17 results about "Echo planar" patented technology

Disclosed in the present invention are a 3D navigator-based 3D gradient spin-echo diffusion imaging method, and a device. The method comprises: first, using a global saturation module to destroy previous residual transverse magnetization; second, by means of a diffusion encoding module, embedding a pair of trapezoidal cosine oscillation gradients or pulse gradients into radio frequency pulses of 90°x-180°y-90°-x, and separating diffusion encoding from signal acquisition; then using a fat saturation module to suppress a fat signal; using a 3D gradient spin-echo readout method to acquire an image signal; and finally, acquiring a 3D navigation echo signal in the last spin echo for correcting a phase error between multiple excitations. The present invention can effectively eliminate phase errors between multiple acquisitions and realize high-resolution whole-brain diffusion imaging. Compared with 2D echo planar imaging, the present invention increases the signal-to-noise ratio of diffusion magnetic resonance imaging, thereby supporting higher-resolution whole-brain 3D diffusion magnetic resonance imaging.

The present invention provides a fast multi-contrast magnetic resonance diffusion imaging and reconstruction method and system, including: using a keyhole echo plane sequence to undersample k-space data of multiple diffusion-weighted images through multiple receiving coils; constructing an objective function including a multi-coil image fidelity term and an image regularization term based on the coil-space-contrast domain tensor low-rank (Low-RankTensorConstraint); minimizing the objective function through an optimization algorithm, reconstructing the diffusion images of all receiving coils and obtaining relevant quantitative parameter images according to the specific way of contrast change. The present invention implements undersampling of k-space through a keyhole-EPI sequence, improves the resolution of multi-contrast diffusion imaging, shortens the echo time, thereby improving the deformation artifacts of the image and reducing the imaging time; avoids the step of solving the coil sensitivity map, reduces the image artifacts caused by variable-density EPI imaging, and improves the robustness and accuracy of the reconstruction result.

The application discloses a physical basis model multi-position high-definition diffusion magnetic resonance imaging method, and relates to a multi-shot planar echo diffusion magnetic resonance imaging method. The method comprises the following steps: 1) acquiring k-space data of a diffusion magnetic resonance imaging to be reconstructed, which is collected by a multi-shot planar echo sequence; 2) designing a bidirectional one-dimensional low-rank reconstruction model based on a local smooth phase; 3) generating data by using a physical diffusion model; 4) training a basis model neural network by using the physical generated data; 5) solving the bidirectional one-dimensional low-rank reconstruction model; and 6) combining reconstruction parameters prompted by the basis model neural network, and generalizing reconstruction to obtain multiple-position high-definition diffusion magnetic resonance images without motion artifacts. The method realizes robust high-definition magnetic resonance diffusion imaging of multiple challenging positions without adjusting parameters by using a bidirectional one-dimensional low-rank optimization reconstruction method and a neural network to adaptively optimize reconstruction parameters.

A method for water-fat separated magnetic resonance imaging (MRI) is provided herein. The method includes acquiring multi-echo MRI data from a subject using an echo planar time-resolved imaging (EPTI) pulse sequence, wherein echo spacing creates in-phase and out-of-phase relationships between water and fat signals. The method includes separating acquired data into odd echoes corresponding to in-phase data and even echoes corresponding to out-of-phase data, independently reconstructing the separated echoes to generate in-phase and out-of-phase images using subspace reconstruction, and generating separate water-only and fat-only multi-echo image series by performing water-fat separation using the in-phase images and the out-of-phase images.

The invention relates to a plane echo imaging method and system, computer equipment and a storage medium, and the method comprises the steps: obtaining a K-space data set obtained after the radio frequency excitation of a to-be-imaged region, the K-space data set comprising an echo time dimension, the K space data set is under-sampled along at least one phase coding direction and echo time dimension; recovering the K space data set along at least one phase coding direction and echo time dimension to obtain an updated K space data set; and reconstructing according to the updated K space data set to obtain a plurality of plane echo images. According to the method and the device, the problem that plane echo imaging cannot give consideration to improvement of the signal-to-noise ratio, the robustness and the calculation speed of the image in related technologies is solved, and the signal-to-noise ratio, the robustness and the calculation speed of the plane echo imaging are comprehensively improved.

An intelligent reconstruction method for abdominal multi-shot high-definition diffusion magnetic resonance, relates to intelligent reconstruction of abdominal diffusion magnetic resonance image based on multi-shot interleaved echo sequence acquisition. It comprises the following steps: 1) acquiring frequency domain data of abdominal diffusion magnetic resonance image acquired by multi-shot interleaved echo sequence; 2) designing intelligent high-definition abdominal diffusion magnetic resonance reconstruction model; 3) constructing a large number of paired training data and using them for training of the phase segmentation network in the reconstruction model to obtain trained network parameters; 4) solving the intelligent high-definition abdominal diffusion magnetic resonance reconstruction model by using the convex set projection algorithm to obtain the final reconstruction result. Compared with the traditional reconstruction algorithm, the proposed method has better reconstruction signal-to-noise ratio and artifact suppression capability, and can realize high-definition diffusion image reconstruction.

Methods, systems, and software are provided for generating quantitative maps and synthetic parameter-weighted images using time-resolved magnetic resonance fingerprinting. The subject methods simultaneously measure multiple quantitative parameters, including T1, T2, T2*, and proton density along with quantitative susceptibility mapping, and can generate multiple synthetic parameter-weighted images, including T1-weighted, T2-weighted, proton density-weighted, and susceptibility-weighted images from a single scan. Time-resolved magnetic resonance fingerprinting schemes are provided to implement an accelerated echo planar sampling of a hybrid space spanned by the phase encoding dimension and the temporal dimension. T2* quantification is added with minimal extra scan time, which also enables simultaneous quantitative susceptibility mapping and synthetic T2* weighted / susceptibility weighted imaging. Multi-parametric quantification can be acquired from time-resolved magnetic resonance fingerprinting within the time of a single breath-hold of a subject, which greatly reduces the impact of inspiration motion.

The application discloses a magnetic resonance temperature imaging method and device based on an echo planar time resolution sequence, and the method comprises the following steps: collecting multi-echo data of a target human tissue based on a preset echo planar time resolution sequence; inputting the multi-echo data into a pre-constructed magnetic resonance water-fat signal model, iteratively processing a plurality of related parameters, and extracting water signals and fat signals of the target human tissue; and determining a phase part affected by temperature in water protons based on the water signals and the fat signals, so as to obtain an actual temperature distribution of the target human tissue. Therefore, the technical problem that, in the prior art, it is difficult to perform real-time monitoring of temperature for a scanning part with high requirements for time resolution or spatial resolution, and the scanning result has artifacts, which has a great influence on the treatment result, is solved.

The application discloses a reconstruction method of planar echo imaging, comprising the following steps: S1, collecting planar echo data and multi-echo gradient echo data of a region to be imaged respectively; S2, performing inverse geometric correction on the multi-echo gradient echo data to generate corrected data; and S3, performing image reconstruction according to the corrected data and the planar echo data to generate an imaging image. The application has the beneficial effect that the correction of the planar echo image is realized by collecting multi-echo gradient echo data and calculating a B0 field, the problem of possible artifacts in the calibration process of the planar echo imaging in the prior art is avoided, and the image of the planar echo imaging is clearer. Meanwhile, the multi-echo gradient echo data is used for coil sensitivity correction, the scanning speed is higher, and the calibration time can be effectively shortened.

A physical intelligent magnetic resonance diffusion weighted image denoising and quantification method relates to diffusion magnetic resonance weighted imaging. The method comprises the following steps: 1) obtaining diffusion weighted magnetic resonance data acquired by a planar echo imaging sequence in multiple diffusion directions; 2) designing a deep learning network model and loss function for physical intelligent magnetic resonance diffusion weighted image denoising and quantification; 3) using the training data set obtained in step 1), training a deep learning network model for physical intelligent magnetic resonance diffusion weighted image denoising and quantification; 4) inputting the diffusion weighted data to be denoised into the trained network to generate the final denoising and quantification results. Through the joint application of physical regularization loss and low b-value data, the low signal-to-noise ratio problem in magnetic resonance diffusion weighted imaging is effectively solved, image denoising is achieved, and accurate quantitative results are further provided. While reducing the number of acquisitions, the image quality and ADC quantitative accuracy can be maintained or even improved.

A method for correcting geometric distortions of thermometry data in magnetic resonance imaging obtained by means of fast planar echo sequences, comprising the following steps: a first series (I) of MRI reference image acquisitions, with phase encoding in one direction (e.g., R->L), a second series (II) of MRI thermometry image acquisitions, with phase encoding in the opposite direction to step one (e.g., L->R), carried out with imaging parameters identical to those used in the first series, an estimation (III, IV) of the geometric distortions, from the magnitude components of the reference images and the thermometry images thus acquired, so as to determine geometric distortion correction data, and an application (V) of the geometric distortion correction data on thermometry images and / or thermometry results obtained from the processing of these thermometry images.See Figure 3.

The present invention discloses a method and device for correcting geometric distortion of MRI images, which relates to the field of medical image processing, and includes the steps of: acquiring echo planar imaging diffusion weighted imaging and fast spin echo diffusion weighted imaging from a magnetic resonance imaging device; performing preprocessing on the echo planar imaging diffusion weighted imaging and the fast spin echo diffusion weighted imaging to obtain preprocessed images. Main technical solutions and effects: Since geometric distortion will directly affect the accurate presentation of anatomical structures and lesion areas in MRI images, the present invention can provide more real and accurate image data by effectively correcting the geometric distortion in the echo planar imaging diffusion weighted imaging images, thereby improving the diagnostic accuracy of doctors, helping doctors better judge the location, size and shape of lesions, and further formulating more reasonable treatment plans.

The application relates to a multi-b-value joint high-definition diffusion magnetic resonance intelligent imaging method, and relates to image reconstruction. 1) data acquisition, containing multi-shot interleaved echo planar diffusion weighted data with b values of 0 s / mm 2 and other b values; 2) generating a training data set, reconstructing a magnetic resonance image with a b value of 0 s / mm 2 , estimating channel sensitivity from the image with a b value of 0; using PAIR to reconstruct diffusion weighted data with other b values as training labels; 3) designing a diffusion weighted intelligent imaging model and a loss function; 4) training a joint multi-b-value intelligent reconstruction network using the training data set; 5) acquiring multi-shot diffusion weighted test data to be reconstructed; 6) reconstructing multi-shot diffusion weighted data using the trained intelligent reconstruction network to obtain a reconstructed image. The time for reconstructing a single picture by using a traditional algorithm can be reduced from 1-2 min to 0.2 s, multi-shot diffusion weighted images can be quickly reconstructed, the signal-to-noise ratio and the image quality can be improved, and Nyquist ghosting can be suppressed.

Magnetic resonance imaging (“MRI”) using a PROPELLER echo-planar time-resolved imaging with dynamic encoding (“PEPTIDE”) scheme is described. The PEPTIDE scheme combines a PROPELLER-style trajectory with an echo-planar time-resolved imaging (“EPTI”) acquisition framework, along with dynamic-updating of sensitivity-encoding information.

The application discloses a 3D gradient spin echo diffusion imaging method and device based on a 3D navigator. The method first destroys previous residual transverse magnetization in a global saturation module; secondly, a pair of trapezoidal cosine oscillation gradients or pulse gradients are embedded into 90° x -180° y -90° ‑x RF pulses to separate diffusion encoding from signal acquisition; then, a fat saturation module is used to suppress fat signals; then, a 3D gradient spin echo readout mode is used to acquire image signals; finally, 3D navigator echo signals are acquired in the last spin echo to correct phase errors between multiple excitations. The application can effectively eliminate phase errors between multi-section acquisitions and realize high-resolution diffusion imaging of the whole brain. Compared with 2D planar echo imaging, the application improves the signal-to-noise ratio of diffusion magnetic resonance imaging, thereby supporting higher-resolution whole brain 3D diffusion magnetic resonance imaging.

The invention discloses a physical basis model multi-part high-definition diffusion magnetic resonance imaging method, and relates to a multi-excitation plane echo diffusion magnetic resonance imaging method. Comprising the following steps: 1) acquiring k space data of diffusion magnetic resonance imaging to be reconstructed acquired by a multi-excitation plane echo sequence; 2) designing a bidirectional one-dimensional low-rank reconstruction model based on a local smooth phase; 3) generating data by using a physical diffusion model; 4) training the base model neural network by using the physical generation data; 5) solving a bidirectional one-dimensional low-rank reconstruction model; and 6) in combination with reconstruction parameters prompted by the basis model neural network, generalization reconstruction is carried out to obtain high-definition diffusion magnetic resonance images of various parts without motion artifacts. According to the method, robust high-definition magnetic resonance diffusion imaging of a plurality of challenge parts without parameter adjustment is realized through a bidirectional one-dimensional low-rank optimization reconstruction method and neural network adaptive optimization reconstruction parameters.

The invention relates to an echo plane spectral imaging system and method, in which an MRI system coil insert for use within a bore of a primary MRI system, the coil insert comprising at least one gradient coil for creating a spatially varying magnetic field along a respective axis and arranged to be electrically driven at an ultrasonic frequency.