Owing to its high resolution, sensitivity, imaged field of view, and frame rate acquisition, Digital Holographic Microscopy (DHM) stands out among the Quantitative phase imaging (QPI) techniques to reconstruct high-resolution phase images from micrometer-sized samples, providing information about the sample’s topography and refractive index. Despite the successful performance of DHM systems, their applicability to in-situ clinical research has been partially hampered by the need for a standard phase reconstruction algorithm that provides quantitative phase distributions without any phase distortion. This invited talk overviews the current advances in computational DHM reconstruction approaches from semi-heuristic to learning-based approaches.
KEYWORDS: Education and training, Data modeling, Holography, Holograms, Image restoration, Digital holography, Deep learning, Computer simulations, Microscopy, Environmental monitoring
Digital Lensless Holographic Microscopy (DLHM) is a phase imaging modality that omits the use of lenses or other bulky hardware to recover information from microscopic objects. Deep learning models have been recently used to substitute traditional DLHM reconstruction algorithms and classify samples from the reconstructed amplitude and phase images. In this work, we have investigated using these models to classify diatom samples, circumventing the whole reconstruction process altogether. We have validated our approach using a simulated DLHM dataset by comparing the performance of three typical image-processing learning-based models: AlexNet, VGG16, and ResNet-18.
A single-shot procedure to reduce speckle noise in numerically computed complex-valued wavefields is presented. The method is supported by the possibility of numerically producing multiple speckle realizations of a calculated complex-valued wavefield to reduce the speckle noise through a noncoherent superposition of the produced realizations. Although the method is applied to digital holographic microscopy, it could be utilized in other techniques where a numerical representation of the complex-valued wavefield of interest can be obtained. Experimental results with nonbiological and biological samples are presented to support the feasibility of the method.
Over the last years structured illumination digital holographic microscopy (SI-DHM) has been experimentally proved to double the resolution limit in conventional DHM. In SI-DHM, the underlying specimen is illuminated using a spatially varying structured illumination (SI) pattern, which enables super-resolution (SR) images to be retrieved using the proper computational reconstruction process. All these reconstruction methods require the acquisition of at least a couple phase-shifted DHM images. In particular, for a pure sinusoidal pattern, there is a need of recording two phase-shifted DHM images per orientation of the pattern (e.g., 6 images per isotropic SR improvement). Taking advantage of the simultaneous recording of the virtual (e.g., conjugated) image in the raw DHM image, here we present a novel computational method to reconstruct an isotropic SR image using one acquisition per pattern’s orientation (e.g. total 3 images per isotropic improvement). Because our proposed method shows a 50% reduction in the data acquisition and, therefore, acquisition time, we believe that our method should increase the utility of SI-DHM in live-cell imaging. We have validated our method using simulated and results.
In this contribution, the 3D-topography of a reflective sample is obtained by single-shot digital holographic microscopy. An off-axis digital holographic microscope operating in reflection mode and telecentric regimen is utilized to reproduce the 3D-topography of fully reflective microscopic sample. The main characteristics of the proposed method that make it different from other strategies for performing the same task are: i) the possibility of producing the 3D-topography by a single-shot, ii) the use of the complete field of view of the microscope, iii) to operate with sensitivity of λ/100, iv) to work without phase perturbations introduced by the illuminating-imaging system, and v) the no need of further numerical processing beyond the regularly required to recover the phase map of the sample. A complete analysis of the illuminating-imaging system through the use of the ABCD diffraction theory of the digital holographic microscope is presented. 3D-topographies of an USAF resolution
Retinal image quality measurements (double-pass and Hartmann-Shack) using spatially coherent light sources like lasers or super-luminescent diodes suffer from the presence of speckle in the final images. This well-known phenomenon diminishes the performance of those systems. Although solutions to this problem have been proposed, there still exist room to implement effective methods to face this challenge. We evaluate the influence of changing the polarization states of a laser beam in a double-pass system in order to reduce the speckle noise. By rotating the linear polarization state during the exposure time of the camera the speckle changes and partially averages out. We use the speckle contrast metric to evaluate the performance of the proposed method over experimental results
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