We present a new acquisition method that enables high-resolution, fine-detail full reconstruction of the three-dimensional movement and structure of individual human sperm cells swimming freely. We achieve both retrieval of the three-dimensional refractive-index profile of the sperm head, revealing its fine internal organelles and time-varying orientation, and the detailed fourdimensional localization of the thin, highly-dynamic flagellum of the sperm cell. Live human sperm cells were acquired during free swim using a high-speed off-axis holographic system that does not require any moving elements or cell staining. The reconstruction is based solely on the natural movement of the sperm cell and a novel set of algorithms, enabling the detailed fourdimensional recovery. Using this refractive-index imaging approach, we believe we have detected an area in the cell that is attributed to the centriole. This method has great potential for both biological assays and clinical use of intact sperm cells.

Many medical and biological protocols for analyzing individual biological cells involve morphological evaluation based on cell staining, designed to enhance imaging contrast and enable clinicians and biologists to differentiate between various cell organelles. However, cell staining is not always allowed in certain medical procedures. In other cases, staining may be time consuming or expensive to implement. Furthermore, staining protocols may be operator-sensitive, and hence lead to varying analytical results by different users, as well as cause artificial imaging artifacts or false heterogeneity. Here, we present a new deep-learning approach, called HoloStain, which converts images of isolated biological cells acquired without staining by holographic microscopy to their virtually stained images. We demonstrate this approach for human sperm cells, as there is a well-established protocol and global standardization for characterizing the morphology of stained human sperm cells for fertility evaluation, but, on the other hand, staining might be cytotoxic and thus is not allowed during human in vitro fertilization (IVF). We use deep convolutional Generative Adversarial Networks (DCGANs) with training that is based on both the quantitative phase images and two gradient phase images, all extracted from the digital holograms of the stain-free cells, with the ground truth of bright-field images of the same cells that subsequently underwent chemical staining. After the training stage, the deep neural network can take images of unseen sperm cells, retrieved from the coinciding holograms acquired without staining, and convert them to their stain-like images. To validate the quality of our virtual staining approach, an experienced embryologist analyzed the unstained cells, the virtually stained cells, and the chemically stained sperm cells several times in a blinded and randomized manner. We obtained a 5-fold recall (sensitivity) improvement in the analysis results, demonstrating the advantage of using virtual staining for sperm cell analysis. With the introduction of simple holographic imaging methods in clinical settings, the proposed method has a great potential to become a common practice in human IVF procedures, as well as to significantly simplify and facilitate other cell analyses and techniques such as imaging flow cytometry.Submitted

Currently, the delicate process of selecting sperm cells to be used for in vitro fertilization (IVF) is still based on the subjective, qualitative analysis of experienced clinicians using non-quantitative optical microscopy techniques. In this work, a method was developed for the automated analysis of sperm cells based on the quantitative phase maps acquired through use of interferometric phase microscopy (IPM). Over 1,400 human sperm cells from 8 donors were imaged using IPM, and an algorithm was designed to digitally isolate sperm cell heads from the quantitative phase maps while taking into consideration both the cell 3D morphology and contents, as well as acquire features describing sperm head morphology. A subset of these features was used to train a support vector machine (SVM) classifier to automatically classify sperm of good and bad morphology. The SVM achieves an area under the receiver operating characteristic curve of 88.59% and an area under the precision-recall curve of 88.67%, as well as precisions of 90% or higher. We believe that our automatic analysis can become the basis for objective and automatic sperm cell selection in IVF. © 2017 International Society for Advancement of Cytometry.

Off-axis holographic multiplexing involves capturing several complex wavefronts, each encoded into off-axis holograms with different interference fringe orientations, simultaneously, with a single camera acquisition. Thus, the multiplexed off-axis hologram can capture several wavefronts at once, where each one encodes different information from the sample, using the same number of pixels typically required for acquiring a single conventional off-axis hologram encoding only one sample wavefront. This gives rise to many possible applications, with focus on acquisition of dynamic samples, with hundreds of scientific papers already published in the last decade. These include field-of-view multiplexing, depth-of-field multiplexing, angular perspective multiplexing for tomographic phase microscopy for 3-D refractive index imaging, multiple wavelength multiplexing for multiwavelength phase unwrapping or for spectroscopy, performing super-resolution holographic imaging with synthetic aperture with simultaneous acquisition, holographic imaging of ultrafast events by encoding different temporal events into the parallel channels using laser pulses, measuring the Jones matrix and the birefringence of the sample from a single multiplexed hologram, and measuring several fluorescent microscopy channels and quantitative phase profiles together, among others. Each of the multiplexing techniques opens new perspectives for applying holography to efficiently measure challenging biological and metrological samples. Furthermore, even if the multiplexing is done digitally, off-axis holographic multiplexing is useful for rapid processing of the wavefront, for holographic compression, and for visualization purposes. Although each of these applications typically requires a different optical system or processing, they all share the same theoretical background. We therefore review the theory, various optical systems, applications, and perspectives of the field of off-axis holographic multiplexing, with the goal of stimulating its further development.

We present a new holographic concept, named six-pack holography (6PH), in which we compress six off-axis holograms into a single multiplexed off-axis hologram without loss of magnification or resolution. The multiplexed hologram contains straight off-axis fringes with six different orientations, and can be generated optically or digitally. We show that since the six different complex wavefronts do not overlap in the spatial frequency domain, they can be fully reconstructed. 6PH allows more than 50% improvement in the spatial bandwidth consumption when compared to the best multiplexing method proposed so far. We expect the 6PH concept to be useful for a variety of applications, such as field-of-view multiplexing, wavelength multiplexing, temporal multiplexing, multiplexing for super-resolution imaging, and others.