1058 results about "Tensor" patented technology

A tensor for use with a surgical navigation system is provided. The tensor comprises a first bone engaging member engageable with a first bone and a second bone engaging member engageable with a second bone. A force-applying mechanism is configured to forcibly move the first and second bone engaging members relative to one another and a sensor detects the value of the force applied by the force-applying mechanism. A transmitter communicates a parameter associated with the tensor to the surgical navigation system.

A system for tracking a moving magnetic target uses a magnetic anomaly sensing system to continually determine magnetic gradient tensors associated with the target and converts the magnetic gradient tensors to gradient contraction scalars. A processor uses the magnetic gradient tensors and gradient contraction scalars to determine a minimum of bearing and range to the target. A velocity of the target is determined using the determined bearing and range at two points in time as the target is moving. To continually track with the moving target, the processor determines adjustments in elevation and azimuth using the magnetic gradient tensors and gradient contraction scalars along with bearing, range and determined velocities of the target. The processor can include a routine that determines range while accounting for asphericity errors introduced by the aspherical nature of constant magnetic gradient contours associated with the target.

The present invention provides elastic constant and visco elastic constant measurement apparatus etc. for measuring in the ROI in living tissues elastic constants such as shear modulus, Poisson's ratio, Lame constants, etc., visco elastic constants such as visco shear modulus, visco Poisson's ratio, visco Lame constants, etc. and density even if there exist another mechanical sources and uncontrollable mechanical sources in the object. The elastic constant and visco elastic constant measurement apparatus is equipped with means of data storing 2 (storage of deformation data measured in the ROI 7 etc.) and means of calculating elastic and visco elastic constants 1 (calculator of shear modulus etc. at arbitrary point in the ROI from measured strain tensor data etc.), the means of calculating elastic and visco elastic constants numerically determines elastic constants etc. from the first order partial differential equations relating elastic constants etc. and strain tensor etc.

A method upsamples an image using a non-linear fully connected neural network to produce only global details of an upsampled image and interpolates the image to produce a smooth upsampled image. The method concatenates the global details and the smooth upsampled image into a tensor and applies a sequence of nonlinear convolutions to the tensor using a convolutional neural network to produce the upsampled image.

An image processing system detects a moving person or other object of interest. The system generates a thresholded difference image by processing a video signal or other type of image signal received from a camera. The difference image is then segmented into regions bounded by vertical lines passing through the image, and silhouette candidates are identified in one or more of the regions. Tensor voting is used to determine saliency values and corresponding tangents for each of the silhouette candidates, and the resulting values and tangents are used to detect the object of interest. In an embodiment in which the object of interest is a moving person, a neck position of the moving person may be detected by analyzing a sum of x-components of tangents along a corresponding silhouette. The detected neck position may then be utilized to determine a head position and a head size for the moving person.

A system and method to determine earth formation properties by positioning a logging tool within a wellbore in the earth formation, the logging tool having a tool rotation axis and a first, a second, and a third tilted transmitter coil, and a tilted receiver coil; rotating the logging tool about the tool rotation axis; energizing each transmitter coil; measuring a coupling signal between each transmitter coil and the receiver coil for a plurality of angles of rotation; determining a coupling tensor; and determining the earth formation properties using the coupling tensor.

A magnetic anomaly sensing system uses triaxial magnetometer (TM) sensors arranged in a three-dimensional array. A processor coupled to the TM sensors generates partial gradient contraction data, and complete gradient tensor data and corresponding complete gradient contraction data. The generated data can be used to align the three-dimensional array with a magnetic target. Once the three-dimensional array is aligned with the magnetic target, the generated data can be used to uniquely determine (i) distance to the magnetic target, (ii) position of the magnetic target relative to the three-dimensional array, and (iii) the magnetic dipole moment of the magnetic target.

A computer system and method of automatically generating a Local Grid Refinement (LGR) gridded model of a gas reservoir. A geologic file includes information identifying the locations of one or more wells according to root grid cells within a volume of the earth to be modeled. User inputs specify the number of hydraulic fractures from each well, and such parameters as the fracture length, etc. User inputs also specify the number of “splits” of the root grid cells containing hydraulic fractures; those root grid cells are then split into finer resolution grid cells of increasing width within the root grid cells containing the fractures. For horizontal wells, user inputs indicate the number of splits of root grid cells containing the lateral portions of the wellbore. Non-orthogonal and complex fractures are processed by a“nested” LGR approach. Geologic properties are assigned to each grid cell, with a tensorial adjustment included for non-orthogonal fractures, and the resulting model is available for simulation.

Disclosed are methods and related devices for use with subjects with cerebral palsy or periventricular leukomalacia. In preferred embodiments, diffusion tensor imaging (DTI) is used to identify neural areas and transcranial magnetic stimulation (TMS) is used to stimulate neural pathways.

The present invention determines the adopting ratio (weight coefficient) between the high image quality processing using the tensor projection method and the high image quality processing using another method according to the degree of deviation of the input condition of the input image, and combines these processes as appropriate. This allows a satisfactory reconstruction image to be acquired even in a case of deviation from the input condition, and avoids deterioration of the high quality image due to deterioration of the reconstruction image by the projective operation.

A 5D printer, which additively manufactures an object, includes an extruder that can move linearly along three orthogonal axes and rotationally around at least one of the axes with respect to the object while depositing a material. A gantry is movable along X, Y and Z axes, and a trunnion table movable about A and B axes is mounted on the gantry. A platen is mounted on the trunnion table, and the extruder deposits the material on the platen while moving the gantry and trunnion table. A model of the object is analyzed to produce a stress tensor for the object, and the depositing is according, to the stress tensor.

A gradiometer is disclosed which has a pair of sensor bars 41, 43 supported in housings 45, 47. Transducers 71 are located adjacent the bars 41, 43 to detect movement of the bars in response to the gravity gradient tensor. At least one of the transducers 71 comprises a first coil 510 and a second coil 516 arranged in parallel and a switch 362 for proportioning current between the coils 510 and 516 so as to create a virtual coil at a position D between the coils 510 and 516.

The method for vascular elastography comprises: i) obtaining a sequence of radio-frequency (RF) images including pre-tissue-motion and post-tissue-motion images in digital form of a vessel delimited by a vascular wall; the pre-tissue-motion and post-tissue-motion images being representative of first and second time-delayed configuration, of the whole vessel; ii) partitioning both the pre-tissue-motion and post-tissue-motion images within the vascular wall into corresponding data windows; approximating a trajectory between the pre- and post-tissue-motion for corresponding data windows; and using the trajectory for each data window to compute the full strain tensor in each data window, which allow determining the Von Mises coefficient. The method can be adapted for non-invasive vascular elastography (NIVE), for non-invasive vascular micro-elastography (MicroNIVE) on small vessels, and for endovascular elastography (EVE).

The present invention provides a gravity gradiometer for measuring components of the gravity gradient tensor. The gravity gradiometer comprises at least one sensor mass for movement in response to a gravity gradient and a pivotal coupling enabling the movement of the at least one sensor mass about an axis. Further, the gravity gradiometer comprises a constant charge capacitor that is arranged so that the movement of the at least one sensor mass generates a change in a voltage across the constant charge capacitor.

The invention discloses a multimodal brain network feature fusion method based on multi-task learning, and the multimodal brain network feature fusion method based on the multi-task learning includes the steps of preprocessing the obtained functional magnetic resonance imaging (fMRI) images and diffusion tensor imaging (DTI) images, registrating the preprocessed fMRI image to the standard AAL template, carrying out a fiber tracking for preprocessed DTI images, calculating fiber anisotropy (FA) value, and constructing structure connection matrix through the AAL template. Clustering coefficient of each brain area in a function connection matrix and the structure connection matrix is calculated to be regarded as function features and structure features. As two different tasks, the function features and the structure features assess an optimal feature set by solving the problem of multi-task learning optimization. The method uses information with multiple modalities complementing each other to learn simultaneously and to classify, improves the classification accuracy, solves the problems that a single task feature does not consider the correlation between features, and the fact that only one modality feature is used for pattern classification can bring to insufficient amount of information.