9 results about "Reconstruction procedure" patented technology

A method of video processing is provided. The method may include inputting attribute data and a sparse-depth map associated with an image area into a sparse-depth completion network. The method may include generating a refined dense-depth map based on the attribute data and the sparse-depth map using the sparse-depth completion network. The method may include performing a three-dimensional (3D) reconstruction procedure based on the refined dense-depth map to generate a point cloud of the image area. The method may include performing a triangular-meshing procedure to generate a mesh model based on the point cloud of the image area. The method may include performing a texture-mapping procedure based on the mesh model and the attribute data to generate a textured mesh of the image area. The method may include performing a vertex-normal procedure based on the textured mesh to generate a 3D representation of the image area.

A method for determining a convolution kernel for an iterative statistical algorithm based on a continuous-to-continuous data model. The method is used for image reconstruction from radiation measurements obtained in emission tomography, specifically in a Time-of-Flight Positron Emission Tomography (TOF PET) scanner. The presented method is a non-list-mode solution that reduces the computational complexity of the reconstruction problem, improves the resolution of reconstructed images, reduces the radiation dose absorbed by patients during TOF PET examinations, and / or shortens the measurement acquisition time without significantly compromising the quality of the diagnostic images. Notably, the quality of the functional images remains at the same level. These improvements are achieved by designing the convolution kernel to account for the statistical properties of the measurement signals registered during the TOF PET scanner's acquisition process.

A user equipment (UE) may implement a method for managing a lower layer mobility protocol procedure. The method includes receiving, via a serving cell, a lower layer mobility configuration and a cell identifier from a radio access network (RAN) at the UE; receiving, via the serving cell, a lower layer mobility command from the RAN at the UE that activates a lower layer mobility configuration; in a first instance, a reconstruction procedure is performed based on a cell identifier; and in a second instance, avoiding performing the reconstruction procedure based on the cell identifier.

A method for a communication device to handle a reestablishment procedure includes initiating the reestablishment procedure, selecting a target cell according to a cell selection procedure, triggering a on-demand system information block 1 procedure to the target cell in response to at least one trigger on-demand system information block 1 procedure condition being satisfied according to a stored wake-up signal configuration, determining whether the target cell is a cell that the communication device can camp on according to a system information block 1 from the target cell, and transmitting a reestablishment request message to the target cell in response to the target cell being the cell that the communication device can camp on.

Data storage devices configured to exploit generative-adversarial-networks (GANs). The GANs include super-resolution GANs (SRGANs). In some examples, a GAN-based reconstruction procedure is implemented within a data storage controller to replace or supplement an error correction coding (ECC) decoding procedure. In other examples, soft bit information is exploited using GANs during decoding. A dissimilarity matrix may be generated to represent differences between an initial image and a GAN-reconstructed image, with matrix values mapped into low-density parity check (LDPC) codewords to facilitate LDPC decoding of data. In still other examples, confidence information obtained from a GAN is incorporated into image pixels. In some examples, GAN reconstruction of data is limited to modifying valley bits. Multiple GANs may be used in parallel with their outcome aggregated.

The present invention relates to a distributed reconstruction resource management method based on cloud devices. The distributed reconstruction resource management method is applied to a distributed reconstruction system for medical image reconstruction in a medical imaging device. A plurality of nodes implementing a data reconstruction program are configured in the distributed reconstruction system. All nodes are located in a broadcast domain of the distributed reconstruction system and periodically broadcast available resource information in a broadcast manner. The method includes: the first node and each node in the broadcast domain update their respective available resource information in real time; if the first node in the broadcast domain receives a local reconstruction task, then according to the resource allocation strategy, the available resource information of the current first node, and the available resource information of other nodes in the broadcast domain, data segmentation of the local reconstruction task is performed and threads for the segmented data are created to distributively complete the local reconstruction task. The above method improves the data processing speed and solves the problem of uneven computing resources.

The invention discloses an automatic three-dimensional reconstruction device, method and system, the device comprises an aluminum profile frame, a rotating platform, an LED lamp, a controller and a plurality of industrial cameras are arranged in the aluminum profile frame, and the plurality of industrial cameras are adjustably arranged on the aluminum profile frame and used for shooting a target object at multiple angles; the rotating platform is located on the bottom face of the aluminum profile frame and used for bearing and rotating a target object. The LED lamp is fixed to the bottom of the aluminum profile frame around the rotating platform. Three of the side faces of the periphery of the aluminum profile frame are sealed by sealing plates, one of the side faces of the periphery of the aluminum profile frame is sealed by a metal plate door, a computer with a three-dimensional reconstruction program is embedded in one sealing plate, the controller is electrically connected with the rotating platform and the industrial camera set through data lines, and the computer is connected and communicated with the controller through a network cable. The device is simple in structure, convenient to operate, low in cost and suitable for three-dimensional reconstruction of various objects, and has wide application prospects and high flexibility.

Disclosed are systems and methods for a computerized framework that provides novel mechanisms for the automatic identification of existing tunnels and hardware, which can be used for compiling of a preoperative and / or intraoperative plan for an anterior cruciate ligament (ACL) revision procedure. The operative plan, among other benefits, automatically avails surgeons with capabilities to locate the tunnels physically, and guides them in their revision ACL reconstruction procedure. According to some embodiments, the disclosed framework can generate synthetic ACL reconstruction CT images from CT images of patients without previous primary ACL reconstruction. The framework can generate realistic ACL reconstruction CTs, which can be used as input for training machine learning or deep learning models. Moreover, this can improve the accuracy, robustness and generalization capacity (e.g., identification of tunnels and hardware in MRIs and CTs) of the machine learning and deep learning based models for ACL tunnel segmentation.