A system for monitoring vital signs includes: an imaging device for acquiring video image files of a living individual; a data analysis system including a processor and memory; a computer program running in the data analysis system to automatically analyze the video images, autonomously identify an area in the images where periodic movements associated with a selected vital sign may be detected and quantified; and, an interface that outputs an electrical signal corresponding to the waveform of the selected vital sign. The system may include a Graphical User Interface, which may display a visual graph of the waveform and a single video frame or a video stream of the individual.

There is provided an optical distance measurement system including an image sensor and a processing unit. The processing unit is configured to generate an image to be calculated according to at least one image captured by the image sensor, wherein different image regions of the image to be calculated correspond to different exposure times thereby improving the accuracy of the distance calculation.

A system for obtaining dark current images includes 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 perform various acts. The acts include obtaining a first image frame, generating a first low-pass filtered image by applying a low-pass filter to the first image frame, and generating a first estimated dark current image by subtracting the first low-pass filtered image from the first image frame.

The present disclosure relates to methods, devices, and systems for blending geographic data when combining geographic data sources. The methods, devices, and systems identify a blend region for transitioning between a first dataset and a second dataset. The methods, devices, and systems extrapolate geographic data from the second dataset to blend with the geographic data from the first dataset to create blended elevation data in the blend region. The methods, devices, and systems may generate an image for a geographic region with the first set of geographic data, the second set of geographic data, and the blended elevation data.

In certain embodiments, an ophthalmic laser surgical system for imaging and treating a target in an eye includes an optical coherence tomography (OCT) device that: directs an imaging beam towards the eye; generates three-dimensional (3D) image data from the imaging beam reflected from the eye; and generates two-dimensional (2D) enface images from the 3D image data. The 2D enface images include a target enface image imaging the target in the eye and a retinal enface image imaging a shadow cast by the target onto the retina. An xy-scanner directs the imaging beam along an imaging beam path towards the eye, and directs a laser beam from the laser device along a laser beam path aligned with the imaging beam path towards the eye. A computer compares the target of the target enface image and the shadow of the retinal enface image to confirm the presence of the target.

A method, system and computer program product for divided processing in providing object detection focus is disclosed. The system includes a first video analytics determinator configured to provide, by infrequent employment thereof within the system, a partial object detection focus in first information that informs as to where moving objects are likely and unlikely to appear within video frames in respect of video. The system also includes a second video analytics determinator configured to: informatively employ the first information to determine a refined object detection focus; and provide the refined tracking and/or object detection focus in second information.

An image processing apparatus includes an obtaining unit configured to obtain a first radiation image of an inspection target object that has been captured by a radiation imaging apparatus, and a generation unit configured to generate a second radiation image including noise reduced as compared with the first radiation image, by inputting the first radiation image obtained by the obtaining unit, to a learned model obtained by performing learning using learning data including a radiation image to which noise simulating system noise of a radiation imaging apparatus in accordance with a distribution that is based on a manufacturing variation of a radiation imaging apparatus is added.

A method includes obtaining waveform return data including waveform return records for multiple sampling events associated with an observed area and determining a relevance score for the waveform return records of the waveform return data. The relevance score for a particular waveform return record is based, at least partially, on estimated information gain associated with the particular waveform return record. The method also includes, based on the relevance scores, selecting a first subset of waveform return records, where one or more waveform return records are excluded from the first subset of waveform return records. The method also includes generating image data based on the first subset of waveform return records.

Methods and systems are provided for improving model robustness and generalizability. The method may comprise: acquiring, using a medical imaging apparatus, a medical image of a subject; reformatting the medical image of the subject in multiple scanning orientations; applying a deep network model to the medical image to improve the quality of the medical image; and outputting an improved quality image of the subject for analysis by a physician.

Systems and methods are provided for registering images. The systems and methods perform operations comprising: receiving, at a first time point in a given radiation session, a first imaging slice corresponding to a first plane; encoding the first imaging slice to a lower dimensional representation; applying a trained machine learning model to the encoded first imaging slice to estimate an encoded version of a second imaging slice corresponding to a second plane at the first time point to provide a pair of imaging slices for the first time point; simultaneously spatially registering the pair of imaging slices to a volumetric image, received prior to the given radiation session, comprising a time-varying object to calculate displacement of the object; and generating an updated therapy protocol to control delivery of a therapy beam based on the calculated displacement of the object.