6 results about "MRI diffusion" patented technology

A computer system that performs pairwise harmonization is described. During operation, the computer system may receive information specifying magnetic-resonance diffusion measurements, where the magnetic-resonance diffusion measurements are associated with at least an individual and a first site. Then, the computer system may perform the pairwise harmonizing of the magnetic-resonance diffusion measurements based at least in part on target magnetic-resonance diffusion measurements, where the target magnetic-resonance diffusion measurements are associated with a population and one or more target sites, and the magnetic-resonance diffusion measurements and the target magnetic-resonance diffusion measurements may be acquired using different magnetic-resonance scanners. Next, the computer system may perform quality control on the pairwise harmonized magnetic-resonance diffusion measurements, where the quality control may include comparing the pairwise harmonized magnetic-resonance diffusion measurements associated with the first site and the one or more target sites.

The invention discloses a liver cancer iconography diagnosis method based on artificial intelligence, which integrates anatomical structure characteristics of CT enhanced scanning, soft tissue heterogeneity characteristics of MRI diffusion weighted imaging and dynamic blood flow characteristics of ultrasound contrast, and covers three dimensions of morphology, histology and hemodynamics of a focus. The one-sidedness defect of single-mode information is overcome, multi-mode data complementation is achieved, the misdiagnosis and missed diagnosis risks caused by feature missing are effectively reduced, and the diagnosis accuracy is improved. The cross-modal attention module calculates the cosine similarity between each modal and the global reference feature and dynamically distributes the weight, thereby avoiding the limitation of the fixed weight, enabling different modal features to make accurate contributions according to the actual expression of the focus, strengthening the characterization capability of the combined feature for the liver cancer focus, and improving the accuracy of the liver cancer focus. And the recognition precision of the model on difficult focuses such as fuzzy boundaries and complex blood supply is improved.

The invention discloses a transcranial electrical stimulation finite element simulation method and a related device, and the method comprises the steps: carrying out the high-frequency conductivity imaging based on magnetic resonance, and obtaining the high-frequency conductivity; according to the high-frequency conductivity, reconstructing a low-frequency conductivity tensor based on a magnetic resonance diffusion tensor imaging technology; constructing an individual head finite element model with voxel-level conductivity according to the reconstructed low-frequency conductivity tensor; and performing electric field solution on the individual head finite element model by using a finite element method to obtain an electrical stimulation electric field distribution simulation result under the specified electrode. According to the method, the limitation of brain tissue segmentation errors and isotropic hypothesis is avoided, the accuracy and physiological credibility of conductivity modeling and simulation are remarkably improved, and a reliable basis can be provided for individualized optimization design and clinical application of transcranial electrical stimulation.

A computer system that performs pairwise harmonization is described. During operation, the computer system may receive information specifying magnetic-resonance diffusion measurements, where the magnetic-resonance diffusion measurements are associated with at least an individual and a first site. Then, the computer system may perform the pairwise harmonizing of the magnetic-resonance diffusion measurements based at least in part on target magnetic-resonance diffusion measurements, where the target magnetic-resonance diffusion measurements are associated with a population and one or more target sites, and the magnetic-resonance diffusion measurements and the target magnetic-resonance diffusion measurements may be acquired using different magnetic-resonance scanners. Next, the computer system may perform quality control on the pairwise harmonized magnetic-resonance diffusion measurements, where the quality control may include comparing the pairwise harmonized magnetic-resonance diffusion measurements associated with the first site and the one or more target sites.

The present disclosure relates to a magnetic resonance diffusion imaging fat suppression method based on echo navigation water-fat separation, comprising: acquiring echo and / or navigation echo corresponding to multiple chemical shift encoding points under the condition that the b value is equal to 0 and the condition that the b value is greater than 0; solving the water map, the fat map, the main magnetic field inhomogeneity and the relaxation time of the target object under the condition that the b value is equal to 0, and determining the water map and the fat map of the target object under the condition that the b value is greater than 0. Through the present disclosure, a chemical shift encoding fat suppression method suitable for clinical use is provided for magnetic resonance EPI diffusion imaging, the interference of fat chemical shift artifacts is reduced, the accuracy of image contrast and quantitative parameter measurement is improved, the universality of chemical shift encoding EPI DWI is improved, and the image reconstruction speed and robustness are accelerated.

The application discloses a kind of based on clustering's magnetic resonance diffusion ordering spectrum processing method, device and readable medium, by obtaining the attenuation spectrum corresponding to several gradient coding magnetic resonance diffusion ordering spectrum, selecting the signal point of each spectral peak on the chemical shift dimension in attenuation spectrum, and constructing the feature vector corresponding to each signal point, length is the number of gradients;According to the feature vector of all signal points of each spectral peak, classification is carried out by clustering algorithm, and the classification result of the signal point of each spectral peak is obtained;According to the classification result of the signal point of each spectral peak and the spectral intensity corresponding to each signal point, statistical analysis is carried out, and the class of each spectral peak is determined, according to the class, the magnetic resonance diffusion ordering spectrum is separated into components, and the separated spectrum corresponding to different components is obtained.The method is simple in operation, widely applicable, excellent in effect, suitable for a small amount of gradient, can effectively shorten time, good in robustness, and small error.