A cell suction support system includes: an image acquisition unit that acquires a microscopic image of a group of cells in a cell container; an image processor that uses the microscopic image to calculate a characteristic amount of each cell, and detects a cell having a characteristic amount that satisfies a predetermined condition; a display that displays information concerning the group of cells so that the detected cell is distinguishable; and a movement controller that moves the cell container so that a designated specific cell is placed at a predetermined suction position, while moving a suction tip to the suction position.

This disclosure describes single-use test cartridges, cell analyzer apparatus, and methods for automatically performing microscopic cell analysis tasks, such as counting blood cells in biological samples. A small unmeasured quantity of a biological sample such as whole blood is placed in the disposable test cartridge which is then inserted into the cell analyzer. The analyzer isolates a precise volume of the biological sample, mixes it with self-contained reagents and transfers the entire volume to an imaging chamber. The geometry of the imaging chamber is chosen to maintain the uniformity of the mixture, and to prevent cells from crowding or clumping, when it is transferred into the imaging chamber. Images of essentially all of the cellular components within the imaging chamber are analyzed to obtain counts per unit volume. The devices, apparatus and methods described may be used to analyze a small quantity of whole blood to obtain counts per unit volume of red blood cells, white blood cells, including sub-groups of white cells, platelets and measurements related to these bodies.

Digital pathology is the concept of capturing digital images from glass microscope slides in order to record, visualize, analyze, manage, report, share and diagnose pathology specimens. The present disclosure is directed to a desktop slide scanner, which enables pathologists to scan slides at a touch of a button. Included is a workflow for reliable imaging, diagnosis, quantification, management, and sharing of a digital pathology library. Also disclosed herein is an analysis framework that provides for pattern recognition of biological samples represented as digital images to automatically quantitatively score normal cell parameters against disease state parameters. The framework provides a pathologist with an opportunity to see what the algorithm is scoring, and simply agree, or edit the result. This framework offers a new tool to enhance the precision of the current standard of care.

A system for forming a metal strip into a die having a predetermined shape through a series of forming operations is described herein. The system includes a base configured to support the metal strip as the metal strip undergoes the series of forming operations; a feeding device configured to advance the metal strip between each forming operation of the series of forming operations and grip the metal strip during each forming operation; a bending device configured to bend a portion of the metal strip extending from the feeding device as one of the series of forming operations; a forming head configured to house a pair of forming tools and provide features to the portion of the metal strip extending from the feeding device as one of the series of forming operations using the one or more forming tools; a robotic arm configured to selectively provide the one or more forming tools to the forming head; and a computing unit in communication with the robotic arm and configured to transmit a control signal to cause the robotic arm to retrieve the pair of forming tools and provide the pair of forming tools to the forming head.

When a user designates a region of interest for a plurality of groups targeted for difference analysis in a microscopic observation image of a sample, an m/z candidate search unit (32) searches for candidates for m/z presumed to differ, based on collected mass spectral data. An intensity histogram creation unit processing unit (33) creates and displays a graph showing a frequency distribution of peak intensities at measurement points included in the region of interest of the groups for each of the m/z candidates. If this graph exhibits multimodality, the data distribution is not suitable for a statistical hypothesis test. Thus, an intensity range determination unit (34) limits an intensity range in accordance with a user's instruction. Then, an ROI correction unit (35) corrects the ROI so as to include only measurement points with peak intensities within the limited intensity range. After that, a test processing unit (36) performs a statistical hypothesis test by using the data corresponding to the corrected ROI. In this way, even if first user's setting of a region of interest is improperly made, it is possible to perform highly reliable difference analysis.

Described herein are systems and methods for assessing a biological sample. The methods include: characterizing a speckled pattern to be applied by a diffuser; positioning a biological sample relative to at least one coherent light source such that at least one coherent light source illuminates the biological sample; diffusing light produced by the at least one coherent light source; capturing a plurality of illuminated images with the embedded speckle pattern of the biological sample based on the diffused light; iteratively reconstructing the plurality of speckled illuminated images of the biological sample to recover an image stack of reconstructed images; stitching together each image in the image stack to create a whole slide image, wherein each image of the image stack at least partially overlaps with a neighboring image; and identifying one or more features of the biological sample. The methods may be performed by a near-field Fourier Ptychographic system.

An imaging apparatus includes an imager with an imaging optical system to having an object-side hypercentric property, an illuminator with a plurality of illumination optical systems having mutually different exit pupil positions and a mover for relatively moving these with respect to a well plate. Imaging is performed simultaneously with stroboscopic illumination when the imager is located at a predetermined imaging position, and illumination optical systems are switched according to the imaging position.

An illuminator includes a light source and an illumination optical system for causing light emitted from the light source to be incident on a sample surface where an imaging object is present. The illumination optical system has an optical axis coaxial with that of an imaging optical system. An image of the light source is formed between the illumination optical system and the imaging optical system. A holder arranges the sample surface between the light source image and the imaging optical system.

Described are platforms, systems, and methods for screening patients. In one aspect, a computer-implemented method comprises: receiving, from a cellular imaging device, image data comprising calcium kinetic features of neuronal cultures derived from a patient; processing the image data through a machine-learning model to determine a diagnosis for the patient based on the calcium kinetic features, the machine-learning model trained using neuronal calcium data; and providing the diagnosis a user interface.

[Problem] To evaluate objective cell groups by estimating a mixing ratio of objective cell group without affecting treatment itself and its production process when the objective cell groups include plural kinds of cell groups having different attributes, and to provide an image analysis system and a culture management system capable of accurately perform a quality control and a production control with low cost. [Solution] The cell quality evaluation system 1 detects a feature amount in each cell easily analyzable from images, and estimates a mixing ratio of each of plural kinds of cell groups included in the objective cell groups based on a distribution of the detected feature amount and pre-recorded information of the feature amount. As the feature amount, the embodiment uses a migration speed of each cell, easily distinguishable by analyzing tracking of each cell from plural images in time series.