A medical image processing apparatus comprises processing circuitry configured to select a reference image from blood vessel images based on contrast images acquired in time series and conduct a transformation process on other blood vessel images such that blood vessel shapes in the other blood vessel images match a blood vessel shape in the reference image, generate a color image where a color that corresponds to a temporal change in a pixel value is assigned to each pixel based on the blood vessel images after the transformation process, and display the color image on a display.

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for jointly training an encoder neural network and a decoder neural network. In one aspect, a method comprises: updating current values of a set of encoder parameters and current values of a set of decoder parameters using gradients of a reconstruction loss function that measures an error in a reconstruction of multi-modal data from a training example, wherein: the reconstruction loss function comprises a plurality of scaling factors that each scale a respective term in the reconstruction loss function that measures an error in the reconstruction of a corresponding proper subset of feature dimensions of the multi-modal data from the training example.

[Object] To provide an information processing device, an information processing method, and a program. [Solution] The information processing device including: a region specification unit configured to specify a biological region for biometric authentication from image data; and an image processing unit configured to perform image processing on a processing region corresponding to the biological region such that biological information acquirable from the biological region is changed.

A system and method for developing applications (Apps) for automated assessment and analysis of processed biological samples. Such samples are obtained, combined with nutrient media and incubated. The incubated samples are imaged and the image information is classified according to predetermined criteria. The classified image information is then evaluated according to Apps derived from classified historical image information in a data base. The classified historical image information is compared with the classified image information to provide guidance on further processing of the biological sample through Apps tailored to process provide sample process guidance tailored to the classifications assigned to the image information.

Systems and methods for producing ultrasound images are disclosed herein. In one embodiment, ultrasound image data are acquired in discrete time increments at one or more positions relative to a subject. Control points are added by a user for two or more image frames and a processor interpolates the location of the control points for image frames obtained at in-between times.

A method of modeling lungs of a patient includes acquiring computed tomography data of a patient's lungs, storing a software application within a memory associated with a computer, the computer having a processor configured to execute the software application, executing the software application to differentiate tissue located within the patient's lung using the acquired CT data, generate a 3-D model of the patient's lungs based on the acquired CT data and the differentiated tissue, apply a material property to each tissue of the differentiated tissue within the generated 3-D model, generate a mesh of the 3-D model of the patient's lungs, calculate a displacement of the patient's lungs in a collapsed state based on the material property applied to the differentiated tissue and the generated mesh of the generated 3-D model, and display a collapsed lung model of the patient's lungs based on the calculated displacement of the patient's lungs.

Methods and systems for determining whether brain tissue is indicative of a disorder, such as a neurodegenerative disorder, are provided. The methods and systems generally utilize data processing techniques to assess a level of congruence between measured parameters obtained from magnetic resonance imaging (MRI) data and simulated parameters obtained from computational modeling of brain tissues.

An image processing apparatus (10) is disclosed that comprises a processor arrangement (16) adapted to receive image data corresponding to a region of interest (1) of a patients cardiovascular system, said image data comprising a temporal sequence (15) of intravascular ultrasound images acquired (150) at different phases of at least one cardiac cycle of said patient, said intravascular ultrasound images imaging overlapping volumes of the patient's cardiovascular system; implement a spatial reordering process of said temporal sequence of intravascular ultrasound images by evaluating the image data to select at least one spatial reference (6, Vref) associated with said temporal sequence of intravascular ultrasound images; estimating a distance to the at least one spatial reference for each of the intravascular ultrasound images of said temporal sequence; and reordering said temporal sequence of intravascular ultrasound images into a spatial sequence of intravascular ultrasound images based on the estimated distances; and generate an output comprising said spatial sequence of intravascular ultrasound images. Also disclosed are a method and computer program product to configure an image processing apparatus accordingly.

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.

An apparatus, method and computer program is described comprising: receiving video data for a scene; determining a movement measurement for at least some of a plurality of subframes of the video data; weighting the movement measurements to generate a plurality of weighted movement measurements, wherein the weighting is dependent on the subframe; and generating a movement indication for the scene from a combination of some or all of the weighted movement measurements.