A computer-implemented method includes obtaining a video of a subject, the video including a plurality of frames; generating, based on the plurality of frames, a plurality of optical flows; and encoding the plurality of optical flows using an autoencoder to obtain a movement-based biomarker value of the subject.

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 system for video-assisted surgery includes one or more displays, a memory including at least one preoperative image, and a camera coupled to capture a video. A controller is coupled to the memory, the camera, and the one or more displays, and the controller includes logic that when executed by the controller causes the system to perform a variety of operations. The system may capture a video of a surgical area, including anatomical features, using the camera, and display the video of the surgical area on the one or more displays. The system may also display the at least one preoperative image on the one or more displays at the same time as the video. The location of the anatomical features shown in the video is displayed as an accentuated region on the at least one preoperative image.

An imaging (e.g., with an optical coherence tomography system) method that includes 1) acquiring repeated B-scans in a manner consistent with forming images, 2) processing the acquired images according to a variable interscan time analysis (VISTA) method, and 3) generating and displaying a color-mapped image pixel color of the color-mapped image fluid flow speed, or a related quantity.

A system for monitoring the movement of objects, structures, models of structures, cables and the like provides for the acquisition of images with an optical sensing device such as a video camera fixedly mounted at a selected distance from the item studied, in which the images are arranged into frames divided into pixels which are characterized by an intensity reflected or emitted over a selected time interval, and a data processing system to calculate a physical displacement as function of time of the item being studied or a portion of the item being studied based on an output from the video camera, and in some embodiments the system visually distinguishes one or more locations in the frame to indicate a difference in the phase of motion for multiple objects appearing in the frame.

A method for predicting brain disease state change is disclosed. The method includes acquiring test images obtained by capturing a portion of a human brain at a time interval, performing a pre-processing procedure of converting the test images into test voxels configured to be processed for image analysis, wherein a respective test voxel of the test voxels is composed of three-dimensional voxel units, mapping first and second test voxels selected from the test voxels acquired from a patient, with each other on a three-dimensional voxel unit, wherein the first test voxel is acquired at a first time-point and the second test voxel is acquired at a second time-point, generating a voxel-based data-set based on the mapped first and second test voxels, extracting a change in the test voxels using a deep neural network, and generating a state change probability model based on the change in the test voxels.

A dynamic analysis apparatus includes: an index value meter that measures, in a plurality of areas in a dynamic image obtained by performing radiography on a region including a blood vessel with respect to a subject, a temporal change of an index value regarding a position and a shape of the blood vessel; an elongation rate calculator that calculates an elongation rate of the blood vessel in each area on the basis of the temporal change of the index value in each area measured by the index value meter; and an elongation rate display that displays a list of the elongation rate in each area calculated by the elongation rate calculator.

An eye-tracking method includes enabling at least one light source of an array of light sources to emit non-visible light to illuminate an eye. The method also includes obtaining at least one image of the eye while the at least one light source is enabled. A position of the eye may then be determined based on a position of the at least one light source within the array of light sources in response to determining that the at least one image indicates a bright pupil condition when the at least one light source was enabled.

There is provided a medical image processing apparatus which includes a first extraction unit configured to extract coronary arteries depicted in images of a plurality of time phases relating to the heart, and to extract at least one stenosed part depicted in each coronary artery; a calculation unit configured to calculate a pressure gradient of each of the extracted coronary arteries, based on tissue blood flow volumes of the coronary arteries; a second extraction unit configured to extract an ischemic region depicted in the images; and a specifying unit configured to specify a responsible blood vessel of the ischemic region by referring to a dominance map, in which each of the extracted coronary arteries and a dominance territory are associated, for the extracted ischemic region, and to specify a responsible stenosis, based on the pressure gradient corresponding to a stenosed part in the specified responsible blood vessel.

The invention discloses an apparatus (100) for processing a medical image associated with a subject. The apparatus comprises a clinical information extractor (102) for determining clinical information associated with the medical image; a plurality of image processors (104), each image processor for performing at least one image processing task in respect of the medical image; and an image processing manager (106) for determining, based at least on the determined clinical information associated with the medical image, at least one image processor of the plurality of image processors to perform one or more tasks in respect of the medical image.