An apparatus, system and process for identifying one or more different tissue types are described. The method may include applying a configuration to one or more programmable light sources of an imaging system, where the configuration is obtained from a machine learning model trained to distinguish between the one or more different tissue types captured in image data. The method may also include illuminating a scene with the configured one or more programmable light sources, and capturing image data that includes one or more types of tissue depicted in the image data. Furthermore, the method may include analyzing color information in the captured image data with the machine learning model to identify at least one of the one or more different tissue types in the image data, and rendering a visualization of the scene from the captured image data that visually differentiates tissue types in the visualization.

The technology disclosed present systems and methods to produce an enhanced resolution image from images of a target using structured illumination microscopy (SIM). The method includes transforming at least three images of the target captured by a sensor in a spatial domain into a Fourier domain to produce at least three frequency domain matrices that each include first blocks of complex coefficients and redundant second blocks of complex coefficients that are conjugates to the first blocks. The method includes reducing computing resources required to produce the enhanced resolution image by using first blocks of complex coefficients to produce at least three phase-separated half-matrices in the Fourier domain. The method includes performing one or more intermediate transformation on the phase-separated half-matrices to produce realigned shifted half-matrices. The method includes calculating complex coefficients of second blocks in the Fourier domain to produce full matrices from half-matrices.

A method for identifying a skin abnormality including using an imaging device, the imaging device including a lighting member for directing light toward a target surface, the lighting member including a plurality of lighting elements, and a filter member positioned between the lighting member and the target surface, the filter member including a plurality of filter elements, capturing a plurality of images of the target surface, each of the plurality of images captured when illuminating a different one or more of the plurality of lighting elements, compiling the plurality of images into a data package, transmitting the data package to a server for processing the data package, and determining, at the server, a presence of an abnormality.

A method of generating a three-dimensional model of an object, is executed by a processor. The method includes executing rendering of the three-dimensional model of the object based on an image captured by the imaging device; and modifying the three-dimensional model.

In a method for time-of-flight (ToF) based measurement, a scene is illuminated using a ToF light source modulated at a first modulation frequency F.sub.MOD.sup.(1). While the light is modulated using F.sub.MOD.sup.(1), depths are measured to respective surface points within the scene, where the surface points are represented by a plurality of respective pixels. At least one statistical distribution parameter is computed for the depths. A second modulation frequency F.sub.MOD.sup.(2) higher than F.sub.MOD.sup.(1) is determined based on the at least one statistical distribution parameter. The depths are then re-measured using F.sub.MOD.sup.(2) to achieve a higher depth accuracy.

An object of the present disclosure is to provide a system for deriving a type of a defect of a semiconductor element and a non-transitory computer-readable medium. The system receives, from the image acquisition tool, image data obtained by sequentially irradiating a plurality of patterns provided on the semiconductor wafer with a beam and extracts characteristics of the plurality of patterns sequentially irradiated with a beam from the received image data, the characteristics being included in the image data, or receives characteristics of the plurality of patterns sequentially irradiated with a beam from the image acquisition tool, the characteristics being extracted from the image data (Step 603), and derives (Step 605) a type of a defect by referring to (Step 604) related information for the characteristics of the plurality of patterns, the related information storing the characteristics of the plurality of patterns and types of defects in association with each other.

A system and method for three-dimensional (3D) microgeometry and reflectance modeling is provided. The system receives images comprising a first set of images of a face and a second set of images of the face. The faces in the first set of images and the second set of images are exposed to omni-directional lighting and directional lighting, respectively. The system generates a 3D face mesh based on the received images and executes a set of skin-reflectance modeling operations by using the generated 3D face mesh and the second set of images, to estimate a set of texture maps for the face. Based on the estimated set of texture maps, the system texturizes the generated 3D face mesh. The texturization includes an operation in which texture information, including microgeometry skin details and skin reflectance details, of the estimated set of texture maps is mapped onto the generated 3D face mesh.

Methods and systems for setting up care areas (CAs) for inspection of a specimen are provided. One system includes an imaging subsystem configured for generating images of a specimen and a computer subsystem configured for determining a number of defects detected in predefined cells within one or more of the images generated in a repeating patterned area formed on the specimen. The computer subsystem is also configured for comparing the number of the defects detected in each of two or more of the predefined cells to a predetermined threshold and designating any one or more of the two or more of the predefined cells in which the number of the defects is greater than the predetermined threshold as one or more CAs. In addition, the computer subsystem is configured for storing information for the one or more CAs for use in inspection of the specimen.

A time of flight (ToF) system includes a light source, a photosensor, a signal generator and a processor. The signal generator outputs a reference signal corresponding to a modulation function for modulated light and a modified transmitted light signal corresponding to a phase shift of the reference signal. The light source outputs the modified transmitted light signal and pixels in the photosensor receives its reflections off the scene. The reference signal is applied to the pixels and the processor determines a depth map for the scene based on values recorded by the pixels. In some examples, the phase shift is implemented using a phase locked loop controller. One or more component phases of the phase shift and an exposure time for each component phase are determined and output by the phase locked loop controller.

A review system and operation method directs a beam of light toward a sample on a stage. The sample is a wafer level packaging wafer or a backend wafer. Defect review is performed based on the light reflected from the sample. The review system can use one or more of: a fluid supplied by an immersion subsystem that includes a fluid supply unit and a fluid removal unit; an illumination pattern for differential phase contrast; or ultraviolet or deep ultraviolet wavelengths.