Abstract: The present disclosure provides a differential resonator and a MEMS sensor. The differential resonator includes a substrate, a first resonator, a second resonator and a coupling mechanism. The first resonator is connected with the second resonator, and the first resonator and the second resonator are movably connected with the substrate. The coupling mechanism includes a first guide beam, a second guide beam, a first coupling beam, a second coupling beam, a first connecting piece and a second connecting piece. The first guide beam and the second guide beam are arranged on two opposite sides of a direction perpendicular to a vibration direction of the first resonator or the second resonator. The first coupling beam is connected with the first guide beam, the second guide beam and the first resonator. The second coupling beam is connected with the first guide beam, the second guide beam and the second resonator.

Abstract: The present disclosure provides a differential resonator and a MEMS sensor. The differential resonator includes a substrate, a first resonator, a second resonator and a coupling mechanism. The first resonator is connected with the second resonator through the coupling mechanism, and the first resonator and the second resonator are connected with the substrate and are able to be displaced relative to the substrate. The coupling mechanism includes a coupling arm, a support shaft, a first connecting piece and a second connecting piece. The coupling arm includes a first force arm, a second force arm and a coupling portion. The support shaft has one end connected with the substrate, and one other end connected with the coupling portion. The first force arm is connected with the first resonator through the first connecting piece, and the second force is connected with the second resonator through the second connecting piece.

Abstract: The disclosure relates to systems and methods for evaluating a blood vessel. The method includes receiving image data of the blood vessel acquired by an image acquisition device, and predicting, by a processor, blood vessel condition parameters of the blood vessel by applying a deep learning model to the acquired image data of the blood vessel. The deep learning model maps a sequence of image patches on the blood vessel to blood vessel condition parameters on the blood vessel, where in the mapping the entire sequence of image patches contribute to the blood vessel condition parameters. The method further includes providing the blood vessel condition parameters of the blood vessel for evaluating the blood vessel.

Abstract: The present application provides a method for updating a map and a mobile robot. The method comprises: acquiring a current map and a corresponding current location data set constructed when a first movement device performs a navigation and movement operation in a physical space, wherein the first movement device performs the navigation and movement operation based on a reference map and a corresponding reference location data set which are corresponding to the physical space and stored in advance; performing a data fusion process on the reference map and the corresponding reference location data set as well as the current map and the corresponding current location data set; taking a map and a corresponding location data set after being data fusion processed as a new reference map and a corresponding new reference location data set in the first movement device. The present application provides a solution for persistence of a map.

Abstract: The disclosure relates to systems and methods for determining blood vessel conditions. The method includes receiving a sequence of image patches along a blood vessel path acquired by an image acquisition device. The method also includes predicting a sequence of blood vessel condition parameters on the blood vessel path by applying a trained deep learning model to the acquired sequence of image patches on the blood vessel path. The deep learning model includes a data flow neural network, a recursive neural network and a conditional random field model connected in series. The method further includes determining the blood vessel condition based on the sequence of blood vessel condition parameters. The disclosed systems and methods improve the calculation of the sequence of blood vessel condition parameters through an end-to-end training model, including improving the calculation speed, reducing manual intervention for feature extraction, increasing accuracy, and the like.

Abstract: Disclosed are a lightweight conductive mortar material, a preparation method therefor and use thereof. The lightweight conductive mortar material includes the following components in parts by weight: 100 parts of cement, 25 parts to 60 parts of a conductive porous lightweight aggregate loaded with a modified agar gel, and 30 parts to 45 parts of water.

Abstract: The present application provides methods and systems for mapping, localization, navigation and control and a mobile robot. Through the technical solution of acquiring a first projected image and second projected image of an entity object when the mobile robot moves to a first position and a second position respectively, building a map or localizing the mobile robot based on angle information of the entity object relative to the mobile robot at the first position and at the second position, the first position and the second position, planning a navigation route based on the built map and localization, and controlling the mobile robot to move along the navigation route, position information of the entity object can be determined precisely, and precision of the built map can be improved. Moreover, movement of the mobile robot can be controlled precisely, and operating precision of the mobile robot and human-computer interaction can be improved.

Abstract: A lidar system based on visible-near infrared-shortwave infrared light bands comprises a light source sub-system, a light receiving sub-system and a signal collecting and processing sub-system, and adopts a laser light source having a supercontinuum spectrum laser comprising the three bands of visible, near infrared and shortwave infrared light. The lidar system conveniently and effectively achieves hyperspectral measurement of three bands of visible, near-infrared, and shortwave infrared lights without needing to replace the laser light source, increasing the capability of detecting target spectrum information and application range, providing more accurate measurement results and post-processing algorithms, and strengthening the capability of simultaneously detecting visible-near infrared-shortwave infrared ligh bands of a lidar system.

Abstract: The present disclosure provides a prediction method for a healthy radius of a blood vessel path, a prediction method for candidate stenosis of a blood vessel path, and a blood vessel stenosis degree prediction device. The prediction method for a healthy radius includes: obtaining a blood vessel radius of the blood vessel path; by a processor, detecting a radius peak of the blood vessel radius of the blood vessel path; and by the processor, predicting the healthy radius of the blood vessel path by performing a regression on the radius peak of the blood vessel radius. The blood vessel stenosis degree prediction device can, in certain embodiments, automatically determine the candidate stenosis and detect the degree of stenosis for the candidate stenosis range, significantly reduce the computation load, improve the detection efficiency and effectively avoid missed detection.

Abstract: The present disclosure relates to a method, storage medium, and system for analyzing an image sequence of a periodic physiological activity. In one implementation, the method includes receiving the image sequence acquired by an imaging device, the image sequence having a plurality of frames, and identifying a feature point in a first frame. The method further includes determining motion vectors for the feature point in the frames of the image sequence. Each motion vector for the feature point is determined based on respective locations of corresponding feature points in frames adjacent to the first frame. The method also includes determining a motion magnitude profile based on the determined motion vectors and determining a phase of each frame in the image sequence based on the motion magnitude profile.

Abstract: Method, system, device and medium for determining a blood flow velocity in a vessel are provided. An example method includes receiving a 3D model of the vessel, which is reconstructed based on X-ray angiography images of the vessel. The method further includes specifying a segment of the 3D model by a start landmark and a termination landmark. Moreover, the method includes determining the blood flow velocity based on length of the segment and perfusion time for the segment by normalizing the blood flow velocity to correspond to a cardiac cycle. The method has a better accuracy in calculating blood flow velocity, and requires no additional modalities other than the original X-ray angiogram sequences used to visualize coronary arteries.

Abstract: The present disclosure relates to a device, a system, and a computer-readable medium for calculating vessel flow parameters based on angiography. In one implementation, the device includes a processor and a memory storing computer-executable instructions that, when executed by the processor, cause the processor to perform the following operations: selecting a plurality of template frames from the angiographic images to generate a 3D model for a vessel; determining a start frame and an end frame in the plurality of angiographic images showing a contrast filling process; determining corresponding locations of front ends of the contrast in the start frame and the end frame in the 3D model of the vessel; calculating a vessel volume between the determined locations of the front ends in the 3D model; and determining an average blood flow rate based on the calculated volume, and a time interval between the start frame and the end frame.

Abstract: The present disclosure is directed to a method and device for generating anatomical labels for a physiological tree structure. The method may include receiving a 3D model and a 3D skeleton line of the physiological tree structure. The 3D model is restructured based on medical image data of the physiological tree structure acquired by an imaging device. The method further includes selecting at least one level from extracting geometrical features from a pool of selectable levels. The method also includes extracting, by a processor, geometrical features from the 3D model of the physiological tree structure along the 3D skeleton line at the selected at least one level. The method also includes generating, by the processor, anatomical labels for the physiological tree structure using a trained learning network based on the extracted geometrical features.

Abstract: There is provided a method and device for data replication. The method comprises: obtaining, in a network interface card, data segments by segmenting input first data; determining, in the network interface card, fingerprints corresponding to the data segments; and comparing, in a central processing unit, the fingerprints of the data segments with existing fingerprints corresponding to processed data segments, and determining, based on a result of the comparing, whether to de-duplicate the data segments corresponding to the fingerprints, to perform the data replication.

Abstract: The present application provides a navigation method, a navigation system, a movement control system and a mobile robot. The navigation method comprises the following steps: identifying a target object corresponding to a preset object type label from images captured by the image acquisition device; determining the relative position between the target and the mobile robot based on at least one image which contains the identified target and is captured by the image acquisition device; and generating a map marked with the object type label through marking corresponding preset object type label on a preset map based on the relative position, wherein the map is used for navigating the mobile robot. In the present application, mobile robot can move to the destination position after the destination position contained in the user instruction being identified based on the object type labels on the map, so as to improve human-computer interactivity.

Abstract: The present application provides a navigation method, a navigation system, a movement control system and a mobile robot. The navigation method comprises the following steps: identifying a target object corresponding to a preset object type label from images captured by the image acquisition device; determining the relative position between the target and the mobile robot based on at least one image which contains the identified target and is captured by the image acquisition device; and generating a map marked with the object type label through marking corresponding preset object type label on a preset map based on the relative position, wherein the map is used for navigating the mobile robot. In the present application, mobile robot can move to the destination position after the destination position contained in the user instruction being identified based on the object type labels on the map, so as to improve human-computer interactivity.

Abstract: The present disclosure relates to a method, storage medium, and system for analyzing an image sequence of a periodic physiological activity. In one implementation, the method includes receiving the image sequence acquired by an imaging device, the image sequence having a plurality of frames and determining local motions for pixels in each frame of the image sequence. The local motion for a pixel may be determined using corresponding pixels in frames adjacent to the frame to which the pixel belongs. The method further includes determining principal motions for the plurality of frames based on the local motions; determining a motion magnitude profile based on the principal motions; and determining the phase of each frame in the image sequence based on the motion magnitude profile.

Abstract: The disclosure relates to systems and methods for determining blood vessel conditions. The method includes receiving a sequence of image patches along a blood vessel path acquired by an image acquisition device. The method also includes predicting a sequence of blood vessel condition parameters on the blood vessel path by applying a trained deep learning model to the acquired sequence of image patches on the blood vessel path. The deep learning model includes a data flow neural network, a recursive neural network and a conditional random field model connected in series. The method further includes determining the blood vessel condition based on the sequence of blood vessel condition parameters. The disclosed systems and methods improve the calculation of the sequence of blood vessel condition parameters through an end-to-end training model, including improving the calculation speed, reducing manual intervention for feature extraction, increasing accuracy, and the like.

Abstract: There is provided a method and device for data replication. The method comprises: obtaining, in a network interface card, data segments by segmenting input first data; determining, in the network interface card, fingerprints corresponding to the data segments; and comparing, in a central processing unit, the fingerprints of the data segments with existing fingerprints corresponding to processed data segments, and determining, based on a result of the comparing, whether to de-duplicate the data segments corresponding to the fingerprints, to perform the data replication.

Abstract: Methods and systems for segmenting images having sparsely distributed objects are disclosed. A method may include: predicting object potential areas in the image using a preliminary fully convolutional neural network; segmenting a plurality of sub-images corresponding to the object potential areas in the image using a refinement fully convolutional neural network, wherein the refinement fully convolutional neural network is trained to segment images on a higher resolution compared to a lower resolution utilized by the preliminary fully convolutional neural network; and combining the segmented sub-images to generate a final segmented image.