The present disclosure relates to a cartridge, detection module, system, and kit for cell and particle detection and analysis. Devices disclosed herein may include at least an optical source, a fluidic chip, and a detection module, wherein the sample flows within the fluidic chip past a detection window, where the cells or particles are imaged by an image acquisition and analysis module that may include an optical detector. The image acquisition and analysis module may count the cells or particles of interest in real-time, or near real-time, or the module may capture images of the cells in order to analyze the sample from combined images at a later time.

An imaging device for determining particle size distribution including a sample receptacle containing a sample and an imager capable of capturing a plurality of images of the sample in a region of observation. The imaging device further includes a radiation source provided linearly opposite to the imager and a base platform that supports the imager and the radiation source.

Among other things, certain embodiments of the present disclosure are related to devices and methods of performing biological and chemical assays, such as but not limited to pH measurement of bio/chemical samples.

A synthetic aperture optics (SAO) imaging method minimizes the number of selective excitation patterns used to illuminate the imaging target, based on the objects' physical characteristics corresponding to spatial frequency content from the illuminated target and/or one or more parameters of the optical imaging system used for SAO. With the minimized number of selective excitation patterns, the time required to perform SAO is reduced dramatically, thereby allowing SAO to be used with DNA sequencing applications that require massive parallelization for cost reduction and high throughput. In addition, an SAO apparatus optimized to perform the SAO method is provided. The SAO apparatus includes a plurality of interference pattern generation modules that can be arranged in a half-ring shape.

The present disclosure relates to systems and methods for cell recognition. At least one embodiment relates to a method for recognizing cell. The method includes receiving an image of the cell. The method also includes performing edge detection on the image of the cell. Further, the method includes detecting ridges within the image of the cell. In addition, the method includes quantifying an internal complexity of the cell by gauging a contrast of the ridges with an average of a Laplacian on the detected ridges.

In one aspect, the present disclosure provides a system for Fourier ptychographic microscopy, the system comprising (i) an image capture apparatus including an objective lens, (ii) at least one processor, and (iii) data storage including program instructions stored thereon that when executed by the at least one processor, cause the system to: (a) capture, via the image capture apparatus, a plurality of initial images of an object, wherein each of the plurality of initial images of the object have a first resolution, and (b) process each of the plurality of initial images in Fourier space to generate a final image of the object having a second resolution, wherein the second resolution is greater than the first resolution.

Embodiments disclosed herein are directed, among other things, to imaging systems, methods, and apparatuses for automatically identifying fields of view (FOVs) for regions in an image encompassing tumor are disclosed. In embodiments and in further aspects of the present invention, a computer-implemented method is disclosed for a tumor region based immune score computation. The method, in accordance with the present invention, involves identifying regions, for example, tumor areas or regions around a tumor area, partitioning a whole slide image or portion of a whole slide image into multiple regions related to the tumor, selecting FOVs within each identified region, and computing a number of cells present in each FOV. An immune score and/or immune-related score may be generated based on the cells counted in each FOV.

Locating morphology in a tissue sample is achieved with devices and methods involving storage of a plurality of feature vectors, each associated with a specific named superpixel of a larger image of a tissue sample from a mammalian body. A microscope outputs, in some embodiments, a live image of an additional tissue sample or a digitized version of the output is used. At least one superpixel of the image is converted into a feature vector and a nearest match between the first feature vector and the plurality of stored feature vectors is made. A first name suggestion is then made based on the nearest match comparison to a store feature vector. Further, regions of interest within the image can be brought to a viewer's attention based on their past history of selection, or that of others.

In one embodiment of the invention, a method to image a probe array is described that includes focusing on a plurality of fiducials on a surface of an array. The method utilizes obtaining the best z position of the fiducials and using a surface fitting algorithm to produce a surface fit profile. One or more surface non-flatness parameters can be adjusted to improve the flatness image of the array surface to be imaged.

An image measurement device including: light sources that irradiate light beams having different peak wavelengths; a staining method obtaining unit which obtains information indicating a staining method of an inspection specimen; an image obtaining unit which: selects a combination of light sources according to the staining method, based on illumination information; and capture inspection images of the inspection specimen with light beams from the selected light sources, and capture reference images of a reference specimen with light beams from the respective light sources; a calculating unit which calculates a positivity based on the inspection images; and an evaluation unit which associates the staining method of the reference specimen with the combination of light sources to generate the illumination information based on a total value of coefficients in a linear sum of the ortho-normalization base vectors of a spectral distribution of light sources calculated based on the reference images.