CN-121985904-A - Accelerating magnetic resonance imaging using parallel imaging and iterative image reconstruction

Abstract

The present disclosure provides various systems and methods for magnetic resonance imaging. In one aspect, a method for magnetic resonance imaging may include receiving a k-space dataset acquired by a Radio Frequency (RF) coil. Each of the k-space data sets may correspond to a different one of the RF coils. Each of the k-space data sets may be truncated and/or undersampled. The method may further include generating a local image of the field of view based on the k-space dataset and generating an initial image based on the local image. The initial image may be a full view of the field of view. The method may further include applying an iterative image reconstruction technique to generate an updated image based on the initial image.

Inventors

• PENG HAIDONG

Assignees

• NEURO42公司

Dates

Publication Date

20260505

Application Date

20240110

Priority Date

20230111

Claims (20)

1. 1. A method for magnetic resonance imaging, the method comprising: Receiving k-space data sets acquired by RF coils of a Radio Frequency (RF) coil assembly, wherein each of the k-space data sets corresponds to a different one of the RF coils, and wherein each of the k-space data sets is truncated and undersampled; generating partial images of a field of view based on the k-space dataset, wherein each of the partial images corresponds to a different one of the k-space datasets; generating an initial image based on the partial image, wherein the initial image is a full view of the field of view, and Applying an iterative image reconstruction technique to generate an updated image based on the initial image, the iterative image reconstruction technique comprising: Designating the initial image as an input image for the iterative image reconstruction technique; Applying a phase correction to the input image to generate a first intermediate image; applying a k-space conjugate synthesis to the input image to generate a second intermediate image; calculating an output image based on the first intermediate image and the second intermediate image; Designating the output image as the input image for the next iteration, and Repeating the applying the phase correction to the input image, the applying the k-space conjugate synthesis to the input image, the calculating the output image, and the designating the output image as the input image for the next round of iterations, wherein the updating image is based on a final output image of the iterative image reconstruction technique.
2. 2. The method of claim 1, wherein the applying the phase correction to the input image, the applying the k-space conjugate synthesis to the input image, the calculating the output image, and the designating the output image as the input image for the next round of iterations are repeated until a difference between the output image and the corresponding input image meets a predetermined threshold.
3. 3. The method of claim 1, further comprising: receiving calibration k-space data sets acquired by the RF coils of the RF coil assembly, wherein each of the calibration k-space data sets corresponds to a different one of the RF coils, and wherein each of the calibration k-space data sets includes a central region, and A phase map of the central region is generated based on the calibration k-space dataset.
4. 4. The method of claim 3, wherein applying the phase correction to the input image to generate the first intermediate image comprises: Determining the amplitude of the input image, and The first intermediate image is calculated based on the amplitude of the input image and the phase map of the central region.
5. 5. The method of claim 4, wherein the k-space dataset comprises acquired k-space values, and wherein applying the k-space conjugate synthesis to the input image to generate the second intermediate image comprises: Generating a first intermediate k-space by fourier transforming the input image, wherein the first intermediate k-space comprises intermediate k-space values; generating a second intermediate k-space from the first intermediate k-space by replacing at least some of the intermediate k-space values with at least some of the acquired k-space values, and The second intermediate image is generated by inverse fourier transforming the second intermediate k-space.
6. 6. The method of claim 5, wherein calculating the output image based on the first intermediate image and the second intermediate image comprises: Adding the product of the first intermediate image and a first weighting factor to the product of the second intermediate image and a second weighting factor; Wherein the sum of the first weighting factor and the second weighting factor is equal to one.
7. 7. The method of claim 6, further comprising generating a coil sensitivity map based on the calibration k-space dataset.
8. 8. The method of claim 7, wherein the k-space dataset is acquired in parallel, and wherein generating the initial image based on the local image comprises generating the initial image based on the local image and the coil sensitivity map.
9. 9. The method of claim 8, wherein generating the initial image based on the local image and the coil sensitivity map comprises generating the initial image in accordance with a sensitivity encoding (SENSE) technique.
10. 10. The method of claim 1, wherein each of the k-space data sets is undersampled in a first lateral direction and a second lateral direction based on an undersampling rate of at least 2, and wherein each of the k-space data sets is truncated in the first lateral direction and the second lateral direction by at least 37.5%.
11. 11. The method of claim 1, wherein each of the k-space data sets is undersampled, truncated, and acquired in parallel such that a scan time required to acquire the k-space data set is less than 10% of a scan time required to acquire a fully sampled, non-truncated k-space data set having a corresponding number of phase encodings.
12. 12. A system, comprising: a magnet array configured to generate a low field strength or ultra-low field strength magnetic field to an object of interest located within a field of view; a Radio Frequency (RF) coil assembly comprising an array of RF coils, wherein the RF coils are positionable about an object of interest in the field of view, and wherein the RF coils are configured to acquire magnetic resonance signals, and A control circuit comprising a processor and a memory, wherein the memory stores the following instructions executable by the processor: Receiving k-space data sets corresponding to magnetic resonance signals acquired by the RF coils, wherein each of the k-space data sets corresponds to a different one of the RF coils, and wherein each of the k-space data sets is truncated and undersampled; generating partial images of the field of view based on the k-space dataset, wherein each of the partial images corresponds to a different one of the k-space datasets; generating an initial image based on the partial image, wherein the initial image is a full view of the field of view, and Iterative image reconstruction techniques are applied to generate an updated image based on the initial image.
13. 13. The system of claim 12, wherein the instructions executable by the processor to apply the iterative image reconstruction technique to generate the updated image comprise instructions to: Designating the initial image as an input image for the iterative image reconstruction technique; Applying a phase correction to the input image to generate a first intermediate image; applying a k-space conjugate synthesis to the input image to generate a second intermediate image; calculating an output image based on the first intermediate image and the second intermediate image; Designating the output image as the input image for the next iteration, and Repeating said applying said phase correction to said input image, said applying said k-space conjugate synthesis to said input image, said calculating said output image and said designating said output image as said input image for said next round of iterations until a difference between said output image and said corresponding input image meets a predetermined threshold, wherein said updating image is based on a final output image of said iterative image reconstruction technique.
14. 14. The system of claim 13, wherein the memory further stores the following instructions executable by the processor: Receiving a calibration k-space dataset corresponding to magnetic resonance signals acquired by the RF coils, wherein each of the calibration k-space datasets corresponds to a different one of the RF coils, and wherein each of the calibration k-space datasets includes a central region, and A phase map of the central region is generated based on the calibration k-space dataset.
15. 15. The system of claim 14, wherein the instructions executable by the processor to apply the phase correction to the input image to generate the first intermediate image comprise instructions to: Determining the amplitude of the input image, and The first intermediate image is calculated based on the amplitude of the input image and the phase map of the central region.
16. 16. The system of claim 15, wherein the memory further stores instructions executable by the processor to generate a coil sensitivity map based on the calibration k-space dataset.
17. 17. The system of claim 16, wherein the instructions executable by the processor to generate the initial image based on the local image comprise instructions to generate the initial image based on the local image and the coil sensitivity map.
18. 18. The system of claim 17, wherein the instructions executable by the processor to generate the initial image based on the local image and the coil sensitivity map comprise instructions to generate the initial image in accordance with a sensitivity encoding (SENSE) technique.
19. 19. The system of claim 13, wherein the k-space dataset comprises acquired k-space values, and wherein the instructions executable by the processor to apply the k-space conjugate synthesis to the input image to generate the second intermediate image comprise instructions to: Generating a first intermediate k-space by inverse fourier transforming the input image, wherein the first intermediate k-space comprises intermediate k-space values; generating a second intermediate k-space from the first intermediate k-space by replacing at least some of the intermediate k-space values with at least some of the acquired k-space values, and The second intermediate image is generated by fourier transforming the second intermediate k-space.
20. 20. The system of claim 13, wherein the instructions executable by the processor to calculate the output image based on the first intermediate image and the second intermediate image comprise instructions to: Adding the product of the first intermediate image and a first weighting factor to the product of the second intermediate image and a second weighting factor; Wherein the sum of the first weighting factor and the second weighting factor is equal to one.

Description

Accelerating magnetic resonance imaging using parallel imaging and iterative image reconstruction Cross Reference to Related Applications The present application is in accordance with the benefits and priority of U.S. patent application Ser. No. 18/153,111 entitled "ACCELERATING MAGNETIC RESONANCE IMAGING USING PARALLEL IMAGING AND ITERATIVE IMAGE RECONSTRUCTION," filed on even date 11 at 1/1 of 2023, volume 35 of the United states code, the disclosure of which is incorporated herein by reference in its entirety. Background The present disclosure relates to Magnetic Resonance Imaging (MRI), medical imaging, medical intervention, and surgical intervention. MRI systems typically include large complex machines that generate significantly high magnetic fields and impose significant limitations on the feasibility of certain surgical interventions. Limitations may include limited physical access to the patient by the surgeon and/or surgical robot and/or limited use of certain electrical and mechanical components in the vicinity of the MRI scanner. Such limitations are inherent in the basic design of many existing systems and are difficult to overcome. Disclosure of Invention According to one aspect, the present disclosure provides a method for magnetic resonance imaging. The method may include receiving a k-space dataset acquired by a Radio Frequency (RF) coil of an RF coil assembly. Each of the k-space data sets may correspond to a different one of the RF coils. Each of the k-space data sets may be truncated and/or undersampled. The method may further include generating a local image of the field of view based on the k-space dataset. Each of the partial images may correspond to a different one of the k-space data sets. The method may further include generating an initial image based on the partial image. The initial image is a full view of the field of view. The method may further include applying an iterative image reconstruction technique to generate an updated image based on the initial image. In some aspects, applying the iterative image reconstruction technique to generate the updated image based on the initial image may include designating the initial image as the input image. Applying the iterative image reconstruction technique may further include applying a phase correction to the input image to generate a first intermediate image, applying a k-space conjugate synthesis to the input image to generate a second intermediate image, and calculating an output image based on the first intermediate image and the second intermediate image. The output image may be designated as the input image for the next iteration. Applying the iterative image reconstruction technique may further include repeating applying phase correction to the input image, applying k-space conjugate synthesis to the input image, calculating an output image, and designating the output image as the input image for a next round of iterations. The updated image may be generated based on a final output image of the iterative image reconstruction technique. According to another aspect, the present disclosure provides a system. The system may include a magnet array, a Radio Frequency (RF) coil assembly, and a control circuit. The magnet array may be configured to generate a low field strength or ultra-low field strength magnetic field to an object of interest located within the field of view. The RF coil assembly may include an RF coil array. The RF coil may be positioned around an object of interest in the field of view. The RF coil may be configured to acquire magnetic resonance signals. The control circuit may include a processor and a memory. The memory may store instructions executable by the processor to receive a k-space dataset corresponding to magnetic resonance signals acquired by the RF coil. Each of the k-space data sets may correspond to a different one of the RF coils. Each of the k-space data sets may be truncated and/or undersampled. The memory may further store instructions executable by the processor to generate a partial image of the field of view based on the k-space dataset. Each of the partial images may correspond to a different one of the k-space data sets. The memory may further store instructions executable by the processor to generate an initial image based on the partial image (where the initial image is a full view of the field of view) and apply iterative image reconstruction techniques to generate an updated image based on the initial image. Drawings Various aspects of the methods of construction and operation described herein, together with further objects and advantages thereof, may best be understood by reference to the following description taken in conjunction with the accompanying drawings. Fig. 1 depicts an assembly of an MRI scanning system according to at least one aspect of the present disclosure, the assembly including a dome-shaped housing of a magnetic array, the dome-shaped housing surrounding a region