SummaryDigital holographic microscopy (DHM) is an important technique that may be used for quantitative phase imaging of unstained biological cell samples. Since the DHM technology is not commonly used in clinics or bioscience research labs, at present there is no well‐accepted focusing criterion for unstained samples that users can follow while recording image plane digital holograms of cells. The usual sharpness metrics that are useful for auto‐focusing of stained cells do not work well for unstained cells as there is no amplitude contrast. In this work, we report a practical method for estimating the best focus plane for unstained cells in the digital hologram domain. The method is based on an interesting observation that for the best focus plane the fringe pattern associated with individual unstained cells predominantly shows phase modulation effect in the form of bending of fringes and minimal amplitude modulation. This criterion when applied to unstained red blood cells shows that the central dip in the doughnut‐like phase profile of cells is maximal in this plane. The proposed methodology is helpful for standardizing the usage of DHM technology across different users and application development efforts.Lay DescriptionDigital holographic microscopy (DHM) is slowly but steadily becoming an important microscopy modality and gaining acceptability for basic bio‐science research as well as clinical usage. One of the important features of DHM is that it allows users to perform quantitative imaging of unstained transparent cells. Instead of using dyes or fluorescent labelling, DHM systems use quantitative phase as a contrast mechanism which depends on the natural refractive index variation within the cell samples. Since minimal wet lab processing is required in order to image cell samples with a DHM, cells can be imaged in their natural state. While DHM is gaining popularity among users, the imaging protocols across the labs or users need to be standardized in order to make sure that the same quantitative phase parameters are used for tasks such as quantitative phased based cell classification.One of the important operational tasks for any microscopy work is to focus the sample under study. While focusing comes naturally to users of brightfield microscopes based on image contrast, the focusing is not straightforward when samples are unstained so that they do not offer any amplitude contrast. When performing quantitative phase imaging, defocus can actually change the phase profile of the cell due to near‐zone (Fresnel) diffraction effects. So unless a standardized focusing methodology is used, it will be difficult for multiple DHM users (potentially at different sites) to agree on quantitative results out of their phase images. DHM literature has prior works which perform numerical focusing of recovered complex wave‐field in the hologram plane to find the best focus plane. However such methods are not user friendly and do not allow user the same focusing experience as in a brightfield microscope. The numerical focusing is therefore a reasonably good method for an optics researcher but not necessarily so for a microscopy technician looking at cell samples with a DHM system in a clinical setting.The present work provides a simple focusing criterion for unstained samples that works directly in the hologram domain. The technique is based on an interesting observation that the when an unstained cell sample is in the best‐focus plane, its corresponding hologram (or fringe pattern) predominantly shows phase modulation manifested by bending of fringes at the location of the cell. This criterion can be converted into a simple numerical method as we have used to find the best‐focus plane using a stack of through focus holograms. We believe that the technique can be used manually by visually observing the holograms or can be converted to an auto‐focus algorithm for a motorized DHM system.

We present a microfluidic holographic cytometry technique using three-dimensional (3D) hydrodynamic focusing for accurate visualization, classification, and quantification of the cells and particles from a mixture. Our approach uses high-resolution, single-shot digital holographic microscopy to image moving cells and particles in a specially-designed microfluidic device that orders the cells and particles in a single file close to the bottom wall of the channel. Our 3D-focusing microfluidic device allows high-magnification holographic imaging without the need for computationally-expensive numerical refocusing used by the existing holographic cytometry techniques. Our microfluidic device also prevents the clustering of cells and can be fabricated at a low-cost using micromilling. To demonstrate the efficacy of our method, we consider a challenging case of classification from a mixture of unstained red blood cells and polystyrene particles, which are otherwise indistinguishable in brightfield and phase-contrast microscopy. Through experiments with cell-particle mixtures with varying proportions, we show that our holographic cytometry technique can precisely count and classify the cells and particles based on their reconstructed phase values. Our holographic cytometry technique has the potential for label-free classification and quantification of infected cells for applications such as disease diagnostics, cancer research, and genomics.

The recorded field of view of any digital imaging system is limited by the physical size of the sensor array. While it is a common knowledge that the image field exists beyond the boundaries of the sensor array, there is generally no way to measure it unless the imaging system (or the object) is translated laterally. We propose a single-shot computational imaging system with a multiple-point impulse response that is able to effectively increase the physical size of the sensor array. The image recorded on the array sensor is not visually meaningful but can be used to recover the image field beyond the native sensor boundary via a sparsity based iterative algorithm, as we demonstrate in this work. The system concept can be considered analogous to structured illumination imaging; however, the structuring is performed here in the Fourier space in order to recover an extended image field. The effective increase in the sensor size depends on the extent of the impulses in the engineered multiple point impulse response. The achievable sensor size extension is therefore limited by the resolution of the phase mask that is introduced in the Fourier plane of the imaging system. We present a simulation study where the individual impulses in the designed impulse response extend over the original array sensor size, thereby doubling the effective sensor dimensions (a four times increase in the number of pixels) without affecting the image resolution. Both binary and gray-scale objects have been considered in our study in order to illustrate that the quality of the extended field of view image depends on the sparsity of the object under consideration. The concept of extended field of view computational imaging as presented here may find a number of practical applications.

We summarize a study involving simultaneous imaging of cervical cells from Pap-smear samples using bright-field and quantitative phase microscopy. The optimization approach to phase reconstruction used in our study enables full diffraction limited performance from single-shot holograms and is thus suitable for reducing cost of a quantitative phase microscope system. Over 48000 cervical cells from patient samples obtained from three clinical sites have been imaged in this study. The clinical sites used different sample preparation methodologies and the subjects represented a range of age groups and geographical diversity. Visual examination of quantitative phase images of cervical cell nuclei show distinct morphological features that we believe have not appeared in the prior literature. A PCA based analysis of numerical parameters derived from the bright-field and quantitative phase images of the cervical cells shows good separation of superficial, intermediate and abnormal cells. The distribution of phase based parameters of normal cells is also shown to be highly overlapping among different patients from the same clinical site, patients across different clinical sites and for two age groups (below and above 30 years), thus suggesting robustness and possibility of standardization of quantitative phase as an imaging modality for cell classification in future clinical usage.

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