A method for preventing wrong-patient errors includes receiving a selection of a current imaging subject. The current imaging subject is selected for a current image acquisition session comprising capturing one or more current images of the current imaging subject utilizing at least a first image sensor system of a first imaging modality. The method includes accessing one or more previous images of a previous imaging subject. The one or more previous images depict the previous imaging subject according to at least a second imaging modality that is different from the first imaging modality. The method includes presenting the one or more previous images on a display system and, in response to determining that the previous imaging subject matches the current imaging subject based upon the one or more previous images, performing the current image acquisition session.

The present disclosure relates to an image information generation method, a pulse wave measurement system and an electronic device. The method comprises: with respect to a target part, acquiring a first infrared image sequence, each infrared image in the first infrared image sequence including at least a vein pattern; by registering the vein pattern in each infrared image in the first infrared image sequence, correcting each infrared image in the first infrared image sequence, thereby obtaining the corrected first infrared image sequence; removing at least the vein regions from respective infrared images in the corrected first infrared image sequence, to obtain image information of remaining regions as image information for pulse wave measurement.

Implementations relate to detecting/replacing transient obstructions from high-elevation digital images, and/or to fusing data from high-elevation digital images having different spatial, temporal, and/or spectral resolutions. In various implementations, first and second temporal sequences of high-elevation digital images capturing a geographic area may be obtained. These temporal sequences may have different spatial, temporal, and/or spectral resolutions (or frequencies). A mapping may be generated of the pixels of the high-elevation digital images of the second temporal sequence to respective sub-pixels of the first temporal sequence. A point in time at which a synthetic high-elevation digital image of the geographic area may be selected. The synthetic high-elevation digital image may be generated for the point in time based on the mapping and other data described herein.

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.

A method and system of diagnosing a medical condition of a target area of a patient using a mobile device are provided. One or more magnetic field images of a target area of a patient are received. One or more hyperspectral images of the target area of the patient are received. For each of the one or more magnetic field images and the one or more hyperspectral images, a three-dimensional (3D) position of the mobile device is tracked with respect to the target are of the patient. A 3D image of the target area is generated based on the received one or more magnetic field images, one or more hyperspectral images, and the corresponding tracked 3D position of the phone with respect to each image. A medical condition of the target area is diagnosed or monitored based on the generated 3D image.

An information processing apparatus calculates an index for a plant growth state with a neural network using fewer images to achieve training of the neural network. The apparatus includes first to N-th image analyzers (N≥2) each analyzing a cultivation area image of a plant cultivation area with a neural network to calculate a state index indicating a growth state of the plant in the cultivation area and including the neural network trained using cultivation area images each having a predetermined growth index classified into a corresponding class of first to N-th growth index classes, and a selector receiving an input of a cultivation area image for which the state index is calculated and causing one of the first to N-th image analyzers trained using cultivation area images classified into the same growth index class as the input cultivation area image to analyze the input cultivation area image.

An ear nose and throat (ENT) imaging and analysis system includes an endoscope usable to capture images of the nasal canal and other aspects of patient anatomy. Endoscopic images may be presented to a user via a touchscreen display, and the software may provide different imaging modes that aid in identifying particular anatomical structures or areas within the nasal canal. In one mode, the system uses an object recognition process to identify the nasal valve opening within the images at a relaxed state, and during forceful inhalation, and then calculates the difference between the two states, which may be suggestive of nasal valve collapse. In other modes, the system is configured to identify abnormalities of the inferior turbinate, septum, or other anatomy, as well as empty spaces within the nasal canal, as well as areas and volumes of empty space and user defined boundaries.

A system for facilitating developmental monitoring of children comprises one or more processors and one or more hardware storage devices storing instructions that are executable by the one or more processors to configure the system to (i) access a set of image data depicting a subject, (ii) extract a set of features from the set of image data, the set of features indicating one or more body characteristics of the subject as represented in the set of image data, and (iii) determine a set of developmental metrics for the subject based upon the set of features, the set of developmental metrics being indicative of a developmental state for the subject.

The present invention relates to a device (1) for fractional flow reserve determination. The device (1) comprises a model generator (10) configured to generate a three-dimensional model (3DM) of a portion of an imaged vascular vessel tree (VVT) surrounding a stenosed vessel segment (SVS), based on a partial segmentation of the imaged vascular vessel tree (VVT). Further, the device comprises an image processor (20) configured to calculate a blood flow (Q) through the stenosed vessel segment (SVS) based on an analysis of a time-series of X-ray images of the vascular vessel tree (VVT). Still further, the device comprises a fractional-flow-reserve determiner (30) configured to determine a fractional flow reserve (FFR) based on the three-dimensional model (3DM) and the calculated blood flow.

Implementations relate to detecting/replacing transient obstructions from high-elevation digital images, and/or to fusing data from high-elevation digital images having different spatial, temporal, and/or spectral resolutions. In various implementations, first and second temporal sequences of high-elevation digital images capturing a geographic area may be obtained. These temporal sequences may have different spatial, temporal, and/or spectral resolutions (or frequencies). A mapping may be generated of the pixels of the high-elevation digital images of the second temporal sequence to respective sub-pixels of the first temporal sequence. A point in time at which a synthetic high-elevation digital image of the geographic area may be selected. The synthetic high-elevation digital image may be generated for the point in time based on the mapping and other data described herein.