A method for analyzing a digestive tract of a patient using ultrasound. The method includes receiving a plurality of ultrasound images taken over a time series, determining movement characteristics of objects within the ultrasound images based on movement of one or more pixels in the ultrasound images over the time series, and outputting a visual data that describes the movement characteristics.

Disclosed is a method and system for three-dimensional tracking of a target located within a body, the method performed using at least one processing system. A two-dimensional scanned image of the body including the target is processed to obtain a two-dimensional image of the target. A first present dataset of the target is predicted using a previous dataset of the target and a state transition model, the first present dataset includes a three-dimensional present position value of the target. A second present dataset of the target is measured by template-matching of the two-dimensional image of the target with a model of the target. A third present dataset of the target is estimated by statistical inference using the first present dataset and the second present dataset. The previous dataset of the target is updated to match the third present dataset.

A method for providing a global cardiac wall motion classification for a patient is disclosed, and includes employing Cardiac Magnetic Resonance (CMR) image data. In some embodiments, the method comprises one or more of a myocardium segmentation step, a slice classification step, a movement feature extraction step, and a global classification or evaluation step, wherein a patient is classified as having normal cardiac wall motion, or as having suspicious or abnormal cardiac wall motion.

Described herein is medical imaging technology for concurrent and simultaneous synthesis of a medical CA-free-AI-enhanced image and medical diagnostic image analysis comprising: receiving a medical image acquired by a medical scanner in absence of contrast agent enhancement; providing the medical image to a computer-implemented machine learning model; concurrently performing a medical CA-free-AI-enhanced image synthesis task and a medical diagnostic image analysis task with the machine learning model; reciprocally communicating between the image synthesis task and the image analysis task for mutually dependent training of both tasks. Methods and systems and non-transitory computer readable media are described for execution of concurrent and simultaneous synthesis of a medical CA-free-AI-enhanced image and medical diagnostic image analysis.

An image processing apparatus according to the present invention calculates, even in a case where a region of a part as an observation target included in an image capturing range is different between a plurality of medical images in different time phases, a degree of slippage of the region of the part as the observation target with high accuracy.

A liquid transfer monitoring method to monitor a transfer state of a liquid such as a sample or a reagent having a high transparency which transmits light is provided. The liquid transfer monitoring method comprises a step of transferring a liquid 30 held in a first liquid holding portion 21 to a second liquid holding portion 22 connected to the first liquid holding portion 21, a step of acquiring information 40 relating to a scattered light intensity obtained by irradiating light 91 on the irregular inner surface 23 of at least one of the first liquid holding portion 21 and the second liquid holding portion 22 after starting the transfer of the liquid 30, and a step of monitoring the liquid transfer to the second liquid holding portion 22 based on the information 40 relating to the intensity of scattered light.

A method for evaluating the effectiveness of a skin treatment on a skin feature includes correcting the color of a first image before the skin treatment, correcting the color of a second image after the skin treatment, determining the sizes of the skin feature in the first and second images, and comparing the corrected colors and sizes of the skin feature in the first and second images. In some embodiments, the first and second images include the skin feature and an indicator adjacent to the skin feature, where the indicator has a standard color and a known size.

A dynamic anatomic atlas is disclosed, comprising static atlas data describing atlas segments and dynamic atlas data comprising information on a dynamic property which information is respectively linked to the atlas segments.

A weeding system for an agricultural weeding vehicle including at least one camera for mounting on an agricultural vehicle to acquire an image of a portion of a field while the agricultural vehicle is moving. The system also includes a spraying unit to be mounted on the agricultural vehicle, a control unit to receive images from the camera, generate a weed species detection signal and selectively cause the spraying of a chemical agent by the spraying unit on the basis of the weed species detection signal. The control unit executes a training-based algorithm based on a set of reference images labeled to indicate the presence or not of at least one weed species in the images.

The present invention has as its objective a procedure for assisting a forensic expert in making decisions in order to identify subjects by comparing images of rigid anatomical structures. This procedure includes a decision-making stage based on a hierarchical analysis model that, in particular realizations, is complemented by a previous stage of segmentation of osseous images and their superimposition.