This Roadmap article on digital holography provides an overview of a vast array of research activities in the field of digital holography. The paper consists of a series of 25 sections from the prominent experts in digital holography presenting various aspects of the field on sensing, 3D imaging and displays, virtual and augmented reality, microscopy, cell identification, tomography, label-free live cell imaging, and other applications. Each section represents the vision of its author to describe the significant progress, potential impact, important developments, and challenging issues in the field of digital holography.

A lateral shearing interferometer is used for direct holographic imaging of microorganisms. This is achieved by increasing the shear to be larger than the object size and results in a very simple and inexpensive common-path imaging device that can be easily coupled to the output of an inverted microscope. The shear is created by reflections from the front and back surface of a glass plate. Stability measurements show a standard deviation of the phase measurements of less than 1nm over 8 min. without any vibration compensation. The setup is applied to imaging both microorganisms in a microfluidic channel and red blood cells and reconstructions are presented.

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Digital holographic microscopy (DHM) is one of the most effective techniques used for quantitative phase imaging of cells. Here we present a compact, easy to implement, portable, and very stable DHM setup employing a self-referencing Lloyd's mirror configuration. The microscope is constructed using a diode laser source and a CMOS sensor, making it cost effective. The reconstruction of recorded holograms yields the amplitude and phase information of the object. The temporal stability of the presented technique was found to be around 0.9 nm without any vibration compensation, which makes it ideal for studying cell profile changes. This aspect of the technique is demonstrated by studying membrane fluctuations of red blood cells.

We present a spatio-temporal analysis of cell membrane fluctuations to distinguish healthy patients from patients with sickle cell disease. A video hologram containing either healthy red blood cells (h-RBCs) or sickle cell disease red blood cells (SCD-RBCs) was recorded using a low-cost, compact, 3D printed shearing interferometer. Reconstructions were created for each hologram frame (time steps), forming a spatio-temporal data cube. Features were extracted by computing the standard deviations and the mean of the height fluctuations over time and for every location on the cell membrane, resulting in two-dimensional standard deviation and mean maps, followed by taking the standard deviations of these maps. The optical flow algorithm was used to estimate the apparent motion fields between subsequent frames (reconstructions). The standard deviation of the magnitude of the optical flow vectors across all frames was then computed. In addition, seven morphological cell (spatial) features based on optical path length were extracted from the cells to further improve the classification accuracy. A random forest classifier was trained to perform cell identification to distinguish between SCD-RBCs and h-RBCs. To the best of our knowledge, this is the first report of machine learning assisted cell identification and diagnosis of sickle cell disease based on cell membrane fluctuations and morphology using both spatio-temporal and spatial analysis.

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Image encryption with optical means has attracted attention due to its inherent multidimensionality and degrees of freedom, including phase, amplitude, polarization, and wavelength. In this paper, we propose an optical encoding system based on multiple intensity samplings of the complex-amplitude wavefront with axial translation of the image sensor. The optical encoding system is developed based on a single optical path, where multiple diffraction patterns, i.e., ciphertexts, are sequentially recorded through the axial translation of a CCD camera. During image decryption, an iterative phase retrieval algorithm is proposed for extracting the plaintext from ciphertexts. The results demonstrate that the proposed phase retrieval algorithm possesses a rapid convergence rate during image decryption, and high security can be achieved in the proposed optical cryptosystem. In addition, other advantages of the proposed method, such as high robustness against ciphertext contaminations, are also analyzed.

Abstract:The ability to extract different bio-medical parameters from one single wristwatch device can be very applicable. The wearable device that is presented in this paper is based on two optical approaches. The first is the extraction and separation of remote vibration sources and the second is the rotation of linearly polarized light by certain materials exposed to magnetic fields. The technique is based on tracking of temporal changes of reflected secondary speckles produced in the wrist when being illuminated by a laser beam. Change in skin's temporal vibration profile together with change in the magnetic medium that is generated by time varied glucose concentration caused these temporal changes. In this paper we present experimental tests which are the first step towards an in vivo noncontact device for detection of glucose concentration in blood. The paper also shows very preliminary results for qualitative capability for indication of dehydration.