Provided is a tool wear monitoring device configured to input a plurality of pieces of image data captured with a microscope camera while changing an angle, and to monitor tool wear. The tool wear monitoring device includes a data analysis unit configured to analyze image data. The data analysis unit binarizes the plurality of pieces of image data captured while changing an angle, extracts data in which a worn region has a maximum area among the plurality of pieces of image data, and analyzes the amount of wear from the extracted data with the maximum area.

Various example embodiments pertain to processing images that depict tissue samples using a neural network algorithm. The neural network algorithm includes multiple encoder branches that are copies of each other that share the same parameters. The encoder branches can, accordingly, be referred to as Siamese copies of each other.

Systems and methods for predicting a patient response to various agents and/or combinations of agents using ex vivo dosing and imaging are disclosed. In one example, a method of determining treatment efficacy includes analyzing a solid cell culture over time, e.g., first and second responses to a solid cell culture to respective treatments may be compared to determine a treatment efficacy of each treatment. Systems and methods for applying the treatments to the cell culture and analyzing the cell culture and efficacy are disclosed.

The present disclosure provides methods of preparing a biological specimen for imaging analysis, comprising fixing and clearing the biological specimen and subsequently analyzing the cleared biological specimen using microscopy. Also included are methods of quantifying cells, for example, active populations of cells in response to a stimulant. The present disclosure also provides devices for practicing the described methods. A flow-assisted clearing device provides rapid clearing of hydrogel-embedded biological specimens without the need of specialized equipment such as electrophoresis or perfusion devices.

A cell evaluation method evaluates the quality of a cell population including a plurality of cells. The cell evaluation method comprises: an index calculation step of calculating an index, based on a captured image of the cell population, the index including at least any one of an average distance representing a packing degree of the cells, a spring constant representing a degree of consistency in distances between the cells, and a hexagonal order parameter representing a degree to which an arrangement of the cells resembles a regular hexagon; and an evaluation step of evaluating the cell population, based on the index calculated in the index calculation step.

Examples relate to systems, methods and computer programs for a microscope system and for determining a transformation function, and to a corresponding microscope system. The system for the microscope system comprises one or more processors and one or more storage devices. The system is configured to obtain first imaging sensor data from a first imaging sensor of a microscope of the microscope system and second imaging sensor data from a second imaging sensor of the microscope, the first imaging sensor data comprises sensor data on light sensed in a first plurality of mutually separated wavelength bands. The second imaging sensor data comprises sensor data on light sensed in a second plurality of mutually separated wavelength bands. The wavelength bands of the first plurality of mutually separated wavelength bands or of the second plurality of mutually separated wavelength bands are wavelength bands that are used for fluorescence imaging. The system is configured to generate a composite color image based on the first imaging sensor data and based on the second imaging sensor data. The composite color image is based on a plurality of color channels. The composite color image is generated using a transformation function to define a transformation to be performed between the imaging sensor data and the composite color image, such that the composite color image is generated using sensor data on light sensed in each wavelength band of the first and second plurality of mutually separated wavelength bands.

A computer-implemented method is provided for analyzing videos of a living system captured with microscopic imaging. The method can include obtaining a base dataset including one or more videos captured with microscopic imaging with at least one of the one or more videos including a cellular event, and cropping out, from the base dataset, sub-videos including one or more objects of interest that may be involved in the cellular event. An artificial neural network (ANN) model can be trained using the plurality of selected sub-videos as training data, to perform unsupervised video alignment, a query sub-video can be aligned using the trained ANN model, and a determination can be made whether or not the query sub-video includes the cellular event.

A direct structured illumination microscopy (dSIM) reconstruction method is provided. First, a time domain modulation signal is extracted through a wavelet. Then, an incoherent signal is converted into a coherent signal. Next, an accumulation amount at each pixel is calculated. Finally, a super-resolution image is generated by using a correlation between signals at different spatial positions. An autocorrelation algorithm of dSIM is insensitive to an error of a reconstruction parameter. dSIM bypasses a complex frequency domain operation in structured illumination microscopy (SIM) image reconstruction, and prevents an artifact caused by the parameter error in the frequency domain operation. The dSIM algorithm has high adaptability and can be used in laboratory SIM, nonlinear SIM imaging systems, or commercial systems.

Holographic Video Microscopy analysis of non-spherical particles is disclosed herein. Properties of the particles are determined by application of light scattering theory to holography data. Effective sphere theory is applied to provide information regarding the reflective index of a sphere that includes a target particle. Known particles may be co-dispersed with unknown particles in a medium and the holographic video microscopy is used to determine properties, such as porosity, of the unknown particles.

The present invention relates to a method for acquiring tomographic images of a sample in a microscopy system, wherein the sample comprises a defined region, and wherein the method comprises determining a location in three-dimensional space of the defined region, wherein the method further comprises capturing an image of at least a part of the sample, and wherein the determination of the location in three-dimensional space of the defined region is based, at least in part, on the image of the part of the sample. The present invention also relates to a corresponding microscopy system and a computer program product to perform the method according to the present invention.