A system for endurance testing including: at least one sensor configured to collect data associated with an individual's movement for an endurance test; an action module configured to determine endurance movements from the collected data and determine a set of test action; and an analysis module configured to analyze the set of test actions to provide a result for the endurance test. A method for endurance testing including: collecting data associated with an individual's movement, via at least one sensor; determining endurance movements from the collected data; determining a set of test action from the endurance movements; analyzing the set of test actions; and providing results associated with the endurance test based on the analyzed set of test actions.

A condition determination device includes a hardware processor that: acquires sensor information obtained by detecting information regarding a subject to be radiographed by using a sensor and order information regarding a radiographing order; and determines a radiographing condition by inputting the sensor information and the order information to a trained identifier.

Systems and methods for estimating quantitative histological features of a subject's tissue based on medical images of the subject are provided. For instance, quantitative histological features of a tissue are estimated by comparing medical images of the subject to a trained model that relates histological features to multiple different medical image contrast types, whether from one medical imaging modality or multiple different medical imaging modalities. In general, the trained model is generated based on medical images of ex vivo samples, in vitro samples, in vivo samples or combinations thereof, and is based on histological features extracted from those samples. A machine learning algorithm, or other suitable learning algorithm, is used to generate the trained model. The trained model is not patient-specific and thus, once generated, can be applied to any number of different individual subjects.

The present disclosure provides a system and method for image data acquisition. The method may include acquiring physiological data of a subject. The physiological data may correspond to a motion of the subject over time. The method may include obtaining a trained machine learning model configured to detect feature data represented in the physiological data. The method may include determining, based on the physiological data, an output result of the trained machine learning model that is generated based on the feature data. The method may include acquiring, based on the output result, image data of the subject using an imaging device.

A method and system for determining a PET image of the scan volume based on one or more PET sub-images is provided. The method may include determining a scan volume of a subject supported by a scan table; dividing the scan volume into one or more scan regions; for each scan region of the one or more scan regions, determining whether there is a physiological motion in the scan region; generating, based on a result of the determination, a PET sub-image of the scan region based on first PET data of the scan region acquired in a first mode or based, at least in part, on second PET data of the scan region acquired in a second mode; and generating a PET image of the scan volume based on one or more PET sub-images.

A method for quantitative flow analysis of a fluid flowing in a conduit from a sequence of consecutive image frames of such a conduit, where such image frames are timely separated by a certain time interval, the method comprising: a) selecting a start image frame and an end image frame from the sequence either automatically or upon user input; b) determining a centerline of the conduit in the start image frame; c) determining a centerline of the conduit in the end image frame; d) selecting a common start point on the centerline of the start image frame and on the centerline of the end image frame either automatically or upon user input; e) selecting an end point on the centerline of the start image frame; f) selecting an end point on the centerline of the end image frame; g) calculating centerline distance between the start point and the end point of the start image frame; h) calculating centerline distance between the start point and the end point of the end image frame; and i) calculating a local flow velocity as a function of the centerline distances of g) and h) and a time interval between the start image frame and the end image frame.
A corresponding imaging device and computer program are also disclosed.

Disclosed is an X-ray image processing apparatus including a data obtaining unit generating first to N-th images indicating an internal structure of an object and an image processing unit receiving the first to N-th images from the data obtaining unit, detecting a movement of the object, and generating a final image from the first to N-th images based on the movement of the object. The data obtaining unit actively controls an X-ray pulse irradiated based on the movement of the object.

A system and method for integrating and synchronizing an automated mechanical cardiopulmonary resuscitation (CPR) device with components of cardiac catheterization laboratories so as to enhance the efficacy of each intervention. Synchronization can include image gating so that a monitor shows real time images during relaxation of the CPR, and a static image during compression of the CPR.

An X-ray CT apparatus of an embodiment acquires projection data of a subject based on X-ray detection data according to biometric information synchronous scanning and generates a CT image of the subject based on the projection data. The X-ray CT apparatus includes a first acquisition unit, a determination unit, and a second acquisition unit. The first acquisition unit acquires biometric information of the subject at a timing when the biometric information synchronous scanning has been performed. The determination unit determines, as priority data, detection data that is a target for which data transfer will be preferentially performed among X-ray detection data acquired in the biometric information synchronous scanning based on the biometric information. The second acquisition unit acquires the priority data from a storage device that holds the detection data.

The invention relates to a system and a method for determining a characteristic of a blood vessel portion, which comprises blood including a contrast agent exhibiting resonant absorption of x-ray photons at a specific energy. The system comprises a tunable monochromatic x-ray source (21) emitting x-ray radiation, an x-ray detector device (22) for detecting the x-ray radiation after it has travelled through the blood vessel portion. A control unit (26) varies a tuning of the x-ray source (21) to vary the energy of the x-ray radiation emitted by the x-ray source (21), and an evaluation unit (27) determines a tuning of the x-ray source (21) at which nuclear resonant absorption of the x-ray radiation incident onto the blood vessel portion occurs and estimates the characteristic on the basis of the determined tuning. The characteristic may particularly be the blood velocity in the blood vessel portion.