The present disclosure relates to improved holographic reconstruction device and a method. In one aspect, the present disclosure relates to improved holographic reconstruction device and method that can measure a digital hologram regardless of optical characteristics of an object to be measured, by an all-in-one type system integrating a transmissive system that measures an object transmitting light and a reflective system that measures an object reflecting light.

Example embodiments relate to imaging devices for in-line holographic imaging of objects. One embodiment includes an imaging device for in-line holographic imaging of an object. The imaging device includes a set of light sources configured to output light in confined illumination cones. The imaging device also includes an image sensor that includes a set of light-detecting elements. The set of light sources are configured to output light such that the confined illumination cones are arranged side-by-side and illuminate a specific part of the object. The image sensor is arranged such that the light-detecting elements detect a plurality of interference patterns. Each interference pattern is formed by diffracted light from the object originating from a single light source and undiffracted light from the same single light source. At least a subset of the set of light-detecting elements is arranged to detect light relating to not more than one interference pattern.

Some embodiments are directed to a technique having an off-axis interferometric geometry that is capable of spatially multiplexing at least six complex wavefronts, while using the same number of camera pixels typically needed for a single off-axis hologram encoding a single complex wavefront. Each of the at least six parallel complex wavefronts is encoded into an off-axis hologram with a different fringe orientation, and all complex wavefronts can be fully reconstructed. This technique is especially useful for highly dynamic samples, as it allows the acquisition of at least six complex wavefronts simultaneously, optimizing the amount of information that can be acquired in a single camera exposure. The off-axis multiplexing holographic system of some embodiments provide an off-axis holography modality that is more camera spatial bandwidth efficient than on-axis holography. Moreover, the off-axis interferometric system allows simple simultaneous acquisition of at least six holographic channels, making it attractive for imaging dynamics.

Systems and methods for uniquely identifying fluid-phase products by endowing them with fingerprints composed of dispersed colloidal particles, and by reading out those fingerprints on demand using Total Holographic Characterization. A library of chemically inert colloidal particles is developed that can be dispersed into soft materials, the stoichiometry of the mixture encoding user-specified information, including information about the host material. Encoded information then can be recovered by high-speed analysis of holographic microscopy images of the dispersed particles. Specifically, holograms of individual colloidal spheres are analyzed with predictions of the theory of light scattering to measure each sphere's radius and refractive index, thereby building up the distribution of particle properties one particle at a time. A complete analysis of a colloidal fingerprint requires several thousand single-particle holograms and can be completed in ten minutes.

The invention relates to an in-vitro method for determining a cell type of a white blood cell in a biological sample without labeling, wherein a microscopy apparatus images the cell and physical parameters of the cell are ascertained from the image of the cell by means of an automated image analysis, wherein the cell type of the white blood cell is determined on the basis of the physical parameters and on the basis of principal component analysis parameters (PCA parameters), wherein the principal component analysis parameters comprise linear combinations of at least some of the physical parameters.

The invention relates to a device, such as a digital holographic microscope, for detecting and processing a first full image of a measurement object, measured with a first offset, wherein an arrangement is provided for generating at least one further full image with at least one offset that differs from the first offset.

A system for performing adaptive focusing of a microscopy device comprises a microscopy device configured to acquire microscopy images depicting cells and one or more processors executing instructions for performing a method that includes extracting pixels from the microscopy images. Each set of pixels corresponds to an independent cell. The method further includes using a trained classifier to assign one of a plurality of image quality labels to each set of pixels indicating the degree to which the independent cell is in focus. If the image quality labels corresponding to the sets of pixels indicate that the cells are out of focus, a focal length adjustment for adjusting focus of the microscopy device is determined using a trained machine learning model. Then, executable instructions are sent to the microscopy device to perform the focal length adjustment.

A trained deep neural network transforms an image of a sample obtained with a holographic microscope to an image that substantially resembles a microscopy image obtained with a microscope having a different microscopy image modality. Examples of different imaging modalities include bright-field, fluorescence, and dark-field. For bright-field applications, deep learning brings bright-field microscopy contrast to holographic images of a sample, bridging the volumetric imaging capability of holography with the speckle-free and artifact-free image contrast of bright-field microscopy. Holographic microscopy images obtained with a holographic microscope are input into a trained deep neural network to perform cross-modality image transformation from a digitally back-propagated hologram corresponding to a particular depth within a sample volume into an image that substantially resembles a microscopy image of the sample obtained at the same particular depth with a microscope having the different microscopy image modality.

Example embodiments relate to methods and imaging systems for holographic imaging. One embodiment includes a method for holographic imaging of an object. The method includes driving a laser using a current which is below a threshold current of the laser. The method also includes illuminating the object using illumination light output by the laser. Further, the method includes detecting an interference pattern formed by object light, having interacted with the object, and reference light of the illumination light.

A cell visualization system includes a digital holographic microscopy (DHM) device, a training device, and a virtual staining device. The DHM device produces DHM images of cells and the virtual staining device colorizes the DHM images based on an algorithm generated by the training device using generative adversarial networks and unpaired training data. A computer-implemented method for producing a virtually stained DHM image includes acquiring an image conversion algorithm which was trained using the generative adversarial networks, receiving a DHM image with depictions of one or more cells and virtually staining the DHM image by processing the DHM image using the image conversion algorithm. The virtually stained DHM image includes digital colorization of the one or more cells to imitate the appearance of a corresponding actually stained cell.