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.

Methods and apparatus for analyzing embryonic development images. The method comprises obtaining a plurality of embryonic development images captured in a time series, determining, for at least one of the plurality of embryonic development images, a time series of evaluation values for each of a plurality of evaluation items associated with the plurality of embryonic development images, and evaluating a characteristic of cells represented in one or more of the plurality of embryonic development images based, at least in part, on the time series of evaluation values for the plurality of evaluation items.

A method of quantifying changes in a visceral organ comprises acquiring first (310) and second (410) medical scans of a visceral organ at first and second timepoints. At least part of the visceral organ in the first medical scan is parcellated into a first set of one or more subregions (420), based on image content, each subregion comprising a plurality of voxels. The first medical scan (310) is aligned to the second medical scan (410), before or after parcellating the first medical scan (310). Then the second medical scan is parcellated into a second set of one or more subregions. A metric is evaluated for a subregion in the first medical scan (310), and for the corresponding subregion in the second medical scan (410). A difference in the metric values provides a measure of a change that has occurred in the subregion, between the first and second timepoints.

There is provided a computer system for evaluating the quality of a fertile ovum. The computer system includes computer processing circuitry configured to receive a plurality of images of a fertile ovum captured in time-series by an imaging apparatus, provide as input to at least one learned model, the plurality of images of the fertile ovum or information based on the plurality of images of the fertile ovum, wherein the at least one learned model has been trained to output, based at least in part, on the plurality of images, fertile ovum analysis information describing characteristics of the fertile ovum used to evaluate a quality of fertile ovum, and provide evaluation support information based, at least in part, on the fertile ovum analysis information, wherein the evaluation support information enables a quality evaluator to interact with the web dashboard to modify at least some of the evaluation support information.

A system and a method monitor a biological process. The method includes obtaining an abnormal tissue mask from an abnormal tissue segmentation of an image of an object containing tissue to be analyzed, the image being acquired at a time t0 being a reference time point. Other images of the object are registered onto the abnormal tissue mask, the other images being acquired at other time points. Image contrasts of the other images are normalized with respect to the contrasts of the image acquired at the reference time point. The normalized images are subtracted for each available contrast in order to obtain difference images. A joint difference image is created by summing the previously obtained difference images. A biological process progression map is created by overlapping the abnormal tissue mask obtained and the joint difference image after applying a pre-defined threshold.

A first acquisition unit acquires stent regions from each of three-dimensional images. A second acquisition unit acquires blood vessel regions from each of the three-dimensional images. A positioning unit acquires a first positioning result by positioning the blood vessel regions for each of the three-dimensional images. A deviation information acquisition unit acquires deviation information indicating a deviation of a stent from a blood vessel between the three-dimensional images based on the stent regions for the three-dimensional images and a deformation vector which is the first positioning result.

Apparatus and methods are described for use with an output device (34), and a blood sample (12) that was drawn from a subject. A microscope system (10) acquires first and second images of the blood sample at respective times. A computer processor (28) determines whether, between acquisitions of the first and second images, there was relative motion between at least one erythrocyte within the sample and at least one entity within the sample, by comparing the first and second images to one another. At least partially in response thereto, the computer processor determines whether the entity is an extra-erythrocytic or an intra-erythrocytic entity, and generates an output on the output device, at least partially in response thereto. Other applications are also described.

To make it possible to improve user convenience, provided is a control device including: a control unit configured to control a position and an attitude of a microscope unit by driving an arm unit that supports the microscope unit on the basis of a captured image of an operating site photographed by the microscope unit during an operation so that a position and attitude condition set before the operation is satisfied. The position and attitude condition is a condition that prescribes a position and an attitude of the microscope unit with respect to the operating site to obtain a desired captured image corresponding to the position and attitude condition.

A method of generating biomarker parameters includes acquiring imaging data depicting a patient using a MRI system. The imaging data is acquired for a plurality of contrasts resulting from application of a pulse on the patient's anatomy. A process is executed to generate a MoCoAve image for each contrast. This process includes dividing the imaging data for the contrast into bins corresponding to one of a plurality of respiratory motion phases, and reconstructing the imaging data in each bin to yield bin images. The process further includes selecting a reference bin image from the bin images, and warping the bin images based on the reference bin image. The warped bin images and the reference bin image are averaged to generate the MoCoAve image for the contrast. One or more biomarker parameter maps are calculated based on the MoCoAve images generated for the contrasts.

Accessed from memory are i) a first brain image, ii) a second brain image, iii) a difference map, and iv) a connectivity element. A GUI may include: concurrently displaying each of these elements. User input to the GUI is received. A location of the user input is determined. The operations also include responsive to determining that the location of the user input is within the display of the first brain image, modifications are made to the display of the i) second brain image, ii) the difference map, and iii) the connectivity element to highlight elements of the display that correspond to an element of the first brain image that corresponds to the location of the user input.