A system, method, and computer readable media are provided for obtaining a first set of skin data from an image capture system including at least one ultraviolet (UV) image of a user's skin. Performing a correction on the skin data using a second set of skin data associated with the user. Quantifying a plurality of skin parameters of the user's skin based on the first skin data, including quantifying a bacterial load. Quantifying the bacterial load by applying a brightness filter to isolate portions of the at least one UV image containing fluorescence, applying a dust filter, identifying portions of the at least one UV image that contain fluorescence due to bacteria, and determining a quantity of bacterial load in the users skin. Determining, using a machine learning model, an output associated with a normal skin state of the user and a current skin state of the user.

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.

A method for determining residue coverage within a field may include receiving, with one or more computing devices, first and second images of the field. The first image may depict a portion of the field at a first time during a crop-growing period and the second image may depict the portion of the field at a second time during the crop-growing period, with the first and second times being different. Furthermore, the method may include generating, with the one or more computing devices, an estimated residue coverage map for the field based on the received first and second images. Additionally, the method may include generating, with the one or more computing devices, a prescription map for the field based on the estimated residue coverage map.

The present application relates to an automated segmentation method for use with echocardiograms (echo). The method uses an iterative Dijkstra's algorithm, a strategic node selection, and a novel cost matrix formulation based on intensity peak prominence and is this termed the “Prominence Iterative Dijkstra's” algorithm, or ProID.

A computer-implemented method of detecting and quantifying a spinal curve is disclosed herein. The method comprises obtaining a Forward-Looking Infrared Radiometer (FLIR) camera, calibrating the FLIR camera to room temperature, stabilizing the FLIR camera for imaging of a spine of a subject at a position horizontally spaced about ½ to about 3 meters, or about ½ to about 2 meters, from the camera, scanning at least a portion of the spine with the FLIR camera to obtain thermal data, and generating an image of the subject's spine. Corresponding systems and methods also are disclosed.

Examples of the present disclosure relate to systems and methods for generating more accurate image(s) of a user via a camera of a consumer product (e.g., mobile phone, tablet, laptop, etc.) for subsequent use in, for example, computer implemented applications, such as skin diagnosis, facial recognition, cosmetic simulation, selection and/or recommendation, etc. Examples of the systems and methods improve image accuracy and quality by addressing issues relating to unpredictable and inconsistent lighting conditions, among others. In an example, the system includes a mobile computing device and an object with known lighting and/or color attributes (e.g., a reference). Such an object acts as a calibration device for images to be captured by the mobile computing device.

A method for medical imaging may include obtaining a plurality of successive images of a region of interest (ROI) including at least a portion of an object's heart. The plurality of successive images may be based on imaging data acquired from the ROI by a scanner without electrocardiography (ECG) gating. The plurality of successive images may be related to one or more cardiac cycles of the object's heart. The method may also include automatically determining, in the plurality of successive images, target images that correspond to at least one of the one or more cardiac cycles of the object's heart.

A pre-5.sup.th-Generation (5G) or 5G communication system for supporting higher data rates Beyond 4.sup.th-Generation (4G) communication system such as long term evolution (LTE) is provided. The method for operating a server includes receiving a first image including at least one tree, determining whether to generate a tree map based on the first image, based on a difference between first tree region data of the first image and second tree region data of a second image which is prestored, and generating the tree map according to determining.

Examples of methodologies and technologies for determining changes in one or more skin conditions of a user over time are described herein. Any changes in skin conditions over time may be used as a diagnosis and/or treatment aid for a physician. Any changes in skin conditions over time may be also used in a computer implemented method that provides diagnosis and/or treatment recommendations.

Systems and methods that facilitate determining interaction between medications and the brain using a brain measure and a brain model. Hidden nervous system states are difficult to predict, diagnose, and treat with therapeutic medications. A Dual Neural Machine Translation (d-NMT) algorithmic system that utilizes sets of parameters for a relapsing-remitting MS model based on patient medical records and adjusts a method of parameterization to produce a model that can match patients' medical records and medical images. These parameters are can be used by a therapeutic determining model to recommend therapies, doses, and time courses accurately.