obtained using a five phase shifting method. These features can give valuable insights into the structures and functioning of biological cells. The algorithm is simple in implementation and can be incorporated into other QPI modalities .

Multispectral polarization microscopy of different stages of human oral tissue: A polarization study.

Many optical techniques have been used in various diagnostics and biomedical applications since a decade and polarization imaging is one of the non-invasive and label free optical technique to investigate biological samples making it an important tool in diagnostics, biomedical applications. We report a multispectral polarization-based imaging of oral tissue by utilizing a polarization microscope system with a broadband-light source. Experiments were performed on oral tissue samples and multispectral Stokes mapping was done by recording a set of intensity images. Polarization-based parameters like degree of polarization, angle of fast axis, retardation and linear birefringence have been retrieved. The statistical moments of these polarization components have also been reported at multiples wavelengths. The polarimetric properties of oral tissue at different stages of cancer have been analyzed and significant changes from normal to pre-cancerous lesions to the cancerous are observed in linear birefringence quantification as (1.7 ± 0.1) × 10-3 , (2.5 ± 0.2) × 10-3 and (3.3 ± 0.2) × 10-3 respectively.

Effect of fluorescein dye concentration in oral cancer tissue: Statistical and spectroscopic analysis.

Oral cancer screening with exogenous agents is highly demanding due to high sensitivity, as the early diagnosis plays a vital role in achieving favorable outcomes for oral squamous cell carcinomas (OSCC) by facilitating prompt detection and comprehensive surgical removal. Optical techniques utilizing the local application of fluorescein dye or fluorescence-guided surgery offer potential for early OSCC detection. The use of fluorescein dye in oral cancer is significantly less, and there is a need to inspect the local application of fluorescein dye in oral cancer patients. Concentration-based investigations of the dye with OSCC patients are essential to ensure accurate fluorescence-guided surgery and screening with fluorescein labeling and to mitigate possible adverse effects. Additionally, analyzing the dye distribution within OSCC tissues can provide insights into their heterogeneity, a critical indicator of malignancy. The present study includes a concentration-based statistical and spectroscopic analysis of fluorescein dye in ex-vivo and in-vivo OSCC patients. In the ex-vivo examination of OSCC tissues, five concentrations (18.66 ± 0.06, 9.51 ±    0.02, 6.38 ± 0.01, 4.80 ± 0.004, and 3.85 ± 0.002 millimolar) are employed for optical analysis. The ex-vivo OSCC tissues are analyzed for multiple statistical parameters at all concentrations, and the results are thoroughly described. Additionally, spectroscopic analysis is conducted on all concentrations for a comprehensive evaluation. Following optical analysis of all five concentrations in the ex-vivo study, two concentrations, 6.38 ± 0.01 and 4.80 ± 0.004 millimolar, are identified as suitable for conducting in-vivo investigations of oral cancer. A detailed spectroscopic and statistical study of OSCC tissues in-vivo has been done using these two concentrations.

Multimodal fluorescence imaging and spectroscopic techniques for oral cancer screening: a real-time approach.

The survival rate of oral squamous cell carcinoma (OSCC) patients is very poor, but it can be improved using highly sensitive, specific, and accurate techniques. Autofluorescence and fluorescence techniques are very sensitive and helpful in cancer screening; being directly linked with the molecular levels of human tissue, they can be used as a quantitative tool for cancer detection. Here, we report the development of multi-modal autofluorescence and fluorescence imaging and spectroscopic (MAF-IS) smartphone-based systems for fast and real-time oral cancer screening. MAF-IS system is indigenously developed and offers the advantages of being a low-cost, handy, non-contact, non-invasive, and easily operable device that can be employed in hospitals, including low-resource settings. In this study, we report the results of 43 individuals with 28 OSCC and 15 oral potentially malignant disorders (OPMDs), i.e., epithelial dysplasia and oral submucous fibrosis, using the developed devices. We observed a red shift in fluorescence emission spectrain vivo. We found red-shift of 7.72 ± 6 nm, 3 ± 4.36 nm, and 1.33 ± 0.47 nm in the case of OSCC, epithelial dysplasia, and oral submucous fibrosis, respectively, compared to normal. The results were compared with histopathology and found to be consistent. Further, the MAF-IS system provides results in real-time with higher accuracy and sensitivity compared to devices using a single modality. Our system can achieve an accuracy of 97% with sensitivity and specificity of 100% and 94.7%, respectively, even with a smaller number of patients (28 patients of OSCC). The proposed MAF-IS device has great potential for fast screening and diagnosis of oral cancer in the future.

Single-shot multispectral quantitative phase imaging of biological samples using deep learning.

Multispectral quantitative phase imaging (MS-QPI) is a high-contrast label-free technique for morphological imaging of the specimens. The aim of the present study is to extract spectral dependent quantitative information in single-shot using a highly spatially sensitive digital holographic microscope assisted by a deep neural network. There are three different wavelengths used in our method: λ=532, 633, and 808 nm. The first step is to get the interferometric data for each wavelength. The acquired datasets are used to train a generative adversarial network to generate multispectral (MS) quantitative phase maps from a single input interferogram. The network was trained and validated on two different samples: the optical waveguide and MG63 osteosarcoma cells. Validation of the present approach is performed by comparing the predicted MS phase maps with numerically reconstructed (F T+T I E) phase maps and quantifying with different image quality assessment metrices.

SERS Nanowire Chip and Machine Learning-Enabled Classification of Wild-Type and Antibiotic-Resistant Bacteria at Species and Strain Levels.

Antimicrobial resistance (AMR) is a major health threat worldwide and the culture-based bacterial detection methods are slow. Surface-enhanced Raman spectroscopy (SERS) can be used to identify target analytes in real time with sensitivity down to the single-molecule level, providing a promising solution for the culture-free bacterial detection. We report the fabrication of SERS substrates having tightly packed silver (Ag) nanoparticles loaded onto long silicon nanowires (Si NWs) grown by the metal-assisted chemical etching (MACE) method for the detection of bacteria. The optimized SERS chips exhibited sensitivity down to 10-12 M concentration of R6G molecules and detected reproducible Raman spectra of bacteria down to a concentration of 100 colony forming units (CFU)/mL, which is a thousand times lower than the clinical threshold of bacterial infections like UTI (105 CFU/mL). A Siamese neural network model was used to classify SERS spectra from bacteria specimens. The trained model identified 12 different bacterial species, including those which are causative agents for tuberculosis and urinary tract infection (UTI). Next, the SERS chips and another Siamese neural network model were used to differentiate AMR strains from susceptible strains of Escherichia coli (E. coli). The enhancement offered by SERS chip-enabled acquisitions of Raman spectra of bacteria directly in the synthetic urine by spiking the sample with only 103 CFU/mL E. coli. Thus, the present study lays the ground for the identification and quantification of bacteria on SERS chips, thereby offering a potential future use for rapid, reproducible, label-free, and low limit detection of clinical pathogens.

Label-free high-resolution white light quantitative phase nanoscopy system.

We present a high-resolution white light quantitative phase nanoscopy (WLQPN) system that can be utilized to visualize nanoparticles and subcellular features of the biological specimens. The five-phase shifting technique, along with deconvolution, is adopted to obtain super-resolution in phase imaging. The phase shifting technique can provide full detector resolution, making it beneficial as compared to the well-known Fourier analysis method. The Fourier transform method requires minimum angle of sin - 1 3 f x λ , where f x is maximum achievable spatial frequency. It limits the highest achievable resolution to much below the actual diffraction limit of the system. Thus, to obtain a high-resolution phase map of the biological specimen, a two-step process is adopted. First, the phase map is recovered using the five-phase shifting algorithm, with full detector spatial resolution. Second, the complex field is obtained from the recovered phase map and further processed using the Richardson Lucy total variation deconvolution algorithm to obtain super-resolution phase images. The present technique was tested on 1951 USAF resolution chart, 200 nm polystyrene beads and Escherichia coli bacteria using a 50×, 0.55NA objective lens. The 200 nm polystyrene beads are visually resolvable and subcellular features of the E. coli bacteria are also observed, suggesting a significant improvement in the resolution.

Homogeneous distribution of phosphor particles inside resin using a vertical vibration method for efficient laser-based white light illumination.

We report what we believe to be an innovative method for the homogeneous distribution of phosphor particles inside the optical resin-based layer using a vertical vibrational technique for efficient laser-based white light illumination. In this method, single-stage vibration energy was efficiently used against phosphor sedimentation with the help of a mechanical vibrator system. The vertical vibrational energy was transferred to negate the downward gravitational effect acting on each phosphor particle. Therefore, the phosphor particles inside the layer were stable and uniformly distributed from the initial to final drying stages, creating approximate refractive index homogeneity inside the medium. The sedimentation problem was resolved, and all the optical parameters to support this method were properly analyzed and found to be stable and suitable for laser-based illumination applications.

White light phase shifting interferometric microscopy with whole slide imaging for quantitative analysis of biological samples.

In this paper, we demonstrate the white light phase shifting interferometer employed as whole slide scanner and phase profiler for determining qualitative and quantitative information over large field-of-view (FOV). Experiments were performed on human erythrocytes and MG63 Osteosarcoma cells. Here, we have recorded microscopic images and phase shifted white light interferograms simultaneously in a stepped manner. Sample slide is translated in transverse direction such that there exists a correlation between the adjacent frames, and they were stitched together using correlation functions. Final stitched image has a FOV of 0.24 × 1.14 mm with high resolution ~0.8 µm. Circular Hough transform algorithm is implemented to the resulting image for cell counting and five-step phase shifting algorithm is utilised to retrieve the phase profiles over a large FOV. Further, this technique is utilised to study the difference between normal and anaemic erythrocytes. Significant changes are observed in anaemic cells as compared to normal cells.

Development of multimodal micro-endoscopic system with oblique illumination for simultaneous fluorescence imaging and spectroscopy of oral cancer.

Multimodality of an optical system implies the use of one or more optical techniques to improve the system's overall performance and maximum utility. In this article, we demonstrate a multimodal system with oblique illumination that combines two different techniques; fluorescence micro-endoscopy and spectroscopy simultaneously and can be utilized to obtain diverse information from the same location of biological sample. In present system, use of graded index (GRIN) rod-lens makes it highly compact and oblique incidence decouples illumination geometry with collection geometry, preventing CCD cameras from saturation and reduces number of optical elements, thereby making system further miniaturized and field-portable. It also overcomes the disadvantages of undesired reflections from different optical elements. The experimental results of simultaneous imaging and spectroscopy of the biological samples are presented along with quantitative spectroscopic parameters; peak wavelength shift, area under the curve and full width half maximum (FWHM). The spatial resolution, spectral resolution and field of view of the system are found to be 4.38 µm, 0.5 nm and 2.071×1.548mm2 , respectively. Furthermore, we have obtained the red shift for cancerous oral tissue with respect to normal oral tissue 5.79 ± 1.071 nm. This could be important indicator for oral cancer screening.

Multimodal biomicroscopic system for the characterization of cells with high spatial phase sensitivity and sub-pixel accuracy.

Multimodal analysis is highly advantageous for various biomedical applications including cancer and brain studies. Simultaneous measurement of quantitative phase with sub-pixel accuracy and fluorescence image is difficult to achieve in single measurement. Conventionally, off-axis interferograms are analyzed using the Fourier-transform method which limits the accuracy of the phase maps by pixel size, and usually the location of the carrier peak is in sub-pixel. We report a multimodal microscopic system consisting of high-resolution (HR) quantitative phase interferometer to retrieve sub-pixel accuracy in phase imaging and an oblique-illumination-based fluorescence imaging system which decouples the excited light from emitted signal light to avoid saturation of the camera, both integrated into a single unit. Here, highly resolved phase maps are obtained using a two-step process. First, using a speckle-free illumination which offers high spatial phase sensitivity. Second, using a hamming window for accurate estimation of original signal frequency information and HR discrete Fourier transform (DFT) which offers sub-pixel accuracy in phase measurements. HR-DFT has computational load of OABß , where A×B is the size of the interferogram and ß is the upsampling factor, making system computationally more robust and efficient compared to zero-padded FFT. The experiment is conducted on MG63 osteosarcoma and human mesenchymal stem cells (hMSCs) and their quantitative parameters are extracted with significantly improved accuracy. The average phase for MG63 cells and hMSCs, for nucleus is obtained to be 8.02 rad ± 0.80 rad and 4.29 rad ± 0.43 rad, respectively, and for cytoplasm is obtained to be 2.63 rad ± 0.96 rad and 1.73 rad ± 0.57 rad, respectively.

Multimodal on-chip nanoscopy and quantitative phase imaging reveals the nanoscale morphology of liver sinusoidal endothelial cells.

Visualization of three-dimensional (3D) morphological changes in the subcellular structures of a biological specimen is a major challenge in life science. Here, we present an integrated chip-based optical nanoscopy combined with quantitative phase microscopy (QPM) to obtain 3D morphology of liver sinusoidal endothelial cells (LSEC). LSEC have unique morphology with small nanopores (50-300 nm in diameter) in the plasma membrane, called fenestrations. The fenestrations are grouped in discrete clusters, which are around 100 to 200 nm thick. Thus, imaging and quantification of fenestrations and sieve plate thickness require resolution and sensitivity of sub-100 nm along both the lateral and the axial directions, respectively. In chip-based nanoscopy, the optical waveguides are used both for hosting and illuminating the sample. The fluorescence signal is captured by an upright microscope, which is converted into a Linnik-type interferometer to sequentially acquire both superresolved images and phase information of the sample. The multimodal microscope provided an estimate of the fenestration diameter of 119 ± 53 nm and average thickness of the sieve plates of 136.6 ± 42.4 nm, assuming the constant refractive index of cell membrane to be 1.38. Further, LSEC were treated with cytochalasin B to demonstrate the possibility of precise detection in the cell height. The mean phase value of the fenestrated area in normal and treated cells was found to be 161 ± 50 mrad and 109 ± 49 mrad, respectively. The proposed multimodal technique offers nanoscale visualization of both the lateral size and the thickness map, which would be of broader interest in the fields of cell biology and bioimaging.

High-throughput spatial sensitive quantitative phase microscopy using low spatial and high temporal coherent illumination.

High space-bandwidth product with high spatial phase sensitivity is indispensable for a single-shot quantitative phase microscopy (QPM) system. It opens avenue for widespread applications of QPM in the field of biomedical imaging. Temporally low coherence light sources are implemented to achieve high spatial phase sensitivity in QPM at the cost of either reduced temporal resolution or smaller field of view (FOV). In addition, such light sources have low photon degeneracy. On the contrary, high temporal coherence light sources like lasers are capable of exploiting the full FOV of the QPM systems at the expense of less spatial phase sensitivity. In the present work, we demonstrated that use of narrowband partially spatially coherent light source also called pseudo-thermal light source (PTLS) in QPM overcomes the limitations of conventional light sources. The performance of PTLS is compared with conventional light sources in terms of space bandwidth product, phase sensitivity and optical imaging quality. The capabilities of PTLS are demonstrated on both amplitude (USAF resolution chart) and phase (thin optical waveguide, height ~ 8 nm) objects. The spatial phase sensitivity of QPM using PTLS is measured to be equivalent to that for white light source and supports the FOV (18 times more) equivalent to that of laser light source. The high-speed capabilities of PTLS based QPM is demonstrated by imaging live sperm cells that is limited by the camera speed and large FOV is demonstrated by imaging histopathology human placenta tissue samples. Minimal invasive, high-throughput, spatially sensitive and single-shot QPM based on PTLS will enable wider penetration of QPM in life sciences and clinical applications.

Fabrication of low cost highly structured silver capped aluminium nanorods as SERS substrate for the detection of biological pathogens.

We report the fabrication of low cost highly structured silver (Ag) capped aluminium (Al) nanorods (NRs) as surface enhanced Raman spectroscopy (SERS) substrate utilising the glancing angle deposition technique. The nano-capping of silver onto the Al NRs can concentrate the local electric field within the minimal volume that can serve as hotspots. The average size of the Ag nanocaps was 50 nm. The newly proposed nanoporous Ag capped Al NRs as SERS substrate could detect the Raman signal of rhodamine 6G (R6G) up to 10-15molar concentration. The significant enhancement in the Raman signal of 107was achieved for Ag capped Al NRs considering R6G as a probe molecule. Using the developed SERS substrate, we recorded Raman spectra forEscherichia colibacteria with its concentration varying from 108colony forming units per ml (CFU ml-1) up to 102CFU ml-1. All the reported Raman spectra were acquired by a portable handheld Raman spectrometer. Hence, this newly proposed low cost, effective SERS substrate can be used commercially for the onsite detection of clinical pathogens. The 3D finite difference time domain simulation model was performed for Ag capped Al nanostructure to understand the generation of hotspots. The simulated results show excellent agreement with the experimental results. We fabricated uncapped Ag nanorods of similar dimensions and performed the experimental measurements and simulations for comparison. We found a significant enhancement in Ag capped Al NRs compared to the long Ag NRs. The description of the Raman signal enhancement has been elaborated.

High-resolution single-shot phase-shifting interference microscopy using deep neural network for quantitative phase imaging of biological samples.

White light phase-shifting interference microscopy (WL-PSIM) is a prominent technique for high-resolution quantitative phase imaging (QPI) of industrial and biological specimens. However, multiple interferograms with accurate phase-shifts are essentially required in WL-PSIM for measuring the accurate phase of the object. Here, we present single-shot phase-shifting interferometric techniques for accurate phase measurement using filtered white light (520±36 nm) phase-shifting interference microscopy (F-WL-PSIM) and deep neural network (DNN). The methods are incorporated by training the DNN to generate (a) four phase-shifted frames and (b) direct phase from a single interferogram. The training of network is performed on two different samples i.e., optical waveguide and MG63 osteosarcoma cells. Further, performance of F-WL-PSIM+DNN framework is validated by comparing the phase map extracted from network generated and experimentally recorded interferograms. The current approach can further strengthen QPI techniques for high-resolution phase recovery using a single frame for different biomedical applications.

High space-bandwidth in quantitative phase imaging using partially spatially coherent digital holographic microscopy and a deep neural network.

Quantitative phase microscopy (QPM) is a label-free technique that enables monitoring of morphological changes at the 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 quantitative phase imaging using partially spatially coherent digital holographic microscopy (PSC-DHM) assisted with a 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 the PSC-DHM 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 heterogeneous macrophages. The performance is evaluated by predicting the HR images from the datasets captured with a low NA lens and compared with the actual HR phase images. An improvement of 9× in the space-bandwidth product is demonstrated for both RBC and macrophages datasets. We believe that the PSC-DHM + 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.