An imaging system includes an imaging device having a holder configured to hold a cell culture plate with a plurality of wells. The imaging device also includes an imaging assembly having a plurality of imaging units, each of which is configured to image one well of the plurality of wells. The imaging system also includes a storage platform in communication with the imaging device configured to receive a plurality of images from the imaging device. The system further includes a computer in communication with the imaging device and the storage platform. The computer is configured to control the imaging device and to display at least one image of the plurality of images.

According to one embodiment, a cell identification system includes an imaging device and an identification device. The imaging device includes a well plate, a rotation mechanism, and an imaging part. The well plate is provided with a plurality of wells capable of accommodating cells. The rotation mechanism rotates the cells. The imaging part images the cells. The identification device includes processing circuitry. The processing circuitry controls the rotation mechanism to rotate the cells, controls the imaging part to image the cells each time the cells are rotated by the rotation mechanism, and inputs an image for the cells captured by the imaging part to a learned model so as to identify a cell in a good state from among the cells.

Disclosed herein are platforms, systems, and methods including a cell culture system that includes a cell culture container comprising a cell culture, the cell culture receiving input cells, a cell imaging subsystem configured to acquire images of the cell culture, a computing subsystem configured to perform a cell culture process on the cell culture according to the images acquired by the cell imaging subsystem, and a cell editing subsystem configured to edit the cell culture to produce output cell products according to the cell culture process.

The present application provides for systems and methods for detecting and estimating signals corresponding to one or more biomarkers in biological samples stained for the presence of protein and/or nucleic acid biomarkers. On particular aspect is directed to a method of estimating an amount of signal corresponding to at least one biomarker in an image of a biological sample. The method includes detecting isolated spots in a first image, deriving an optical density value of a representative isolated spot based on signal features from the detected isolated spots, estimating a number of predictive spots in signal aggregates in each of a plurality of sub-regions based on the derived optical density value of the representative isolated spot, and storing the estimated number of predictive spots and detected isolated spots in each of the plurality of generated sub-regions in a database.

A method for characterizing cancer organoid response to an immune cell based therapy, includes providing a panel of different combinations of cancer organoid cells and immune cells to culturing wells and culturing the different combination under conditions that support organoid growth. Brightfield and corresponding fluorescence images of the culturing wells are captured and provided to one or more trained machine learning algorithms that identify and distinguish cancer organoid cells from immune cells and characterize cancer organoid morphology changes caused by an immune cell based therapies, from which an analytical report including a characterization of cancer organoid cell death caused by the immune cell based therapy is provided.

Embodiments allow for rapid antimicrobial susceptibility testing (AST) at a low cost. Embodiments may use changes in the pixel intensity from reflected light to determine microorganism growth and antimicrobial resistance. Dilutions of an antimicrobial are added to a standard well plate or other array. A pathogen or other microorganism may be added to the dilutions in the well plate. The well plate may be incubated for a time period less than 3 hours. The well plate may then be imaged and the resulting image data may be analyzed. Wells where the microorganism is able to grow may appear darker than wells where the microorganism did not grow. Differences pixel intensity of the wells is used to determine the susceptibility or resistance of the microorganism to the antimicrobial. The image data may be used to determine the minimum inhibitory concentration (MIC), the lowest dilution concentration of antimicrobial that inhibits growth.

Systems and methods are provided for automatically imaging and analyzing cell samples in an incubator. An actuated microscope operates to generate images of samples within wells of a sample container across days, weeks, or months. A plurality of images is generated for each scan of a particular well, and the images within such a scan are used to image and analysis metabolically active cells in the well. Tins analysis includes generating a “range image” by subtracting the minimum intensity value, across the scan, for each pixel from the maximum intensity value. This range image thus emphasizes cells or portions of cells that exhibit changes in activity over a scan period (e.g., neurons, myocytes, cardiomyocytes) while de-emphasizing regions that exhibit consistently high intensities when images (e.g., regions exhibiting a great deal of autofluorescence unrelated to cell activity).

Methods and systems for analysis of image data generated from various reference points. Particularly, the methods and systems provided are useful for real time analysis of image and sequence data generated during DNA sequencing methodologies.

Provided is a particle measuring method for measuring, based on image data containing an image of a plurality of particles, a size of each of the particles included in the image data. The particle measuring method includes: acquiring a position of each of the plurality of particles from the image data; extracting two particles vicinal to each other; and calculating the size of each of the particles based on a distance between the two vicinal particles.

Techniques are described for dynamically correcting image distortion during imaging of a patterned sample having repeating spots. Different sets of image distortion correction coefficients may be calculated for different regions of a sample during a first imaging cycle of a multicycle imaging run and subsequently applied in real time to image data generated during subsequent cycles. In one implementation, image distortion correction coefficients may be calculated for an image of a patterned sample having repeated spots by: estimating an affine transform of the image; sharpening the image; and iteratively searching for an optimal set of distortion correction coefficients for the sharpened image, where iteratively searching for the optimal set of distortion correction coefficients for the sharpened image includes calculating a mean chastity for spot locations in the image, and where the estimated affine transform is applied during each iteration of the search.