Systems and methods are provided for use in processing image data associated with crop-bearing fields. One example computer-implemented method includes accessing a first data set including images associated with a field, where the images have a spatial resolution of about one pixel per at least about one meter, and generating, based on a generative model, defined resolution images of the field from the first data set. In doing so, the defined resolution images each have a spatial resolution of about X centimeters per pixel, where X is less than about 5 centimeters. The method also includes deriving index values for the field, based on the defined resolution images of the field, and predicting a characteristic (e.g., a yield, etc.) for the field based on the index values and, in some implementations, at least one environmental metric for the field.

A fully automated solution to vessel analysis based on image data including a system for analysis of a vessel that receives at least 2D images of a patient's vessels, the images obtained from two different angles during X-ray angiography, where the system uses color or grayscale features from a location of a stenosis in the images to provide an FFR value for the vessel.

The present invention relates to the field of medical monitoring, and, in particular, to non-contact detecting and monitoring of patient breathing. Systems, methods, and computer readable media are described for calculating a change in depth of a region of interest (ROI) on a patient and assigning one or more visual indicators to at least a portion of a graphic based on the calculated changes in depth and/or based on a tidal volume signal generated for the patient. In some embodiments, the systems, methods, and/or computer readable media can display the visual indicators overlaid onto at least the portion in real-time and/or can display the tidal volume signal in real-time. The systems, methods, and/or computer readable media can trigger an alert and/or an alarm when a breathing abnormality is detected.

The present invention relates to a method for cancer cell separation, and more specifically, relates to a method for cancer cell separation using micro-vibration.

A biological sample sorting method, a surface acoustic wave microfluidic chip, a system, a terminal, and a storage medium are disclosed. The method includes: injecting a mixed solution containing biological samples into a surface acoustic wave microfluidic chip, and applying a first sinusoidal signal thereto forming a standing wave sound field therein to aggregate the biological samples; collecting images of the aggregated biological samples; performing moving target identification and tracking on the images of the biological samples using a deep learning model, performing cluster analysis and classification on a tracked moving target to obtain a target sample, and generating a delay enabling signal of the target sample according to a moving speed of the target sample; and applying a second sinusoidal signal to the surface acoustic wave microfluidic chip according to the delay enable signal to move the target sample thus sorting out the target sample.

One variation of a method for monitoring growth of plants within a facility includes: aggregating global ambient data recorded by a suite of fixed sensors, arranged proximal a grow area within the facility, at a first frequency during a grow period; extracting interim outcomes of a set of plants, occupying a module in the grow area, from module-level images recorded by a mover at a second frequency less than the first frequency while interfacing with the module during the period of time; dispatching the mover to autonomously deliver the module to a transfer station; extracting interim outcomes of the set of plants from plant-level images recorded by the transfer station while sequentially transferring plants out of the module at the conclusion of the grow period; and deriving relationships between ambient conditions, interim outcomes, and final outcomes from a corpus of plant records associated with plants grown in the facility.

A method for processing digital subtraction angiography (DSA) or computed tomography (CT) images for reduced radiation exposure to a DSA or CT subject includes receiving, as input, a plurality of captured DSA or CT image frames of a contrast agent flowing through a volume of interest in a subject. The method further includes fitting a mathematical model to measured contrast agent density of individual voxels of the captured DSA or CT image frames to produce a mathematical model of contrast agent flow across the captured DSA or CT image frames. The method further includes sampling the mathematical model of contrast agent flow for the individual voxels to produce reconstructed DSA or CT image frames. The method further includes outputting at least one of the reconstructed CT or DSA image frames.

A process to identify a tailor-made cosmetic formula adapted to an user, including a step of collecting picture or video information, a step of storing said information into a database, a step of storing said information into a database, a step of comparing the collected information with the information in the database, a step of devising analysis results, characterized in that said process comprises a step of submission of a cosmetic formulation including at least one cosmetic base and/or at least one active ingredient tailored to the user.

The disclosure relates to the generation of radiological images of an examination area of an object under examination. On the basis of measured radiological images of an examination area that show blood vessels in the examination area with decreasing contrast intensity over time, the disclosure generates artificial radiological images of the examination area that show blood vessels with constant contrast intensity.

A processor for an endoscope includes an image processing unit that obtains a severity of a lesion in which a degree of progression is represented by one value, wherein the image processing unit includes a feature amount calculation unit configured to calculate a first pixel evaluation value indicating a degree of a first feature of appearance appearing in a lesion part, a representative value calculation unit configured to calculate a first representative evaluation value by integrating the first pixel evaluation values, and an integration unit configured to adjust an influence degree of the first representative evaluation value indicating a change in the severity with respect to a change in the first representative evaluation value based on information on a color component of an image, and calculate the severity of the lesion based on at least the first representative evaluation value by using the adjusted influence degree.