Abstract: A 3D anatomical model of one or more blood vessels of a patient may be obtained using CT angiography, while a 2D image of the blood vessels may be obtained based on fluoroscopy. The 3D model may be registered with the 2D image based on a contrast injection site identified on the 3D model and/or in the 2D image. A fused image may then be created to depict the overlaid 3D model and 2D image, for example, on a monitor or through a virtual reality headset. The injection site may be determined automatically or based on a user input that may include a bounding box drawn around the injection site on the 3D model, a selection of an automatically segmented area in the 3D model, etc.

Abstract: Digital breast tomosynthesis (DBT) may provide richer information than full-field digital mammography (FFDM). DBT data such as DBT slices may be processed based on deep learning techniques such as using a neural network, and the DBT slices may be divided into groups and a pre-determined number of representative images may be derived based on the grouping. The neural network may be configured to process the representative images to predict the presence or non-presence of a breast disease such as breast cancer.

Abstract: Mammography data such as DBT and/or FFDM images may be processed using deep learning based techniques, but labeled training data that may facilitate the learning may be difficult to obtained. Described herein are systems, methods, and instrumentalities associated with automatically generating and/or augmenting labeled mammography training data, and training a deep learn model based on the auto-generated/augmented data for detecting a breast disease (e.g., breast cancer) in a mammography image.

Abstract: For detecting motion in MR imaging, a regression model, such as a convolutional neural network, is machine trained. To generalize to MR imagers, MR contrasts, or other differences in MR image generation, the regression model is trained adversarially. The discriminator for adversarial training discriminates between classes of the variation source (e.g., type of MR imager or type of contrast) based on values of features learned in the regression model for detecting motion. By adversarial training, the regression model learns features that are less susceptible or invariant to variation in image source.

Abstract: The present disclosure relates to a control method of a virtual object, a control apparatus, a device and a medium. The method displays a target virtual scene in a target interactive interface, under the condition that there is a target virtual object in the plurality of virtual objects, displays a target control, the target virtual object being a virtual object controllable by the virtual subject in a non-contact manner; in response to receiving a trigger operation on the target control, causes the virtual subject to perform non-contact control on the target virtual object according to a control mode corresponding to the target control, wherein the target virtual scene includes a plurality of virtual objects and a virtual subject controlled by a user.

Abstract: Container data sharing is provided. A second container of a cluster of containers is started to process a service request in response to detecting a failure of a first container processing the service request. The service request and data generated by the first container that failed stored on a physical external memory device is accessed. The service request and the data generated by the first container that failed is loaded on the second container from the physical external memory device via a dedicated hardware link for high-speed container failure recovery.

Abstract: Techniques, systems, and devices are described for providing a computational frame for estimating high-dimensional stochastic behaviors. In one exemplary aspect, a method for performing numerical estimation includes receiving a set of measurements of a stochastic behavior. The set of correlated measurements follows a non-standard probability distribution and is non-linearly correlated. Also, a non-linear relationship exists between a set of system variables that describes the stochastic behavior and a corresponding set of measurements. The method includes determining, based on the set of measurements, a numerical model of the stochastic behavior. The numerical model comprises a feature space comprising non-correlated features corresponding to the stochastic behavior. The non-correlated features have a dimensionality of M and the set of measurements has a dimensionality of N, M being smaller than N.

Abstract: Deep learning-based systems, methods, and instrumentalities are described herein for MRI reconstruction and/or refinement. An MRI image may be reconstructed based on under-sampled MRI information and a generative model may be trained to refine the reconstructed image, for example, by increasing the sharpness of the MRI image without introducing artifacts into the image. The generative model may be implemented using various types of artificial neural networks including a generative adversarial network. The model may be trained based on an adversarial loss and a pixel-wise image loss, and once trained, the model may be used to improve the quality of a wide range of 2D or 3D MRI images including those of a knee, brain, or heart.

Abstract: Described herein are systems, methods, and instrumentalities associated with using an invertible neural network to complete various medical imaging tasks. Unlike traditional neural networks that may learn to map input data (e.g., a blurry reconstructed MRI image) to ground truth (e.g., a fully-sampled MRI image), the invertible neural network may be trained to learn a mapping from the ground truth to the input data, and may subsequently apply an inverse of the mapping (e.g., at an inference time) to complete a medical imaging task. The medical imaging task may include, for example, MRI image reconstruction (e.g., to increase the sharpness of a reconstructed MRI image), image denoising, image super-resolution, and/or the like.

Abstract: Embodiments include synchronization of automation files among different computing systems. Aspects include receiving a notification that an automation file on a first computing system has been updated, the notification including a first set of data including a timestamp corresponding to the update and comparing the timestamp to a second timestamp, wherein the second timestamp corresponds to the automation file stored on a second computing system. Based on determining a difference between the timestamps, aspects include transmitting a synchronization request to the second computing system. Based on receiving a notification that the second computing system successfully executed the synchronization request, aspects include updating a second set of data to match the first set of data. Based on receiving a notification that the second computing system failed to executed the synchronization request, aspects include notifying a user of a required update to the second computing system.

Abstract: The present disclosure provides a system and method for fetus monitoring. The method may include obtaining ultrasound data relating to a fetus collected by an ultrasound imaging device; generating a 4D image of the fetus based on the ultrasound data; directing a display component of a virtual reality (VR) device to display the 4D image to an operator; detecting motion of the fetus based on the ultrasound data; and directing a haptic component of the VR device to provide haptic feedback with respect to the motion to the operator.

Abstract: Described herein are systems, methods, and instrumentalities associated with tracking groups of small objects in medical images. The tracking may be accomplished by, for each one of a sequence of medical images, determining a plurality of candidate objects captured in the medical image, grouping the plurality of candidate objects into a plurality of groups of candidate objects and dividing the medical image into a plurality of regions that each surrounds a corresponding group of candidate objects. Each of the plurality of regions may be examined to extract respective features associated with each corresponding group of candidate objects. A match between a first group of candidate objects in a first medical image and a second group of candidate objects in a second medical image may be determined based on first features associated with the first group and second features associated with the second group.

Abstract: A long-distance high-voltage cable fault degree detection method. A cable fault positioning curve is obtained by using a frequency-domain reflection method, and a cable fault positioning compensation curve is determined by means of theoretical calculation in combination with the parameters of a frequency-domain incident signal, cable structure parameters, and characteristic parameters of each layer of materials of the field test; furthermore, a cable fault diagnosis curve is determined on the basis of the cable fault positioning curve and the cable fault positioning compensation curve, the severity of the fault is determined by means of the amplitude of a peak point of the cable fault diagnosis curve, and the accuracy of long-distance high-voltage cable fault degree diagnosis is effectively improved.

Abstract: A heat-collecting and energy-efficient pot for gas stove is formed of a main body, an outer casing outside said main body, a top edge made integrally with said main body, a base of said main body smaller than said top edge, a loop molded inwards at the bottom of said outer casing, said loop being in contact with said base, a plurality of through-holes evenly provided on said loop for the flame to pass through, two symmetrical handles on said outer casing, a plurality of smoke exhaust holes on the wall between said two handles at the upper end of said outer casing, and a heat-collecting chamber between said outer casing and said main body; when the heat-collecting and energy-efficient pot for gas stove is used, the extended flame enters the heat-collecting chamber via the through-holes and exchanges heat with the side wall of the main body to facilitate energy collection and the smoke is discharged from the smoke exhaust holes.

Abstract: Provided is a secondary battery, including: an electrode assembly, a packing bag, an electrode lead and an insulation part; the electrode assembly is housed in the packing bag having a sealing part on edge, and the electrode lead is connected to the electrode assembly and passes through the sealing part. The sealing part includes a main body area, a first step area and a first transition area which are located on same side of the electrode lead along width direction, and the main body area, first transition area and first step area are successively arranged along direction approaching the electrode lead; the insulation part is wrapped around the electrode lead, and has a first portion which is located on a side of the electrode lead close to the main body area along width direction and covered by the first step area on both sides in thickness direction.

Abstract: This application provides a positive electrode plate for lithium-ion battery and a lithium-ion battery containing the same. The positive electrode plate may include a current collector, and a capacity layer and a power layer that are specially designed, able to effectively eliminate, in an economical and simple manner, the adverse impact on the battery performance caused by a product resulting from a pre-lithiation material releasing lithium during charge-discharge cycles, thereby significantly improving the first-cycle coulombic efficiency, cycling performance, and service life of batteries.

Abstract: An electrochemical device including a housing, an electrode assembly, and a first bonding piece. The electrode assembly is located in the housing. The first bonding piece bonds the housing and the electrode assembly together. A bonding strength between the first bonding piece and the housing is F1, and a bonding strength between the first bonding piece and the electrode assembly is F2, 5%?F1/F2?70%, and 15 N/m?F1?500 N/m.

Abstract: Disclosed herein include systems, devices, and methods for calling overlapping copy number variants (CNVs) of a gene. The gene can comprise a plurality of regions. The gene can have a plurality of CNVs. Two alleles of the gene of a subject can be determined based on a number of copies of each region of the plurality of regions and all CNVs of the plurality of CNVs of the gene comprising the region.

Abstract: Disclosed are an ultrasonic imaging system and a viscosity quality control method, in which ultrasonic waves for detecting shear waves propagated in a region of interest are transmitted to the region of interest to obtain ultrasonic echo signals, a frequency dispersion distribution diagram is calculated based on the ultrasonic echo signals, a viscosity parameter is calculated based on the frequency dispersion distribution diagram, and the viscosity parameter is performed with quality control based on the frequency dispersion distribution diagram. The present disclosure provides a scheme of quality control on the viscosity parameter.