Abstract: A method of denoising a plurality of input images, including grouping the plurality of input images into a plurality of groups; determining, for each group of the plurality of groups, an initial representative image for the group; performing, for each group, a sequence of T1 denoising sampling steps using a diffusion-based probabilistic model, starting with the initial representative image for the group, to generate a corresponding sequence of representative images for the group, wherein T1 is an integer greater than or equal to 1; and for each input image in each group, performing a second sequence of T2 denoising sampling steps using the model to generate a final image that is a restored image corresponding to the input image, wherein T2 is an integer greater than or equal to 1, and T=T1+T2.

Abstract: The present disclosure provides a data maximum/minimum value (max/min) aggregation method and system for privacy protection. A Paillier cryptosystem is used to encrypt user data, so as to protect privacy and security of user health data. Further, time aggregation is implemented to help a control center obtain an overall health condition of a client in one aggregation period. By using a homomorphic property of the Paillier cryptosystem, the present disclosure implements aggregation of a max/min of privacy protection, and helps the control center obtain a max or a min of health data of the client in the aggregation period.

Abstract: A method of denoising a plurality of input images, including grouping the plurality of input images into a plurality of groups; determining, for each group of the plurality of groups, an initial representative image for the group; performing, for each group, a sequence of T1 denoising sampling steps using a diffusion-based probabilistic model, starting with the initial representative image for the group, to generate a corresponding sequence of representative images for the group, wherein T1 is an integer greater than or equal to 1; and for each input image in each group, performing a second sequence of T2 denoising sampling steps using the model to generate a final image that is a restored image corresponding to the input image, wherein T2 is an integer greater than or equal to 1, and T=T1+T2.

Abstract: A method for performing cardiac motion compensation in a computed tomography (CT) imaging system is provided. The method includes receiving projection data acquired from an imaging object by the CT imaging system. The method also includes, until a predefined termination criterion is met, iteratively reconstructing, based on estimated cardiac motion, the received projection data to generate a motion-compensated image of the imaging object, determining a vessel region of interest (ROI) within the generated motion-compensated image, and updating the estimated cardiac motion, based on an optimization cost function associated with the determined vessel ROI. The method further includes outputting, as a final reconstructed image of the imaging object, the generated motion-compensated image.

Abstract: A medical image processing method includes obtaining a set of projection data acquired in a computed tomography (CT) scan of a three-dimensional region of an object to be examined; generating for each time point of a plurality of time points of the CT scan based on a part of the obtained set of projection data corresponding to the time point, a pair of feature maps for estimating motion at the time point so as to generate a plurality of pairs of feature maps, each feature map representing a feature of an image reconstructed from the part of the obtained set of projection data; estimating, based on the generated plurality of pairs of feature maps, a four-dimensional motion field; and reconstructing, based on the estimated four-dimensional motion field and the obtained set of projection data, a CT image of the object.

Abstract: A medical data processing method according to an embodiment includes inputting first medical data relating to a subject imaged with a medical image capture apparatus to a learned model to configured to generate second medical data having lower noise than that of the first medical data and having a super resolution compared with the first medical data based on the first medical data to output the second medical data.

Abstract: A changeover valve includes: a valve body and an internal-communication air duct and a driving device arranged in the valve body; wherein the valve body is connected with a housing of a vacuum cleaner, the housing is provided with a ventilation opening, an air inlet duct for driven inlet air and an air outlet duct for driven outlet air, the ventilation opening is provided with a filter element, a first end of the internal-communication air duct is connected with the ventilation opening, an outer side of the internal-communication air duct is connected with the driving device, so that the driving device drives a second end of the internal-communication air duct to rotate by a preset angle, the second end of the internal-communication air duct is connected at the air inlet duct and the air outlet duct communicates with the external space.

Abstract: A medical image processing method includes obtaining a first set of projection data by performing, with a first CT apparatus including a first detector with a first pixel size, a first CT scan of an object in a first imaging region of the first detector; obtaining a first CT image with a first resolution by reconstructing the first set of projection data; obtaining a processed CT image with a resolution higher than the first resolution by applying a machine-learning model for resolution enhancement to the first CT image; and displaying the processed CT image or outputting the processed CT image for analysis. The machine-learning model is obtained by training using a second CT image based on a second set of projection data acquired by a second CT scan of the object in a second imaging region with a second CT apparatus including a second detector with a second pixel size.

Abstract: An information processing method of an embodiment is a processing method of information acquired by imaging performed by a medical image diagnostic apparatus, the information processing method includes the steps of: acquiring noise data by imaging a phantom using a medical imaging apparatus; based on first subject projection data acquired by the imaging performed by a medical image diagnostic modality of a same kind as the medical image diagnostic apparatus and the noise data, acquiring synthesized subject data in which noise based on the noise data is added to the first subject projection data; and acquiring a noise reduction processing model by machine learning using the synthesized subject data and second subject projection data acquired by the imaging performed by the medical image diagnostic modality.

Abstract: A blockchain data index method, a blockchain data storage method and a device are provided. This method first persists a block into a block file, persists an index data layer into an index database, then obtains a matching transaction location according to a query condition, and finally obtains a complete transaction from the block file. In the present application, through expanding the process of the blockchain data storage processing, the blockchain index data is stored in an independent index database and transaction atomicity of multi-database is guaranteed, and a data index mechanism, in which business information is customized in a transaction note field, and then a transaction is associated with the business information through the customized transaction note index field and finally the complete transaction is acquired based on key transaction information, is established.

Abstract: According to some embodiments, a method comprises obtaining a group of reconstructed-image data; converting the group of reconstructed-image data to a derivative of Radon space, thereby generating Radon-space data, wherein the Radon-space data have a radial sampling pattern in the derivative of Radon space; and generating resampled data by inputting the Radon-space data into a first trained machine-learning model for resampling Radon-space data, wherein the resampled data have a cone-beam-projection-geometry-shaped sampling pattern in the derivative of Radon space.

Abstract: A method for scatter estimation in a CT including a detector having multiple detector pixels includes: obtaining projection data by scanning an imaging object; reconstructing image data from the projection data; estimating, based on the projection data, a first scatter distribution; selecting, based on the first scatter distribution, a first subset of the pixels; calculating, based on the projection data and the image data, a second scatter distribution with respect to the selected first subset, the second scatter distribution having higher accuracy than the first scatter distribution; acquiring, based on the second scatter distribution, a third scatter distribution with respect to a second subset of the pixels, the third scatter distribution having higher spatial resolution than the second scatter distribution.

Abstract: An ultrasound diagnosis apparatus of an embodiment includes storage circuitry and processing circuitry. The storage circuitry stores therein a trained model trained using a first ultrasound signal containing a saturated signal as input data and a second ultrasound signal in which effect of saturation is reduced from the first ultrasound signal, as target data. The processing circuitry inputs a third ultrasound signal containing a saturated signal to the trained model and acquires a fourth ultrasound signal that is output from the trained model and in which effect of saturation is reduced from the third ultrasound signal, to generate the fourth ultrasound signal.

Abstract: A method of controlling computed tomography (CT) scanning includes performing a scout CT scan of a 3D region of a head of a subject to be examined, using a CT gantry having an X-ray source and an X-ray detector both rotatably supported thereby, to produce image data. Anatomical landmarks are detected for identifying an orbitomeatal base line (OMBL), by inputting cross-sectional image data of the 3D region generated from the image data to a trained machine learning model. A tilt angle of the CT gantry is determined based on the detected anatomical landmarks. A diagnostic CT scan of the object is performed using the CT gantry tilted at the determined tilt angle.

Abstract: A method for harmonic imaging is provided and includes inputting first training ultrasound data, including a fundamental component and a harmonic component, to each of a plurality of teacher models, and training each teacher model with the first training ultrasound as teacher input data and second training ultrasound data, including the harmonic component, as teacher target data; acquiring, for each teacher, corresponding first estimated data output from the teacher model, in response to input of first ultrasound data to the teacher model; selecting a first particular teacher model by evaluating the corresponding first estimated data output from each of the trained teacher models; and training a student model with the first ultrasound data as student input data and the corresponding first estimated data of the selected first particular teacher model as student target data.

Abstract: An information processing method controls a CT scanner such that the method includes, but is not limited to, determining an X-ray irradiation period from an electrocardiogram acquired from an electrocardiography device attached to a living object to be imaged, by processing the electrocardiogram at multiple different cardiac phases; performing, by controlling a CT gantry including and rotatably supporting an X-ray source and an X-ray detector, a diagnostic CT scan in the determined X-ray irradiation period, of at least a part of the heart region, to obtain a CT image; and causing a display unit to display the obtained CT image. The method can be performed at least by an information processing apparatus including processing circuitry and/or computer instructions stored in a non-transitory computer readable storage medium for performing the method.

Abstract: An apparatus, method, and computer-readable medium having processing circuitry to receive first ultrasound data including at least one harmonic component, and apply the first ultrasound data to inputs of a trained deep neural network model that outputs enhanced ultrasound image data, the deep neural network model having been trained with training data including input ultrasound data and corresponding target ultrasound data having predetermined target features, and output the enhanced ultrasound image data.

Abstract: An integrated circuit structure and a chip are provided. The chip includes a first pad set, a second pad set, a connection circuit, and a signal pad set. The first pad set includes a plurality of first pads. The second pad set includes a plurality of second pads respectively corresponding in position to the first pads. Each of the first pads and the corresponding second pad are electrically coupled to each other through the connection circuit so as to be operable by choosing one therefrom. The signal pad set arranged between the first pad set and the second pad set and includes a plurality of signal pads.

Abstract: A changeover valve includes: a valve body and an internal-communication air duct and a driving device arranged in the valve body; wherein the valve body is connected with a housing of a vacuum cleaner, the housing is provided with a ventilation opening, an air inlet duct for driven inlet air and an air outlet duct for driven outlet air, the ventilation opening is provided with a filter element, a first end of the internal-communication air duct is connected with the ventilation opening, an outer side of the internal-communication air duct is connected with the driving device, so that the driving device drives a second end of the internal-communication air duct to rotate by a preset angle, the second end of the internal-communication air duct is connected at the air inlet duct and the air outlet duct communicates with the external space.

Abstract: An ultrasound diagnosis apparatus according to an embodiment includes processing circuitry. This processing circuitry collects a first ultrasound signal including one or more harmonic components. By executing weighed addition processing where a coefficient distribution is applied to the first ultrasound signal for different directions of two or more dimensions, the processing circuitry generates a second ultrasound signal including components of each order at a ratio different, at a specific frequency, from a ratio among the frequency components included in the first ultrasound signal.