Quantitative phase microscopy: automated background leveling techniques and smart temporal phase unwrapping

Investigation of refractive index dynamics during in vitro embryo development using off-axis digital holographic microscopy

Embryo quality is a crucial factor affecting live birth outcomes. However, an accurate diagnostic for embryo quality remains elusive in the in vitro fertilization clinic. Determining physical parameters of the embryo may offer key information for this purpose. Here, we demonstrate that digital holographic microscopy (DHM) can rapidly and non-invasively assess the refractive index of mouse embryos. Murine embryos were cultured in either low- or high-lipid containing media and digital holograms recorded at various stages of development. The phase of the recorded hologram was numerically retrieved, from which the refractive index of the embryo was calculated. We showed that DHM can detect spatio-temporal changes in refractive index during embryo development that are reflective of its lipid content. As accumulation of intracellular lipid is known to compromise embryo health, DHM may prove beneficial in developing an accurate, non-invasive, multimodal diagnostic.

Computationally enhanced quantitative phase microscopy reveals autonomous oscillations in mammalian cell growth

The fine balance of growth and division is a fundamental property of the physiology of cells, and one of the least understood. Its study has been thwarted by difficulties in the accurate measurement of cell size and the even greater challenges of measuring growth of a single cell over time. We address these limitations by demonstrating a computationally enhanced methodology for quantitative phase microscopy for adherent cells, using improved image processing algorithms and automated cell-tracking software. Accuracy has been improved more than twofold and this improvement is sufficient to establish the dynamics of cell growth and adherence to simple growth laws. It is also sufficient to reveal unknown features of cell growth, previously unmeasurable. With these methodological and analytical improvements, in several cell lines we document a remarkable oscillation in growth rate, occurring throughout the cell cycle, coupled to cell division or birth yet independent of cell cycle progression. We expect that further exploration with this advanced tool will provide a better understanding of growth rate regulation in mammalian cells.

In vitro monitoring of photoinduced necrosis in HeLa cells using digital holographic microscopy and machine learning

Digital holographic microscopy supplemented with the developed cell segmentation and machine learning and classification algorithms is implemented for quantitative description of the dynamics of cellular necrosis induced by photodynamic treatment in vitro. It is demonstrated that the developed algorithms operating with a set of optical, morphological, and physiological parameters of cells, obtained from their phase images, can be used for automatic distinction between live and necrotic cells. The developed classifier provides high accuracy of about 95.5% and allows for calculation of survival rates in the course of cell death.

Two-dimensional phase unwrapping using the transport of intensity equation

We report a method for two-dimensional phase unwrapping based on the transport of intensity equation (TIE). Given a wrapped phase profile, we generate an auxiliary complex field and propagate it to small distances to simulate two intensity images on closely spaced planes. Using the longitudinal intensity derivative of the auxiliary field as an input, the TIE is solved by employing the regularized Fourier-transform-based approach. The resultant phase profile is automatically in the unwrapped form, as it has been obtained as a solution of a partial differential equation rather than as an argument of a complex-valued function. Our simulations and experimental results suggest that this approach is fast and accurate and provides a simple and practical solution for routine phase unwrapping tasks in interferometry and digital holography.

Invalid phase values removal method for absolute phase recovery

A novel approach is presented for more effectively removing invalid phase values in absolute phase recovery. The approach is based on a detailed study involving the types and cases of invalid phase values. Meanwhile, some commonalities of the existing removal algorithms also are thoroughly analyzed. It is well known that rough absolute phase and fringe order maps can very easily be obtained by temporal phase unwrapping techniques. After carefully analyzing the components and fringe order distribution of the rough fringe order map, the proposed method chiefly adopts an entirely new strategy to refine a pure fringe order map. The strategy consists of three parts: (1) the square of an image gradient, (2) subregion areas of the binary image, and (3) image decomposition and composition. In combination with the pure fringe order map and a removal criterion, the invalid phase values can be identified and filtered out from the rough absolute phase map. This new strategy not only gets rid of the limitations of traditional removal methods but also has a two-fold function. The paper also offers different metrics from the experiment to evaluate the quality of the final absolute phase. In contrast with other removal methods, experimental results have verified the feasibility, effectiveness, and superiority of the proposed method.