A computer-implemented method and system for tracking skin concerns. Color-coded substrates come in different colors, each color being associate with a different skin concern. The color-coded substrates include at least one hydrocolloid and active agent. The color-coded substrates can come in different area-specific shapes for applying on different areas of the skin or face. The color-coded substrates can come in different dosages. A computing device, such as a smartphone, can be used to take scans of the skin with or without substrates, and the computing device is configured to analyze the skin and color-coded substrates based on color or shape or other symbols to make recommendations so that a subject will be able to track the progress of any skin concern.

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.

An imaging system, such as a DBT system, capable of providing an operator of the system with information concerning the location, magnitude and direction of motion detected by the system during performance of the scan to enhance image processing. The imaging system provides the motion information to the operator directly in conjunction with the images processed by the imaging system thereby providing the operator with sufficient information for decisions regarding the need for additional images for completing the scan with the imaging system before the patient is discharged, or even before the breast is decompressed.

A medical scan assisted review system is operable to receive, via a network, a medical scan for review. Abnormality data is generated by identifying a plurality of abnormalities in the medical scan by utilizing a computer vision model that is trained on a plurality of training medical scans. The abnormality data includes location data and classification data for each of the plurality of abnormalities. Text describing each of the plurality of abnormalities is generated based on the abnormality data. The abnormality data and the text is transmitted to a client device. A display device associated with the client device displays the abnormality data in conjunction with the medical scan via an interactive interface, and the display device further displays the text via the interactive interface.

A system for non-invasive estimation of dementia progression. The system includes a computer device and a server. The computer device obtains an image of a subject's head from at least one angle. The server and/or computer device includes a plurality of machine learning models configured to: analyze the image for patterns related to dementia symptoms; and estimate progress of said dementia symptoms of said subject based on the analysis. The server and/or computer device pre-processes the image by performing a plurality of pre-processing steps comprising: importing the image; detecting eyes and shape of the head based on a previously trained machine learning model; rotating the image based on detection of the eyes and shape of the head; normalizing the image to one standard.

Disclosed is a cell image analysis device 2 including: a display unit 52; a storage unit 31 which stores learning data which is a set of data of a cell image and data of an analyzed image in which a region of interest included in the cell image is specified, and a discriminator which is created using a learning model constructed by machine learning using the learning data; a test data input receiver 36 configured to receive an input of test data; a discriminator evaluation unit 37 configured to evaluate the discriminator using the test data; an evaluation result storing unit 38 configured to store evaluation data including an evaluation result of the discriminator and the test data used for the evaluation in association with the discriminator; and a display processor 39 configured to display the test data and/or the evaluation result associated with the discriminator on a screen of the display unit in response to an input for selecting the discriminator.

The present disclosure relates to a method for tracking a tumor in a CT image and a system for diagnosing using the same. The method for tracking tumor includes the operations of: generating a 3D modeling image including at least one characteristic area in a subject's body based on the CT image of the subject; tracking a change according to a flow of time in the 3D modeling image with respect to the subject's characteristic area to generate time series data; and schematizing the time series data.

A method of establishing a quantitative measure of contrast enhancement in contrast medical imaging through computer analysis of baseline and enhanced images allows statistical comparison of protocols and imaging parameters from routine hospital operations to enhance and evaluate such protocols and parameters.

Embodiments of the invention provide a system and method for determining an FFR value for a pathology in a vessel. A value of a predetermined attribute is extracted from a location of the pathology in an image of the vessel and a temporal feature is calculated based on the value of the predetermined attribute. The temporal feature is input to an estimator and an FFR value for the pathology is obtained from an output of the estimator. A structural feature of the pathology may also be input to the estimator to obtain the FFR value based on the temporal feature and the structural feature.

Described herein are systems and methods for image-based (e.g., MRI-based) spatial and temporal mapping of macrophages and other cell types, without the need for image contrast agents. These systems and methods are particularly useful for imaging macrophages because they naturally store metabolites, such as iron. Alternatively, the systems and methods described herein can be used where contrast agents are administered, rather than looking only at endogenous metabolite deposits.