51 results about "MRI diffusion" patented technology

Diffusion tensor magnetic resonance signals are analyzed. Diffusion weighted, signals are acquired, each signal having a plurality of voxels (10). The diffusion weighted signals are sampled to obtain at least one set of resampled diffusion weighted signals (11). A diffusion tensor for each voxel is determined from each set of the resampled diffusion weighted signals (12). An empirical statistical distribution is determined for a quantity associated with the diffusion tensor from the diffusion tensors determined from the at least one set of the resampled diffusion weighted signals (13).

A method predicting stroke evolution uses magnetic resonance diffusion and perfusion images obtained shortly after the onset of stroke symptoms to automatically estimate the eventual volume of dead cerebral tissue resulting from the stroke. The diffusion and perfusion images are processed to extract region(s) of interest presenting tissue at risk of infarction. A midplane algorithm is also used to calculate ratio and diffusion and perfusion measures for modelling infarct evolution. A parametric normal classifier algorithm is used to predict infarct growth using the calculated measures.

Pulse sequences are applied to a fluid in an earth formation in a static magnetic field having internal gradients. From the received signals, relaxation and diffusion characteristics of the fluid are determined. The determination takes into account the internal field gradients.

The invention provides a single-scanning quantitative magnetic resonance diffusion imaging method based on dual echo, and relates to a magnetic resonance imaging method. According to the method, two echoes with the same evolution time are generated through two small-angle excitation pulses with the same turning angle, so that the same transverse relaxation time is achieved; a displacement gradient is added after each excitation pulse to achieve central displacement of the two echo signals in a signal space, and a diffusion gradient is added after the first excitation pulse, so that diffusion reduction only exists in the first echo signal; accordingly, signals under different diffusion factors are obtained. The two echo signals are from one imaging slice, so that the two echo signals can be separated through priori knowledge of the two echo signals by matching sparse conversion with a corresponding separation algorithm. Finally, a quantitative ADC image is obtained by performing apparent diffusion coefficient calculation on two signals obtained through separation. Single-scanning quantitative ADC imaging is obtained through the method, and the quality of the obtained ADC image is good.

The embodiment of the invention discloses an image distortion correcting method and device. The method comprises the following steps of: extracting an image contour of a source image; obtaining distortion information according to the image contour; and correcting the source image by using the distortion information so as to register the source image with a target image. By using the method and device, disclosed by the invention, the influences of the contrast, b value, direction variation and the like in a diffusion weighted magnetic resonance image on the correction are avoided; moreover, additional reference scanning is not needed so that convenient, fast and accurate image distortion correction is realized.

The invention discloses a motion correction method for magnetic resonance multiple excitation diffusion imaging. The method comprises the steps of collecting a magnetic resonance multiple excitation sequence; obtaining an image echo signal and a two-dimensional navigation signal through a magnetic resonance scanning sequence; estimating motion parameters through the two-dimensional navigation signal; performing rotational and translational correction on the image echo signal and the two-dimensional navigation signal according to the motion parameters, and discarding tainted data, thereby obtaining corrected data; integrating the corrected data collected in multiple excitation to perform parallel imaging reconstruction; estimating rotational motion parameters through an image registration algorithm to perform diffusion gradient correction on a reconstructed image; and performing final calculation by utilizing corrected diffusion image and diffusion gradient to obtain diffusion tensor imaging parameters. According to the method, various motion errors in a magnetic resonance diffusion imaging scanning process can be effectively corrected, so that an artifact-free high-resolution diffusion tensor image is obtained, the errors are effectively reduced, and the accuracy of calculating magnetic resonance diffusion imaging tensor parameters is improved.

In a method and apparatus to correct distortions in magnetic resonance diffusion images, a distortion model is provided to a computer, at least one reference image is acquired, multiple diffusion images are acquired and after the acquisition of one diffusion image of the multiple diffusion images the following steps are executed in the computer. The diffusion image is brought into registration with the at least one reference image, the distortion model is adapted using the result of the registration, and distortions of the diffusion image are corrected using the distortion model.

The invention discloses a multi-tensor-based magnetic resonance diffusion weighted image structure adaptive smoothing method, relates to a magnetic resonance diffusion weighted image smoothing method, belongs to the field of medical image processing, and solves the problem that the accuracy of the fiber structure information of each obtained voxel is low because of poor noise suppression in the conventional method. The multi-tensor-based magnetic resonance diffusion weighted image structure adaptive smoothing method comprises the following steps: firstly, selecting related parameters, and setting an initial neighborhood radius; secondly, calculating the initial fiber structure information of each voxel; thirdly, calculating the weights of all voxels in the neighborhood radius on the voxel according to the fiber structure information, performing weighted smoothing on a magnetic resonance diffusion weighted image, and recalculating the fiber structure information of each voxel after the magnetic resonance diffusion weighted image is smoothed; fourthly, judging whether a stopping criterion for iteration is met or not, if not, expanding the neighborhood radius and continuing to performing the third step, or else, ending the calculating. The multi-tensor-based magnetic resonance diffusion weighted image structure adaptive smoothing method is applicable to processing the information of the magnetic resonance diffusion weighted image.

The invention discloses an under-sampling magnetic resonance diffusion spectrum reconstruction method in combination with sparse and low-rank characteristics, and relates to an under-sampling reconstruction method of magnetic resonance diffusion spectrum. The method comprises generating a Laplace-Fourier joint transformation matrix; establishing an under-sampling reconstruction model in combination with sparse and low-rank characteristics; solving an algorithm based on the under-sampling reconstruction model in combination with sparse and low-rank characteristics; obtaining a recovered diffusion spectrum vector s by the step 3, and obtaining [Rho]s by an operator [Rho] as the ultimately recovered diffusion spectrum. The method comprises generating a Laplace-Fourier joint transform matrix according to experimental parameters; then establishing an under-sampling reconstruction model in combination with sparse and low-rank characteristics; reconstructing the diffusion spectrum vector by an iterative algorithm; and finally transforming the diffusion spectrum vector into the diffusion spectrum. The method reconstructs a complete magnetic resonance diffusion spectrum with a small amountof data, has high reconstruction precision and a good anti-noise ability.

In a method and magnetic resonance (MR) system for determining at least one measuring point-in-time in a cardiac cycle for conducting diffusion measurements of the myocardium of an examination object, a sequence of MR images of the heart is acquired and a time curve of a parameter of the cardiac geometry is determined in the sequence of MR images. At least one mean of the parameter of the cardiac geometry is determined from the time curve of the parameter. For the determined at least one mean of the parameter, the associated point-in-time in the time curve of the parameter is determined in which the determined mean occurs, wherein the determined point-in-time defines the at least one measuring point-in-time in a cardiac cycle during which the diffusion measurements of the myocardium are carried out.

The invention belongs to the field of analysis chemistry of Fischer-Tropsch synthesis water composition detection and specifically relates to nuclear magnetic resonance detection methods for Fischer-Tropsch synthesis water compositions. According to a method, on the basis of a three-dimensional nuclear magnetic resonance diffusion sorting spectrum -<1>H-<1>H homonuclear chemical shift correlationspectrum, through utilization of difference of a diffusion rate and a coupling signal of each composition of Fischer-Tropsch synthesis water in a solvent, obtained diffusion rate and coupling signal data is represented in a three-dimensional map form; horizontal and longitudinal coordinates of a map are chemical shift; vertical coordinates are diffusion coefficients; chemical shift planes with different diffusion coefficients are obtained on the vertical coordinates according to the difference of the diffusion coefficient of each composition in the Fischer-Tropsch synthesis water; compounds with the same diffusion coefficient value are identified in sequence according to the coupling signals of the -<1>H-<1>H homonuclear chemical shift correlation spectrum; and each composition in the Fischer-Tropsch synthesis water is detected. According to the method, an obtained analysis result is visual and clear, detection resolution is high, operation is simple, the result is accurate and precision is high. Fischer-Tropsch synthesis water sample compositions can be detected qualitatively and quantitatively. The method is applicable to qualitative detection of various low carbon small molecular compound compositions.

The invention relates to an image processing technology, and specifically relates to a brain structure network connection optimization method based on a random partitioning model. The problem that a brain structure network built using the existing brain structure network building method is of low credibility is solved. The brain structure network connection optimization method based on a random partitioning model is implemented according to the following steps: S1, preprocessing a magnetic resonance diffusion weighted image, and partitioning the preprocessed magnetic resonance diffusion weighted image; S2, calculating the number of fiber bundles of every two brain intervals; S3, binarizing a fiber bundle number matrix of the brain intervals according to a threshold; S4, building a brain structure central network model based on multiple brain structure network model samples; S5, calculating the credibility of connection in the brain structure central network model; and S6, rebuilding and optimizing the brain structure central network model. The method is suitable for brain structure network building.

Disclosed is a noninvasive measuring method of microstructure of biological tissue. The noninvasive measuring method includes: performing magnetic resonance diffusion-weighted imaging on the biological tissue; measuring actual image signal strength of each pixel point in each magnetic resonance image; according to the actual image signal strength and calculated image signal strength, solving to acquire extracellular clearance volume ratio, cell volume ratio, blood vessel volume ratio, intracellular diffusion vector in a diffusion-weighted vector direction, blood diffusion vector in the diffusion-weighted vector direction and extracellular clearance diffusion vector in the diffusion-weighted vector direction of each pixel point in the magnetic resonance images; restructuring magnetic resonance images. By the noninvasive measuring method, structural information of different tissue components can be provided, and anisotropic diffusion characteristics of water molecules in the tissue can be analyzed well.