Systems and methods for determining a heath status of a patient through an automated interview. One of the systems include one or more computers in one or more locations and one or more storage devices storing instructions that, when executed by one or more computers, cause the one or more computers to perform operations including: providing, to a user interface of a user device, questions for a user to respond to in an interactive manner, in which each of the questions following the first questions is adaptive based on the user's response to one or more of the previous questions; capturing motion and appearance of the user in a video sequence while the user is responding to the questions; and analyzing the motion of the user in the video sequence to determine one or more indications of a disease or of a change in a disease progression.

A method comprising: receiving an image stream of a mammalian cardiac muscle cell; defining or having defined a region of interest (ROI) within said cell; calculating a fast Fourier transform (FFT) of said ROI; detecting peaks in said FFT; and determining at least one of sarcomere length, mitochondrial length, and mitochondrial width, based, at least in part, in said detected peaks

A sensor system that employs sub-pixel sized beads for assays is disclosed. The sensor system includes a first plurality of sensor pixels that define a first active sensor area. The first active sensor area is configured to receive a first portion of a fluid sample. The first portion is mixed with a plurality of first functionalized beads for performing a first assay. The sensor system also includes at least a second plurality of sensor pixels that define a second active sensor area. The second active sensor area is configured to receive a second portion of the fluid sample. The second portion is mixed with a second plurality of functionalized beads for performing a second assay. The first assay and the second assay may be configured to detect different concentration ranges of an analyte in the fluid sample.

The present disclosure relates to a method, storage medium, and system for analyzing an image sequence of a periodic physiological activity. In one implementation, the method includes receiving the image sequence acquired by an imaging device, the image sequence having a plurality of frames, and identifying a feature point in a first frame. The method further includes determining motion vectors for the feature point in the frames of the image sequence. Each motion vector for the feature point is determined based on respective locations of corresponding feature points in frames adjacent to the first frame. The method also includes determining a motion magnitude profile based on the determined motion vectors and determining a phase of each frame in the image sequence based on the motion magnitude profile.

A device includes: a distribution information acquiring part configured to acquire, based on an image in which a plurality of cells that are cultivated in a predetermined area are imaged, distribution information relating to a distribution in the predetermined area of the plurality of cells; and a determination part configured to determine a cultivated state of the plurality of cells based on the distribution information acquired by the distribution information acquiring part.

In positron emission tomography (PET) imaging, PET imaging data (22) having TOF localization is reconstructed. TOF image reconstruction (30) is performed on the PET imaging data to produce a TOF reconstructed image (32). The TOF image reconstruction utilizes the TOF localization of the PET imaging data. Non-TOF image reconstruction (40) is also performed on the PET imaging data to produce a non-TOF reconstructed image (42). The non-TOF image reconstruction does not utilize the TOF localization of the PET imaging data. A comparison image (50) is computed which is indicative of differences between the TOF reconstructed image and the non TOF reconstructed image. An adjustment (54) is determined for the TOF image reconstruction based on the comparison image, such as alignment correction of an attenuation map (18), and the TOF image reconstruction is repeated on the PET imaging data with the determined adjustment to produce an adjusted TOF reconstructed image.

There are provided a medical image processing apparatus, an endoscope apparatus, a diagnostic support apparatus, and a medical service support apparatus capable of detecting red blood cells using an endoscope image. A medical image processing apparatus includes: a medical image acquisition unit that acquires short wavelength medical images, which are medical images including a subject image and which are obtained by imaging a subject with light in a shorter wavelength band than a green wavelength band; and a red blood cell detection unit that detects red blood cells using the short wavelength medical images. The light in the short wavelength band is, for example, light in a blue band or a violet band of a visible range. The red blood cell detection unit detects, for example, a high-frequency, granular, and high-density region as red blood cells.

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.

Clinical assessment devices, systems, and methods are provided. A clinical assessment system, comprising a processor in communication with an imaging device, wherein the processor is configured to receive, from the imaging device, a sequence of image frames representative of a contrast agent perfused subjects tissue across a time period; classify the sequence of image frames into a plurality of first tissue classes and a plurality of second tissue classes based on a spatiotemporal correlation among the sequence of image frames by applying a predictive network to the sequence of image frames to produce a probability distribution for the plurality of first tissue classes and the plurality of second tissue classes; and output, to a display in communication with the processor, the probability distribution for the plurality of first tissue classes and the plurality of second tissue classes.

An analysis device includes: a cell image acquisition unit that acquires a plurality of cell images in which a stimulated cell has been captured; a feature value calculation unit that calculates a feature value for each of first and second constituent elements constituting the cell, from the cell images acquired by the cell image acquisition unit; a correlation calculation unit that calculates correlations between first feature values and between second feature values in the first and second constituent elements calculated by the feature value calculation unit; a correlation extraction unit that extracts the correlation between the first feature values by selecting the first feature values with respect to the correlations between the feature values in the first and second constituent elements calculated by the correlation calculation unit; and a display unit that displays the correlation between the first feature values extracted by the correlation extraction unit.