8 results about "Single voxel" patented technology

The application relates to a variational correlation evaluation method and device, which comprises the following steps: acquiring magnetic resonance image data to obtain to-be-processed data; determining an iteration position sequence of the to-be-processed data and extracting iteration features to obtain a training set and a test set; inputting the training set into a variational correlation evaluation classification model for iteration training and testing, judging whether the trained variational correlation evaluation classification model converges or not, and obtaining the variational correlation evaluation classification model when the model converges, and performing effective feature extraction based on the variational correlation evaluation classification model; determining each effective feature position sequence, converting the effective feature position sequence into a three-dimensional brain structure matrix, covering the three-dimensional brain structure matrix to a preset standard human brain template, and identifying effective features related to each stimulation condition. The application quantifies the contribution of a single voxel in the process of executing a specific cognitive function, and finally identifies and extracts the least amount of features that can best represent the target stimulation condition.

The invention discloses an ESDF map construction method and device based on priority dynamic updating, and relates to the technical field of intelligent driving, and the method comprises the steps: constructing a corresponding three-dimensional space model; dividing the three-dimensional space model into a plurality of single voxel grids, obtaining an initial distance of a nearest obstacle corresponding to a single voxel corresponding to each single voxel grid based on the initial pose information, and constructing an ESDF map; based on a preset processing view field range and the real-time pose information of the target vehicle, setting a dynamic update priority rule of each single voxel; based on the dynamic updating priority rule of each single voxel, an updating task list sorted according to the priority is formulated, and the ESDF map is dynamically updated. According to the method, the defects in the prior art are overcome, the map updating efficiency is improved through a priority-based dynamic updating mechanism, and support is provided for L4-level intelligent sanitation vehicle path planning and obstacle avoidance control.

The application discloses a diffusion-weighted magnetic resonance spectrum parallel acquisition and reconstruction method. The method comprises the following steps: adding a pair of diffusion gradients in a single voxel spectrum sequence to obtain a single voxel diffusion-weighted magnetic resonance spectrum sequence; performing point-by-point summation on single-band radio frequency pulses at each voxel position of interest to obtain multi-band radio frequency pulses; obtaining a multi-voxel diffusion-weighted magnetic resonance spectrum signal through the single voxel diffusion-weighted magnetic resonance spectrum sequence and the multi-band radio frequency pulses; obtaining a sensitivity map of each channel of a receiving coil; separating and reconstructing the multi-voxel diffusion-weighted magnetic resonance spectrum signal according to the sensitivity map; and finally obtaining a separated and reconstructed multi-voxel diffusion-weighted magnetic resonance spectrum signal. The application can simultaneously measure diffusion-weighted magnetic resonance spectrum signals of multiple voxels of a human body, and obtain a signal-to-noise ratio and an apparent diffusion coefficient equivalent to those of a single voxel diffusion-weighted magnetic resonance spectrum signal, thereby saving at least half of the scanning time.

A method for characterizing the microscale diffusion characteristics of a single voxel in magnetic resonance imaging, comprising: S1, constructing a probability density function of a plurality of single-voxel diffusion characteristic distributions; S2, designing a special sequence to scan and image a target object to obtain scan data for constructing the probability density function of the plurality of single-voxel diffusion characteristic distributions; and S3, calculating the probability density function of the plurality of single-voxel diffusion characteristic distributions in step S1 according to the imaging sequence parameters and the scan data in step S2 to obtain the microscale diffusion characteristic results of the single voxel. The method for characterizing the microscale diffusion characteristics of a single voxel in magnetic resonance imaging solves the problem of how to use a single voxel in millimeter-scale magnetic resonance imaging to characterize the complex diffusion characteristics associated with the microscale tissue structure in the single voxel.

The invention discloses a virtual joint calculation method for TGS efficiency scale and emission track length, and belongs to the technical field of radioactive waste detection, and the method comprises the steps: selecting a waste bin and a detector, dividing voxels of the waste bin, dividing regions of the voxels, setting a rotation position for the waste bin, and setting A scanning positions for the detector; establishing primary simulation; presetting an efficiency scale matrix E and a track length matrix T; traversing A scanning positions of the Y rotation positions, performing simulation at each scanning position of each rotation position, counting the full-energy peak count and the equivalent track length of each track voxel, and respectively storing E and T; and subsequently, the counting rate Di of the scanning position i can be calculated according to E and T. According to the method, errors caused by separate calculation of the efficiency scale and the track length can be reduced, the accuracy of track length calculation is improved, the edge efficiency error of the detector is eliminated, and the reconstruction quality of an emission image can be effectively improved while the calculation efficiency is improved under the condition that a single pixel is a multi-point source.

Embodiments of the present application disclose a medical image processing method and device, an image processing apparatus and a medium. The method comprises: determining an arterial input function of an arterial blood vessel for supplying blood to a target part and attenuation coefficient enhancement information of a single voxel corresponding to the arterial blood vessel according to a plurality of groups of dynamic enhancement CT images collected at different time points; inputting the arterial input function and the attenuation coefficient enhancement information into a preset estimation model to obtain a preset blood flow parameter of the target part, the preset blood flow parameter comprising a blood flow velocity and an average transit time, and the preset estimation model being constructed based on a box-type attenuation function. The technical problem that the prior art cannot accurately determine the blood flow parameter of the dynamic enhancement CT is solved.

This invention provides a multidimensional magnetic resonance imaging (MRI) method and apparatus, comprising: determining the acquisition sequence and acquisition parameters for MRI; performing full sampling of the sample under test based on the acquisition parameters to obtain full-sample one-dimensional signal data, and generating a full-sample one-dimensional distribution of the sample under test using a Laplace transform algorithm; performing sparse sampling based on the acquisition parameters to obtain a multidimensional magnetic resonance signal of the sample under test, and extracting multidimensional magnetic resonance sampling data of each monomer element based on the multidimensional magnetic resonance signal; determining the initial multidimensional magnetic resonance distribution of each monomer element based on the multidimensional magnetic resonance sampling data of each monomer element using a Laplace transform algorithm; iteratively updating the initial multidimensional magnetic resonance distribution to obtain the updated multidimensional magnetic resonance distribution of each monomer element; and generating a multi-parameter spectrum of the sample under test based on the updated multidimensional magnetic resonance distributions. This multidimensional magnetic resonance imaging method and apparatus improves the accuracy of the obtained multidimensional magnetic resonance distribution spectrum.

This invention provides a method and system for quantifying the volume of peripancreatic necrotic tissue based on enhanced CT images, belonging to the field of medical image processing technology. The method involves constructing and training a deep convolutional neural network model to automatically segment enhanced abdominal venous phase CT images, outputting a pixel-level probability map of peripancreatic necrotic tissue. The probability map is then converted into a three-dimensional segmentation mask using image morphology processing algorithms. The volume of peripancreatic necrotic tissue is calculated based on the number of voxels and the volume of a single voxel in the three-dimensional segmentation mask. This invention solves the problems of high subjectivity, low accuracy, and time-consuming and laborious manual layer-by-layer delineation in traditional manual estimation. It achieves full automation of the peripancreatic necrotic tissue segmentation and volume quantification process, providing an objective, accurate, and repeatable quantitative tool for assessing the severity of acute pancreatitis, selecting intervention timing, and dynamically monitoring treatment efficacy.