35 results about "Single voxel" patented technology

A method and apparatus are provided for transforming an irregular, unorganized cloud of data points (100) into a volumetric data or “voxel” set (120). Point cloud (100) is represented in a 3D cartesian coordinate system having an x-axis, a y-axis and a z-axis. Voxel set (120) is represented in an alternate 3D cartesian coordinate system having an x′-axis, a y′-axis, and a z′-axis. Each point P(x, y, z) in the point cloud (100) and its associated set of attributes, such as intensity or color, normals, density and/or layer data, are mapped to a voxel V(x′, y′, z′) in the voxel set (120). Given that the point cloud has a high magnitude of points, multiple points from the point cloud may be mapped to a single voxel. When two or more points are mapped to the same voxel, the disparate attribute sets of the mapped points are combined so that each voxel in the voxel set is associated with only one set of attributes.

The present invention relates to a phantom for evaluating performance of an ultra high field Magnetic Resonance Imaging (MRI) apparatus. Specifically, the present invention relates to a multi-purpose phantom which can grasp a degree of diagnostic capability of an MRI apparatus using a comprehensive result of imaging conditions and variables and simultaneously analyze and evaluate performance of Magnetic Resonance Imaging (MRI), performance of Magnetic Resonance Spectroscopy (MRS) and metabolic components of a human body within a predetermined range of error and limit. The phantom for evaluating performance of an ultra high field Magnetic Resonance Imaging (MRI) apparatus may include: an outer container opened and closed using a stopper and formed with an insertion hole for injecting components of a liver metabolite and a lipid; an inner container for quantitatively evaluating the components of the liver metabolite and the lipid, acquiring an MRI image using a spin echo sequence, and acquiring a relaxation time through spectroscopy using a single voxel technique of the MRI apparatus; a geometric accuracy evaluation apparatus installed at an upper end portion of the outer container in a shape of three-dimensional lattice type frame; slice position evaluation apparatuses of different shapes, capable of measuring a position of a slice in a middle of the outer container; a contrast resolution evaluation apparatus configured of a plurality of holes in the middle of the outer container to perform evaluation at regular intervals; a spatial resolution evaluation apparatus installed inside the outer container, in which a plurality of hole bundles configured of space evaluation holes is formed to have a same diameter and arranged in an evaluation frame in parallel at regular intervals to have holes of different diameters in each of the hole bundles; a slice thickness evaluation apparatus installed at a height a same as that of the spatial resolution evaluation apparatus and attached to the outer container to be formed in a shape of a stair; and a brain metabolite evaluation apparatus configured of a plurality of layers at a lower portion of the outer container.

The present invention is directed to a system and method of resealing spectroscopic data acquired with phased-array or surface coils to absolute “local” units and, hence, preserves the industry-desirable quantitative approach to single voxel MRS. An MRS signal is acquired from water using a body coil and is used as a reference signal to scale MR spectroscopic data acquired with a plurality of RF receive coils, i.e. phased-array or surface coils. In the resealing process, the amplitude of water in the MRS data will be set to match the amplitude of the water reference signal.

The invention provides a brain functional region positioning method based on local smoothing regressions. The brain functional region positioning method based on the local smoothing regressions comprises the following steps of pretreating data and deciding a design matrix X; taking a voxel vi as the center of a sphere and r as a semidiameter for the establishment of a spherical selected region and extracting the time sequence of all the voxels in the spherical selected region; according to the time sequence of all the voxels in the spherical selected region and the design matrix, forming an objective function and optimizing the objective function; calculating a condition specificity effect of the voxel vi; turning to the next voxel vi+1 and repeating steps from S2 to S4 till the execution of the steps on each voxel of a whole brain; and setting a threshold value for a whole brain perception mapping so as to obtain a brain functional region positioning map relevant with stimulus conditions. All the generalized linear models based on the regressions of the single voxels and based on Gaussian smoothing filtering can be regarded as special cases of the invention; the brain functional region positioning method based on the local smoothing regressions can be integrated into a framework used for a searchlight method; after the obtainment of regression coefficients, mahalanobis distances between various predictor coefficients are calculated; and through the adjustment on hyper-parameters alpha and beta, smoothing effects of various degrees are obtained.

The invention discloses a 3D printing slicing method for an implicit expression medical model, and relates to computer graphics and 3D printing. The method comprises the following steps of searching the volume data to obtain solid volume elements meeting conditions; dividing a single voxel into a series of sub eight partitions, and performing recursive operation; integrating all the eight partitions to project the specific height, and obtaining three-dimensional linear interpolation of each point at the corresponding layer height; matching each square vertex with a standard stepping square mode, and storing sampling points; acquiring a plurality of adjacent sampling points and retracting, and calculating a retracting distance; obtaining all sampling points and adjacent points of the sampling points, and constructing a complete inner layer contour; checking whether the current sampling point has an error; removing known self-intersection points, and optimizing the shape of an inner-layer contour; retracting inwards to increase a virtual layer; constructing a parallel scanning line field, and calculating intersection point coordinates of the scanning line field and the virtual layer;adopting labyrinth filling for alternate wiring to achieve internal filling . The method reduces consumables, time and space expenses..

A computed tomography method for determining a volumetric representation of a sample comprises using reconstructed volume data of the sample from x-ray projections of the sample taken by an x-ray system, computing a set of artificial projections of said sample by a forward projection from said reconstructed volume data , and determining, essentially from process data of said reconstruction including said reconstructed volume data and/or said x-ray projections, individual confidence measures for single voxels of said volume data based on calculating, for each of said measured x-ray projections, the difference between the contribution of this measured x-ray projection to the voxel under inspection and the contribution from a corresponding artificial projection to the voxel under inspection.

The invention provides a method for realizing a pure absorption line type two-dimensional magnetic resonance single-voxel localized J decomposition spectrum. ZS modules are added at different positions to form an N sequence and an R sequence, the experimental result of the R sequence symmetrically flipped along an indirect dimension F1 = 0 Hz, and superimposing the symmetrically flipped experimental result of the R sequence and the result of the N sequence to obtain the pure absorption line type single-voxel two-dimensional localized J decomposition spectrum. The N sequence is formed through adding the ZS module after the first 90 DEG localized pulse, the R sequence is formed through adding the ZS module after the last 180 DEG localized pulse, the delay times at both sides of the last 180DEG of each of the sequences are uniform and are t1/2, and indirect dimensional F1 evolution is performed. The ZS module consists of a selective 180 DEG soft pulse, a Z-directional gradient magnetic field and a symmetric spoiled gradient, so the selective 180 DEG soft pulse realizes the evolution refocusing of different nuclei at different spatial positions, and the coherence order of the resonance nuclei transfers; and the ZS modules of the N sequence and the R sequence have different positions, so final two-dimensional signal composition modes are different.

The invention discloses a laser radar 3D point cloud ground detection method. The problem that an expected ground filtering effect is difficult to achieve in the prior art is solved. The method comprises the following steps: collecting point cloud data of roads around a vehicle; cutting the point cloud data, and determining a region-of-interest range; initializing 3D voxel grids, and obtaining coordinates of each 3D voxel grid in a laser radar coordinate system; traversing all the point cloud data, filling 3D voxel grids corresponding to the coordinates with the point cloud data, and recording indexes; carrying out plane fitting on the point cloud data in each 3D voxel grid, traversing all the point cloud data, calculating the distance from the point cloud data to a plane, comparing a distance threshold value with a height threshold value, and judging whether the corresponding point cloud data is a ground point or not; and sending all point cloud data which are judged to be non-ground points into a clustering algorithm to realize detection of obstacle target points. And for a scene of a single voxel, ground points are identified and distinguished, and an expected ground filtering effect is achieved.

The invention relates to a skeleton line extraction method suitable for a complex multi-cavity three-dimensional model, and the method comprises the steps: taking a voxel model as input, firstly, based on a topological refinement algorithm, gradually deleting simple voxel points which do not affect a local connection relation through parallel iteration refinement, and obtaining a basic skeleton line with a single pixel width; secondly, an undirected graph model is constructed for the basic skeleton line according to the distance relation, and edges, located outside the model or at outlier positions, in a graph are removed through pretreatment; and then, iteratively detecting a small basic ring structure in the combined image, and removing local redundant edges and burr-shaped noise edges in skeleton lines in combination with the degree and length information of vertexes. And finally, fitting each section on the skeleton line by adopting a moving average algorithm and a B-spline curve section to obtain a smooth skeleton line conforming to a model topological structure. The method is accurate in result and high in robustness, and can play a very important role in application aspects of three-dimensional model deformation, topology, form acquisition and the like.

A method for measuring diffusional anisotropy in diffusion-weighted magnetic resonance imaging. The method includes determining an orientation diffusion function (ODF) for one or more fibers within a single voxel, wherein the ODF includes lobes representative of a probability of diffusion in a given direction for the one or more fibers. The method also includes characterizing an aspect ratio of the lobes. The method further includes determining a multi-directional anisotropy metric for the one or more fibers based on the aspect ratio of the lobes.

Provided is a grid model voxelization method and apparatus. The method includes the following steps of acquiring a grid model; determining a plurality of voxel units and preprocessing at a part of the grid model according to the preset voxelization parameters to obtain the pre-facet list of each voxel unit; processing the pre-facet list of each voxel unit to obtain a preferable facet list set, the preferable facet list set of each voxel unit includes at least one preferable facet list to express that at least one facet in the pre-facet list is included in the voxel unit; acquiring the total facet list of a single voxel grid according to the preferable facet list set of each voxel unit; acquiring the total facet list according to the total facet list of their respective single voxel grids of the plurality of voxel units, the total facet list is used for forming the corresponding voxels of the grid model after the voxelization. The grid model voxelization method and apparatus can completely guarantee all of the details of the grid model in the voxelization result in an accurate, efficient and robustness manner.

The invention relates to a method for training a brain image segmentation model. The method comprises the following steps: collecting a brain image data set; segmenting the brain image by using a plurality of analysis software to obtain a plurality of groups of machine labels; performing manual labeling on a part of the brain image to obtain an artificial label; and based on the brain image data set and the associated label, iteratively training the segmentation model to be trained by circularly executing the following steps to obtain a target segmentation model: inputting the brain image into the segmentation model to be trained to obtain a predicted segmentation result; according to the consistency between the machine labels of the single voxels, determining the weights of the labels; calculating a loss function value according to the difference between the predicted segmentation result and each label and the weight; adjusting network parameters of the to-be-trained segmentation model based on loss function value minimization to obtain a current iteration segmentation model; wherein the weight of the machine label of the single voxel is negatively correlated with the consistency. The invention further relates to a brain image segmentation method and a brain image segmentation device.

A guide map is created for placing a spectroscopic voxel in a region of interest in single voxel magnetic resonance spectroscopy. An anatomically planned image of the region of interest is obtained by MRI. stepping spectroscopic voxels across the region of interest, measuring a characteristic of the magnetic field used in the MRI at each location of the imaging voxel, and using the measurements to derive an indication of a magnetic field over the region of interest A guided FWHM map of the magnetic field uniformity/inhomogeneity. The guide map is created by superimposing the guide FWHM map on the anatomical planning image. A spectroscopic voxel having a size corresponding to the spectroscopic voxel is placed within the region of interest according to the guide map. Thereafter, spectral data is acquired from the region of interest confined to the single voxel.

An NMR (nuclear magnetic resonance) single voxel localization and one-dimensional pure chemical shift spectroscopy method comprises steps as follows: a to-be-detected sample is put in a detection cavity of a magnetic resonance imaging instrument; the position of the sample in the detection cavity is adjusted to ensure that an interested region is located at the center of the detection cavity for tuning, shimming and power and frequency correction; pai/2 non-selective radio-frequency pulse width of an excitation sample is measured, and measured pai/2 non-selective radio-frequency pulse can turn the magnetization vector from the Z-axis longitudinal direction to the XY transverse plane; a single voxel localization and one-dimensional pure chemical shift spectroscopy pulse sequence is imported to the imaging instrument, and a signal excitation module, a single voxel localization module and a pure chemical shift evolution module of the single voxel localization and one-dimensional pure chemical shift spectroscopy pulse sequence are opened; sequence parameters are set, and data sampling is executed; after data are sampled, sampled data are subjected to post-processing, post-processing includes two-dimensional Fourier transform, spectrogram indirect dimension projection and DMUSIC (decay multiple signal classification), and single voxel localization and one-dimensional pure chemical shift spectroscopy with high resolution and high signal-to-noise ratio is obtained.

It is an integrative platform for visualization, preprocessing and quantitation of MRS data acquired using single voxel, multi voxel magnetic resonance spectroscopy imaging (MRSI) and MEshcher-GArwood Point-RESolved Spectroscopy (MEGA-PRESS) acquisition methods. The method integrates both time- and frequency-domain signal processing methods on a single platform. The method is optimized for proton (¹H) and phosphorous (³¹P) MRS data. It employs the use of iterative baseline estimation and fitting procedure to provide improved quantitation accuracy. The method can be used in both interactive and automatic mode to cater to the needs of researchers and clinicians.