Abstract: A deep learning (DL) network corrects/performs sinogram completion in computed tomography (CT) images based on complementary high- and low-kV projection data generated from a sparse (or fast) kilo-voltage (kV)-switching CT scan. The DL network is trained using inputs and targets, which respectively generated with and without kV switching. Another DL network can be trained to correct sinogram-completion errors in the projection data after a basis/material decomposition. A third DL network can be trained to correct sinogram-completion errors in reconstructed images based on the kV-switching projection data. Performance of the DL network can be improved by dividing a 3D convolutional neural network (CNN) into two steps performed by respective 2D CNNs. Further, the projection data and DLL can be divided into high- and low-frequency components to improve performance.

Abstract: An anastomosis clamp (1) and a delivery system thereof, where the anastomosis clamp (1) includes inner lancets (102, 602), round corners (103, 603), and outer rings (101, 601) that are sequentially connected; the delivery system may be used in cooperation with the anastomosis clamp (1); and the delivery system includes a distal end (2), a middle flexible sheath (3), and a handle (4).

Abstract: An image display method, a device, and a medium. The image display method includes displaying an emoji recommendation panel in a chat interface once an input text displayed in the chat interface triggers an emoji recommendation event, in which a target entry icon is displayed in the emoji recommendation panel, and the target entry icon is used to trigger display of a custom target emoji image; stopping displaying the emoji recommendation panel in response to detecting a first trigger operation on the target entry icon; and displaying, in the chat interface, a target emoji presentation panel corresponding to the target entry icon. A first preview image is displayed in the target emoji presentation panel, and the first preview image is a preview image of the target emoji image.

Abstract: A medical image processing apparatus according to an embodiment comprises a memory and processing circuitry. The memory is configured to store a plurality of neural networks corresponding to a plurality of imaging target sites, respectively, the neural networks each including an input layer, an output layer, and an intermediate layer between the input layer and the output layer, and each generated through learning processing with multiple data sets acquired for the corresponding imaging target site. The processing circuitry is configured to process first data into second data using, among the neural networks, the neural network corresponding to the imaging target site for the first data, wherein the first data is input to the input layer and the second data is output from the output layer.

Abstract: An information processing method processes an x-ray image including the steps of: obtaining first lower-radiation dose three-dimensional image data during a first scan of a patient; and detecting, using a trained neural network, a presence of an artifact (e.g., a metal artifact) in the first lower-radiation dose three-dimensional image data. An information processing apparatus includes processing circuitry for performing the detection method, and computer instructions stored in a non-transitory computer readable storage medium cause a computer processor to performing the detection method.

Abstract: Methods and apparatuses for retaining or treating a dental arch to apply a lateral expansion force to a lower jaw while permitting the extrusion of one or more teeth may include the use of a maxillary dental appliance device and/or a mandibular dental appliance device including projection regions extending from the occlusal surfaces of the device to apply a laterally outward expansion force.

Abstract: Devices, systems, and methods obtain scan data that were generated by scanning a scanned region, wherein the scan data include groups of scan data that were captured at respective angles; generate partial reconstructions of at least a part of the scanned region, wherein each partial reconstruction of the partial reconstructions is generated based on a respective one or more groups of the groups of scan data, and wherein a collective scanning range of the respective one or more groups is less than the angular scanning range; input the partial reconstructions into a machine-learning model, which generates one or more motion-compensated reconstructions of the at least part of the scanned region based on the partial reconstructions; calculate a respective edge entropy of each of the one or more motion-compensated reconstructions of the at least part of the scanned region; and adjust the machine-learning model based on the respective edge entropies.

Abstract: A device assembly system includes a control apparatus, a mobile apparatus, a lifting apparatus, and a plug in/out apparatus. The control apparatus is configured to control, based on an operation and maintenance instruction, the mobile apparatus, the lifting apparatus, and the plug in/out apparatus to complete an operation of the operation and maintenance instruction. The mobile apparatus is configured to move the device assembly system to a first location, and the first location identifies a rack in which a device is assembled. The lifting apparatus is configured to move the plug in/out apparatus to a target location in a first direction. The plug in/out apparatus is configured to place the device to be assembled at the target location, or obtain the device from the target location.

Abstract: A node interconnection apparatus includes a computing node, a resource control node, and a device interconnection interface connecting the computing node and the resource control node. Each of the computing node and the resource control node includes a processing unit and a storage unit, and the resource control node further includes a resource interface for connecting with a network storage device. The resource control node manages a storage resource of the network storage device, and when the computing node needs to start up, the resource control node obtains operating system startup information from the network storage device and provides the operating system startup information to the computing node. The computing node can start up without the need for storing startup information locally.

Abstract: A method of processing information acquired by imaging performed by a medical image diagnostic apparatus, the method including but not limited to at least one of (A) acquiring a training image volume including at least one three-dimensional object having an embedded three-dimensional feature having a first cross-sectional area in a first three-dimensional plane; selecting a second cross-sectional area in a second three-dimensional plane containing the embedded three-dimensional feature, wherein the second cross-sectional area is larger than the first cross-sectional area; and training an untrained neural network with an image of the second cross-sectional area generated from the training image volume; and (B) acquiring a first set of training data; determining a first distribution of tissue density information from the first set of training data; generating from the first set of training data a second set of training data by performing at least one of a tissue-density shifting process and a tissue-density sca

Abstract: Aan integrating system for evaluating and managing cultivation and targeted adoption includes a cultivating adoption evaluating and managing system, a profit returning module, and a contract terminating, rescinding and assigning module; the cultivating adoption evaluating and managing system includes, an adoption confirming system, a cultivating data and harvesting database, a contract database; the adoption confirming system includes, an adoption reporting evaluating procedure module, a contract concluding procedure module; the adoption reporting evaluating procedure module is connected to the adoption buying proposing module; with the system, an automatic solution is provided to the adoption contract, the procedure of the contract drafting to the contract signing can be processed online for establishing the filing operation; the purchasing price in the market and the profit statuses of both parties can be obtained in any desired time for the investing party and the cultivating party.

Abstract: A water quality monitoring and maintaining system includes a water quality monitoring instrument, a process system and a water quality treating module. The water quality monitoring instrument is used for collecting a plurality of water quality data of a monitored water in a monitored environment. The process system is used for processing an error correcting operation and a storing operation for the plurality of water quality data collected by the water quality monitoring instrument, thereby establishing a water quality data model. The water quality treating module is used for adjusting the plurality of water quality data of the monitored environment according to the water quality data model.

Abstract: Provided are a video sharing method and apparatus, an electronic device, and a storage medium. The method comprises: determining a designated user, and triggering a video filming instruction for the designated user; displaying a filming interface in response to receipt of the video filming instruction; initiating video filming in response to receipt of an initiate instruction, and in response to determining that voice information is received, adding the voice information in the form of a subtitle to the filming interface to obtain a filmed video; and sharing the filmed video with the designated user through a conversation message.

Abstract: A method, apparatus, and computer-readable storage medium for controlling exposure/irradiation during a main three-dimensional X-ray imaging scan using at least one spatially-distributed characteristic of a pre-scan/scout scan preceding the main scan. The at least one spatially-distributed characteristic includes (1) a spatially-distributed noise characteristic of the pre-scan and/or (2) a spatially-distributed identification of exposure-sensitive tissue types. The at least one spatially-distributed characteristic can be calculated from images reconstructed from sinogram/projection data and/or from sinogram/projection directly using a neural network.

Abstract: A one-way valve is provided. The one-way valve includes a housing and a valve core assembly. The housing is provided with a valve port. A ratio of a wall thickness of the housing to an outer diameter of the housing is in a range of 0.08 and 0.12. The valve core assembly is movably disposed in the housing and configured to open or seal the valve port.

Abstract: An electrochemical cell includes a cathode including a cathode active material; an anode including silicon, conductive carbon, lithium metal, sodium metal, magnesium metal, sulfur, or a combination of any two or more thereof; a separator; and an electrolyte including a lithium sulfonylimide salt, an asymmetric fluorinated glycol ether, and optionally an electrolyte additive, an aprotic gel polymer, or a mixture thereof.

Abstract: A multi-bit resolution sub-pipeline structure for measuring a jump magnitude of a transmission curve, comprising: a sub-analog-to-digital converter having n-bit resolution configured to quantize input analog voltage signals and output digital voltage signals; a sub-digital-to-analog converter having n-bit resolution configured to convert the digital voltage signals output by the sub-analog-to-digital converter into corresponding analog voltage signals; a decoder having n-bit resolution configured to decode an n-bit binary input signal; and a switched-capacitor amplification unit configured to, when in a normal mode, perform sampling and residue amplification on the input analog voltage signals; and when in a test mode, measure the jump magnitude of the transmission curve corresponding to each decision level. Magnitude measurement of a transmission curve is performed within 2n clock periods, th and a measurement result is sent to a back-end digital domain of the A/D converter for correction.

Abstract: Devices, systems, and methods receive scan data that were generated by scanning a region of a subject with a computed tomography apparatus; generate multiple partial angle reconstruction (PAR) images based on the scan data; obtain corresponding characteristics of the multiple PAR images; perform correspondence mapping on the multiple PAR images based on the obtained corresponding characteristics and on the multiple PAR images, wherein the correspondence mapping generates correspondence-mapping data; and generate a motion-corrected reconstruction image based on the correspondence-mapping data and on one or both of the scan data and the PAR images.

Abstract: Apparatuses and methods for customized retainers to prevent relapse. In particular, described herein are customized retainers, and methods and apparatuses for making customized retainers that specifically reenforce and prevent movement of one or more teeth having a higher likelihood of relapse following completion of an orthodontic treatment plan.