WO2022027419A1 - 磁共振成像方法、装置及计算机存储介质 - Google Patents

磁共振成像方法、装置及计算机存储介质 Download PDF

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WO2022027419A1
WO2022027419A1 PCT/CN2020/107359 CN2020107359W WO2022027419A1 WO 2022027419 A1 WO2022027419 A1 WO 2022027419A1 CN 2020107359 W CN2020107359 W CN 2020107359W WO 2022027419 A1 WO2022027419 A1 WO 2022027419A1
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dimensional
magnetic resonance
gradient field
resonance imaging
sequence
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PCT/CN2020/107359
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French (fr)
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王海峰
梁栋
郑海荣
刘新
苏适
丘志浪
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深圳先进技术研究院
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Priority to PCT/CN2020/107359 priority Critical patent/WO2022027419A1/zh
Priority to EP20761130.2A priority patent/EP4194877A4/en
Priority to US17/010,870 priority patent/US11918335B2/en
Publication of WO2022027419A1 publication Critical patent/WO2022027419A1/zh

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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R33/00—Arrangements or instruments for measuring magnetic variables
    • G01R33/20—Arrangements or instruments for measuring magnetic variables involving magnetic resonance
    • G01R33/44—Arrangements or instruments for measuring magnetic variables involving magnetic resonance using nuclear magnetic resonance [NMR]
    • G01R33/48—NMR imaging systems
    • G01R33/54—Signal processing systems, e.g. using pulse sequences ; Generation or control of pulse sequences; Operator console
    • G01R33/56—Image enhancement or correction, e.g. subtraction or averaging techniques, e.g. improvement of signal-to-noise ratio and resolution
    • G01R33/561—Image enhancement or correction, e.g. subtraction or averaging techniques, e.g. improvement of signal-to-noise ratio and resolution by reduction of the scanning time, i.e. fast acquiring systems, e.g. using echo-planar pulse sequences
    • G01R33/5611—Parallel magnetic resonance imaging, e.g. sensitivity encoding [SENSE], simultaneous acquisition of spatial harmonics [SMASH], unaliasing by Fourier encoding of the overlaps using the temporal dimension [UNFOLD], k-t-broad-use linear acquisition speed-up technique [k-t-BLAST], k-t-SENSE
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/05—Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fields; Measuring using microwaves or radio waves 
    • A61B5/055—Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fields; Measuring using microwaves or radio waves  involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R33/00—Arrangements or instruments for measuring magnetic variables
    • G01R33/20—Arrangements or instruments for measuring magnetic variables involving magnetic resonance
    • G01R33/28—Details of apparatus provided for in groups G01R33/44 - G01R33/64
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R33/00—Arrangements or instruments for measuring magnetic variables
    • G01R33/20—Arrangements or instruments for measuring magnetic variables involving magnetic resonance
    • G01R33/44—Arrangements or instruments for measuring magnetic variables involving magnetic resonance using nuclear magnetic resonance [NMR]
    • G01R33/48—NMR imaging systems
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R33/00—Arrangements or instruments for measuring magnetic variables
    • G01R33/20—Arrangements or instruments for measuring magnetic variables involving magnetic resonance
    • G01R33/44—Arrangements or instruments for measuring magnetic variables involving magnetic resonance using nuclear magnetic resonance [NMR]
    • G01R33/48—NMR imaging systems
    • G01R33/483—NMR imaging systems with selection of signals or spectra from particular regions of the volume, e.g. in vivo spectroscopy
    • G01R33/4833—NMR imaging systems with selection of signals or spectra from particular regions of the volume, e.g. in vivo spectroscopy using spatially selective excitation of the volume of interest, e.g. selecting non-orthogonal or inclined slices
    • G01R33/4835—NMR imaging systems with selection of signals or spectra from particular regions of the volume, e.g. in vivo spectroscopy using spatially selective excitation of the volume of interest, e.g. selecting non-orthogonal or inclined slices of multiple slices

Definitions

  • the present application relates to the technical field of image processing, and in particular, to a magnetic resonance imaging method, a magnetic resonance imaging device, and a computer storage medium.
  • Magnetic resonance imaging (MRI, Magnetic Resonance Imaging) technology is widely used in clinical medicine and medical research due to its advantages of no radiation and high resolution.
  • the scanning speed of magnetic resonance imaging is slow. Excessive scanning time causes discomfort to the patient, and at the same time, it is easy to introduce motion artifacts in the reconstructed magnetic resonance image, thereby affecting the quality of the reconstructed magnetic resonance image. How to speed up the speed of magnetic resonance imaging has always been studied. Hotspots and Difficulties.
  • the present application provides a magnetic resonance imaging method.
  • the method includes: acquiring three-dimensional undersampling data of a target object acquired based on a first three-dimensional magnetic resonance imaging sequence; wherein the first three-dimensional magnetic resonance imaging sequence has a first sinusoidal gradient field in a phase direction and a second sinusoidal gradient in a slice selection direction Gradient fields, the durations of the first and second sinusoidal gradient fields are within the readout plateau duration of the readout gradient field applied in the readout direction, and the first and second sinusoidal gradient fields are of order 0
  • the moment is 0, and the phase difference between the first sinusoidal gradient field and the second sinusoidal gradient field is ⁇ /2;
  • the three-dimensional point spread function is calculated based on the three-dimensional undersampling data or the two-dimensional mapping data of the target object; wherein, the two-dimensional mapping data and The field of view of the 3D undersampled data is the same; the sensitivity map of the target object is calculated based on the 3D low-resolution full sampling data of the target object; the
  • the present application provides a magnetic resonance imaging device.
  • the device includes a processor and a memory, the processor is coupled to the memory, and executes instructions during operation, so as to cooperate with the memory to implement the above-mentioned magnetic resonance imaging method.
  • the present application provides a computer storage medium.
  • the computer storage medium stores a computer program, and the computer program can be executed by the processor to implement the above-mentioned magnetic resonance imaging method.
  • the first sinusoidal gradient field is applied in the phase direction in the first three-dimensional magnetic resonance imaging sequence
  • the second sinusoidal gradient field is applied in the slice selection direction
  • the application time of the first sinusoidal gradient field and the second sinusoidal gradient field is During the readout plateau duration of the readout gradient field applied in the readout direction, and the 0-order moment of the first sinusoidal gradient field and the second sinusoidal gradient field are both 0, it does not affect the target object in a repetition time based on the first Signals produced by a 3D magnetic resonance imaging sequence.
  • collecting the three-dimensional under-sampling data of the target object can speed up the scanning speed of the target object.
  • the three-dimensional point spread function is calculated based on the two-dimensional mapping data, which can further reduce the scanning time of the target object and improve the imaging efficiency.
  • FIG. 1 is a schematic flowchart of a first embodiment of a magnetic resonance imaging method provided by the present application
  • FIG. 2 is a sequence diagram of an embodiment of a first three-dimensional magnetic resonance imaging sequence provided by the present application
  • FIG. 3 is a timing diagram of an embodiment of the first sinusoidal gradient field and the second sinusoidal gradient field provided by the present application;
  • FIG. 4 is a timing diagram of another embodiment of the first sinusoidal gradient field and the second sinusoidal gradient field provided by the present application;
  • FIG. 5 is a timing diagram of another embodiment of the first sinusoidal gradient field and the second sinusoidal gradient field provided by the present application;
  • FIG. 6 is a timing diagram of still another embodiment of the first sinusoidal gradient field and the second sinusoidal gradient field provided by the present application;
  • FIG. 7 is a timing diagram of still another embodiment of the first sinusoidal gradient field and the second sinusoidal gradient field provided by the present application.
  • FIG. 8 is a timing diagram of still another embodiment of the first sinusoidal gradient field and the second sinusoidal gradient field provided by the present application;
  • FIG. 9 is a schematic diagram of under-sampling magnetic resonance signals by the fast parallel imaging technology with controllable aliasing provided by the present application.
  • FIG. 10 is a sequence diagram of an embodiment of a second three-dimensional magnetic resonance imaging sequence provided by the present application.
  • FIG. 11 is a sequence diagram of an embodiment of a third three-dimensional magnetic resonance imaging sequence provided by the present application.
  • FIG. 12 is a sequence diagram of an embodiment of a fourth three-dimensional magnetic resonance imaging sequence provided by the present application.
  • FIG. 13 is a sequence diagram of an embodiment of a fifth three-dimensional magnetic resonance imaging sequence provided by the present application.
  • Figure 14 is the phantom 2 ⁇ 2 times acceleration test result provided by the application.
  • FIG. 15 is a result of applying the magnetic resonance imaging method provided by the application to a human brain imaging result in a three-dimensional equilibrium steady-state free precession sequence
  • 16 is a schematic structural diagram of an embodiment of a magnetic resonance imaging device provided by the present application.
  • FIG. 17 is a schematic structural diagram of an embodiment of a computer storage medium provided by the present application.
  • Magnetic resonance parallel imaging methods are a kind of methods to accelerate the speed of MRI scanning, such as sensitivity encoding technology (SENSE, sensitivity encoding) and generalized autocalibrating partial parallel acquisition technology (GRAPPA, generalized autocalibrating partially parallel acquisitions) and so on.
  • This kind of method achieves the purpose of fast scanning by reducing the amount of collected data and using redundant information contained in multi-channel coils to reconstruct three-dimensional undersampled data.
  • Wave Controlled Aliasing In Parallel Imaging is a parallel imaging technology used to speed up 3D magnetic resonance scanning.
  • the MRI gradient coil is used to apply a sinusoidal gradient field with a phase difference of ⁇ /2 in the slice selection and phase directions, and a fast parallel imaging technology with controllable aliasing (2D CAIPIRINHA, two-dimension Controlled Aliasing In Parallel Imaging is used) Results In Higher Acceleration) undersampling the data, so that the aliasing artifacts caused by undersampling are scattered along the readout, layer selection and phase directions, reducing the degree of image aliasing artifacts in each pixel, thereby greatly reducing the The loss of the signal-to-noise ratio of the geometry factor (g-factor, geometry factor) in parallel imaging reconstruction is reduced, and the purpose of high-speed acceleration is achieved.
  • wave-CAIPI technology has been applied to fast spin echo (TSE, Turbo Spin Echo), magnetization-prepared fast gradient echo (MP-RAGE, Magnetization-Prepared RApid Gradient Echo) and short magnetization vector visualization (ViSTa, Visualization of In sequences such as Short Transverse relaxation time component), high-acceleration and high-resolution 3D MRI imaging is achieved.
  • TSE fast spin echo
  • MP-RAGE magnetization-prepared fast gradient echo
  • ViSTa Visualization of In sequences such as Short Transverse relaxation time component
  • Wave-CAIPI technology can more uniformly disperse aliasing artifacts into the entire imaging field of view (FOV, Field-Of-View), thereby reducing the loss of g-factor signal-to-noise ratio and achieving the purpose of high-speed accelerated scanning.
  • FOV Imaging field of view
  • the zero-order moment of the applied sinusoidal gradient field in the layer selection or phase direction is not zero, which will disturb the original signal of the MRI sequence, resulting in the generation of artifacts.
  • FIG. 1 is a schematic flowchart of a first embodiment of a magnetic resonance imaging method provided by the present application. This embodiment includes the following steps:
  • S101 Acquire three-dimensional undersampling data of a target object acquired based on a first three-dimensional magnetic resonance imaging sequence.
  • the first three-dimensional magnetic resonance imaging sequence is obtained by adjusting the seventh three-dimensional magnetic resonance imaging sequence by using the wave gradient controllable aliasing parallel imaging technology.
  • the first three-dimensional magnetic resonance imaging sequence further includes a first sinusoidal gradient field in the phase direction, and further includes a second sinusoidal gradient field in the slice selection direction. That is, the nuclear magnetic resonance system sends radio frequency pulses and gradient pulses to the target object based on the first three-dimensional magnetic resonance imaging sequence, which is equivalent to that the nuclear magnetic resonance system sends the radio frequency pulses and gradient pulses of the seventh three-dimensional magnetic resonance imaging sequence to the target object, and sends the radio frequency pulses and gradient pulses to the target object.
  • the target object emits a first sinusoidal gradient field and a second sinusoidal gradient field.
  • the durations of the first sinusoidal gradient field and the second sinusoidal gradient field are within the readout plateau duration of the readout gradient field applied in the readout direction, and the 0th order moments of the first sinusoidal gradient field and the second sinusoidal gradient field are both 0. Therefore, the signal generated by the target object based on the seventh three-dimensional magnetic resonance imaging sequence within one repetition time is not affected, so that no additional artifacts are introduced.
  • the seventh three-dimensional magnetic resonance imaging sequence may be a three-dimensional balanced Steady-State Free Precession (bSSFP) sequence, a three-dimensional gradient echo (Gradient Echo, GRE) sequence, a fast spin echo ( Turbo Spin Echo, TSE) sequence, magnetization-prepared fast gradient echo (Magnetization-Prepared RApid Gradient Echo, MP-RAGE) sequence or short magnetization vector visualization (Visualization of Short Transverse relaxation time component, ViSTa) sequence, etc. No restrictions.
  • bSSFP Steady-State Free Precession
  • GRE three-dimensional gradient echo
  • Turbo Spin Echo Turbo Spin Echo
  • MP-RAGE magnetization-prepared fast gradient echo
  • ViSTa short magnetization vector visualization
  • FIG. 2 is a sequence diagram of an embodiment of the first three-dimensional magnetic resonance imaging sequence provided in the present application.
  • the seventh three-dimensional magnetic resonance imaging sequence is a bSSFP sequence.
  • the 0-order moments of the first sinusoidal gradient field and the second sinusoidal gradient field are both 0, which means that in the first three-dimensional magnetic resonance imaging sequence, in the multiple closed regions formed by the first sinusoidal gradient field and the time axis, The area of the closed area located above the time axis is equal to the area of the closed area located below the time axis; the same is true for the second sinusoidal gradient field.
  • the first duration of applying the first sinusoidal gradient field in the phase direction is an integer multiple of the sinusoidal period, such as 1, 2, 5, 10 and so on.
  • the second duration of applying the second sinusoidal gradient field in the layer selection direction is also an integer multiple of the sinusoidal period, such as 1, 2, 5, 10 or 20 times.
  • the first duration and the second duration are less than or equal to the readout plateau duration DR of the readout gradient field.
  • the first duration may be shorter than the second duration, and the first duration and the second duration may be adjusted according to the readout plateau duration and sinusoidal period of the readout gradient field, which is not limited in this application.
  • the sinusoidal frequencies of the first sinusoidal gradient field and the second sinusoidal gradient field are the same, and the phases of the first sinusoidal gradient field and the second sinusoidal gradient field differ by ⁇ /2.
  • the first application time of the first sinusoidal gradient field may be an odd multiple of a quarter sinusoidal period earlier than the second application time of the second sinusoidal gradient field, e.g. 1, 3, 5 or 7 times, etc. That is, the first application time may be earlier than the second application time by one quarter of a sine period, three quarters of a sine period, five quarters of a sine period, or seven quarters of a sine period, or the like. Of course, the first application time may also be later than an odd multiple of the second application time by a quarter of a sine period.
  • FIG. 3 is a timing diagram of an embodiment of the first sinusoidal gradient field and the second sinusoidal gradient field provided by the present application
  • Fig. 4 is the timing chart of another embodiment of the first sinusoidal gradient field provided by the application and the second sinusoidal gradient field
  • Fig. 5 is another implementation of the first sinusoidal gradient field provided by the application and the second sinusoidal gradient field
  • Figure 6 is a timing diagram of another embodiment of the first sinusoidal gradient field and the second sinusoidal gradient field provided by the application
  • Figure 7 is the first sinusoidal gradient field and the second sinusoidal gradient field provided by the application.
  • FIGS. 3-8 is a timing diagram of still another embodiment of the first sinusoidal gradient field and the second sinusoidal gradient field provided by the present application.
  • the first application time, the second application time, and the number of sinusoidal periods of the first sinusoidal gradient field and the second sinusoidal gradient field in FIGS. 3-8 are only illustrative, and the present application is not limited thereto.
  • the first sine gradient field and the second sine gradient field in this embodiment may be obtained by a sine gradient field or a cosine gradient field through operations such as phase shifting, truncation, and combinations thereof, as shown in the first sine gradient field in FIG. 3 to FIG. 8 .
  • a sinusoidal gradient field is shown.
  • the first sinusoidal gradient field can be regarded as obtained by truncating the cosine wave by half a period (- ⁇ /4 to ⁇ /4), that is, the initial application direction of the first sinusoidal gradient field and the second sinusoidal gradient field The initial application direction is opposite.
  • the first sinusoidal gradient field and the second sinusoidal gradient field may be expressed by formulas, and FIG. 3 is used as an example in this embodiment.
  • t is the time
  • A is the magnitude of the sinusoidal gradient field
  • DC is the duration of one sinusoidal cycle
  • DR is the readout plateau duration of the readout gradient field.
  • a is a positive odd number
  • b is a positive natural number
  • c is a positive natural number
  • d is a positive natural number
  • bDC is the first duration
  • dDC is the second duration
  • both bDC and cDC are less than DR .
  • the readout K-space trajectory is a spiral form along the readout direction.
  • a three-dimensional point spread function is applied, so that each voxel of the target object is diffused along the readout direction, so in the aliased part of the image obtained by parallel imaging, the difference in coil sensitivity between aliased voxels It also increases, so that the g factor reaches a level very close to 1 during reconstruction, which can reduce the amplification of noise.
  • the first sinusoidal gradient field is applied during the readout plateau duration of the readout gradient field and the 0-order moments of the first sinusoidal gradient field and the second sinusoidal gradient field are both 0, which can eliminate the first sinusoidal gradient field and the second sinusoidal gradient
  • the field interferes with the magnetic resonance signals generated by the target object based on the first magnetic resonance imaging sequence for a repetition time, thereby avoiding the introduction of additional artifacts in the reconstructed magnetic resonance images.
  • the wave gradient controllable aliasing fast parallel imaging technology uses the data undersampling strategy to undersample the magnetic resonance signals generated by the first three-dimensional magnetic resonance imaging sequence on the target object to obtain a three-dimensional magnetic resonance imaging sequence. undersampled data.
  • the data under-sampling strategy keeps the K-space coverage unchanged, but increases the distance between adjacent phase coding lines and adjacent layer-selected coding lines.
  • Increasing the phase encoding interval and increasing the layer selection encoding interval in the K-space means that the imaging field of view is reduced in the image domain, that is, the down-sampled K-space is directly inverse Fourier transformed to the image domain, and image aliasing will occur.
  • These aliasing artifacts need to be removed by subsequent reconstruction algorithms, such as reconstruction of 3D undersampled data using sensitivity maps, which will be described in detail in subsequent steps.
  • the data undersampling strategy may be a fast parallel imaging technology with controllable aliasing, a sensitivity coding technology in parallel imaging, or an overall automatic calibration partial parallel acquisition technology, etc., which is not limited in this application.
  • the undersampling of magnetic resonance signals is described by taking the fast parallel imaging technology with controllable aliasing (Two-Dimension Controlled Aliasing In Parallel Imaging Results In Higher Acceleration, 2D CAIPIRINHA) as an example.
  • the fast parallel imaging technology with controllable aliasing can disperse the aliasing caused by undersampling to the phase and slice selection directions at the same time.
  • the sensitivity difference between the aliased pixels is enlarged, so as to achieve the purpose of reducing the geometric factor and reducing the reconstruction artifacts.
  • FIG. 9 is a schematic diagram of under-sampling a magnetic resonance signal by the fast parallel imaging technology with controllable aliasing provided by the present application.
  • the direction perpendicular to the plane is the readout direction
  • the intersection of the black dotted lines is the readout line that needs to be collected for full sampling.
  • the undersampling strategy adopted in this embodiment requires The acquired readout line is indicated by the bold solid origin.
  • S102 Calculate and obtain a three-dimensional point spread function based on the three-dimensional undersampled data or the two-dimensional mapping data of the target object.
  • a 3D point spread function is used to correct the k-space sampling trajectory.
  • the 3D point spread function can be calculated based on 3D undersampled data.
  • the three-dimensional undersampled data can be calculated by the joint estimation method, and the three-dimensional point spread function can be obtained by iterative optimization.
  • the calculation of the three-dimensional point spread function can also be obtained by collecting two-dimensional mapping data and calculating.
  • the two-dimensional mapping data includes first two-dimensional mapping data, second two-dimensional mapping data, third two-dimensional mapping data, and fourth two-dimensional mapping data.
  • the first two-dimensional mapping data, the second two-dimensional mapping data, the third two-dimensional mapping data, and the fourth two-dimensional mapping data all have the same field of view as the three-dimensional undersampling data.
  • FIG. 10 is a sequence diagram of an embodiment of the second three-dimensional magnetic resonance imaging sequence provided by the present application
  • FIG. 11 is a sequence diagram of an embodiment of the third three-dimensional magnetic resonance imaging sequence provided by the present application
  • FIG. 12 is a sequence diagram of an embodiment of a fourth three-dimensional magnetic resonance imaging sequence provided by the present application
  • FIG. 13 is a sequence diagram of an embodiment of a fifth three-dimensional magnetic resonance imaging sequence provided by the present application.
  • the sequences in FIGS. 10-13 are for illustration only, and the present application is not limited thereto.
  • the first two-dimensional mapping data is collected based on the effect of the pulse corresponding to the second three-dimensional magnetic resonance imaging sequence on the target object; the second two-dimensional mapping data is collected based on the effect of the pulse corresponding to the third three-dimensional magnetic resonance imaging sequence on the target object.
  • the third two-dimensional mapping data is collected based on the action of the pulse corresponding to the fourth three-dimensional magnetic resonance imaging sequence on the target object; the fourth two-dimensional mapping data is based on the action of the pulse corresponding to the fifth three-dimensional magnetic resonance imaging sequence on the target object collected.
  • the phase direction of the second three-dimensional magnetic resonance imaging sequence includes the first sinusoidal gradient field and the first gradient field, as shown in FIG. 10 ; the phase direction of the third three-dimensional magnetic resonance imaging sequence includes the first gradient field and does not include the first gradient field.
  • a sinusoidal gradient field as shown in Figure 11.
  • the slice selection direction of the fourth three-dimensional magnetic resonance imaging sequence includes the second sinusoidal gradient field and the first gradient field, as shown in FIG. 12 ; the slice selection direction of the fifth three-dimensional magnetic resonance imaging sequence includes the first gradient field and does not include the first gradient field.
  • Two sinusoidal gradient fields as shown in Figure 13.
  • the gradient fields of the first gradient field and the seventh gradient field in the layer selection direction are the same, so that the accuracy of the trajectory correction of the three-dimensional low-resolution full sampling data based on the two-dimensional mapping data can be improved.
  • the timing diagrams of the first gradient field in FIGS. 10 and 12 are only for illustration, and the first gradient field may also be other gradient fields.
  • the time required to collect the first two-dimensional mapping data and the second two-dimensional mapping data is 2 ⁇ repetition time (TR) ⁇ number of phase encoding lines (Np); the third two-dimensional mapping data and the fourth two-dimensional mapping data are collected.
  • the time required for mapping the data is 2 ⁇ repetition time (TR) ⁇ number of coding lines of the selected layer (Ns). Since the above-mentioned mapping data collects two-dimensional data, the required scanning time is short, which can improve the scanning efficiency of the target object.
  • a two-dimensional point spread function in the phase direction can be obtained. Specifically, the first two-dimensional mapping data is divided by the second two-dimensional mapping data to obtain a two-dimensional point spread function in the phase direction.
  • the formula is expressed as follows:
  • waveP y (k x ,y) is the first two-dimensional mapping data of any point (k x ,y) in the phase direction
  • P y (k x ,y) is the first two-dimensional mapping data of any point (k x ,y) in the phase direction
  • Two-dimensional mapping data, PSF y (k x , y) is the point spread function value of any point (k x , y) in the phase two-dimensional point spread function PSF y .
  • the two-dimensional point spread function in the layer selection direction can be obtained. Specifically, the third two-dimensional mapping data is divided by the fourth two-dimensional mapping data to obtain a two-dimensional point spread function in the layer selection direction.
  • the formula is expressed as follows:
  • waveP z (k x ,z) is the third two-dimensional mapping data of any point (k x ,z) in the layer selection direction
  • P z (k x ,z) is any point in the layer selection direction (k x ,z)
  • the fourth two-dimensional mapping data of , PSF z (k x , z) is the point spread function value of any point (k x , z) in the two-dimensional point spread function PSF z of the layer selection direction.
  • the three-dimensional point spread function can be obtained based on the two two-dimensional point spread functions.
  • the formula is expressed as:
  • PSF yz (k x , y, z) is the three-dimensional point spread function value of any three-dimensional point (k x , y, z) in the three-dimensional point spread function PSF yz .
  • acquiring 2D mapping data in the phase direction and the slice selection direction can greatly reduce the time for mapping data acquisition, thereby reducing the time for MRI data acquisition.
  • S103 Calculate the sensitivity map of the target object based on the three-dimensional low-resolution full sampling data of the target object.
  • the fast parallel imaging technology with controllable aliasing is used to undersample the data. Aliasing caused by undersampling needs to be separated using a sensitivity map.
  • Sensitivity maps can be computed from 3D low-resolution fully sampled data.
  • three-dimensional low-resolution full sampling data of the target object acquired based on the sixth three-dimensional magnetic resonance imaging sequence is acquired.
  • the sensitivity map is then calculated based on the 3D low-resolution fully sampled data.
  • the sensitivity map is obtained, for example, by using the eigenvalue iterative self-stabilizing parallel imaging reconstruction technique to calculate the three-dimensional low-resolution full-sampled data.
  • the three-dimensional low-resolution full sampling data and the three-dimensional under-sampling data have the same field of view.
  • the sixth three-dimensional magnetic resonance imaging sequence may also be a fast spin echo sequence or a three-dimensional equilibrium steady-state free precession sequence, or the like.
  • S104 Perform image reconstruction on the three-dimensional undersampled data by using the three-dimensional point spread function and the sensitivity map to obtain a reconstructed magnetic resonance image.
  • the K-space trajectory is corrected by the 3D point spread function, and the reconstructed magnetic resonance image can be obtained by separating each layer image from the aliased image through the sensitivity map.
  • the MRI reconstructed image can be calculated by the following formula:
  • wave(x, y, z) is the three-dimensional undersampled data
  • M is the aliasing matrix based on 2D CAIPIRINHA
  • F x and is the one-dimensional Fourier transform and inverse transform along the readout direction
  • recon(x,y,z) is the reconstructed magnetic resonance image
  • PSF yz (k x ,y,z) is the three-dimensional point spread function
  • C(x, y, z) are sensitivity maps.
  • the above-mentioned method step sequence is an optional method step sequence of this embodiment. It can be understood that the acquisition sequence of the three-dimensional point spread function, the sensitivity map and the three-dimensional under-sampling data can be combined arbitrarily.
  • the wave controllable aliasing parallel imaging technology is applied to the first three-dimensional magnetic resonance imaging sequence, and the first sinusoidal gradient field is applied during the readout platform duration of the readout gradient field, and the first sinusoidal gradient field is
  • the 0-order moments of the gradient field and the second sinusoidal gradient field are both 0, which can accelerate the magnetic resonance scanning while reducing the first sinusoidal gradient field and the second sinusoidal gradient field within a repetition time.
  • the target object is based on the first magnetic resonance imaging. MRI signals generated by the sequence, thereby avoiding the introduction of additional artifacts in the reconstructed MRI images.
  • Fig. 14 is the 2x2 times acceleration test result of the phantom provided by this application.
  • 14a is a reconstructed image based on a fully sampled three-dimensional balanced steady-state free precession sequence
  • 14b is a reconstructed image based on wave-CAIPI technology applied to bSSFP sequence
  • Fig. 14c is obtained based on the magnetic resonance imaging method provided in this application Rebuild the image.
  • the wave-CAIPI technique is applied to the three-dimensional balanced steady-state free precession sequence.
  • FIG. 15 is the result of applying the magnetic resonance imaging method provided by the present application to the imaging results of a human brain in a three-dimensional balanced steady-state free precession sequence.
  • FIG. 15a is the reconstructed image of the human brain in coronal, sagittal and transverse views, and the corresponding residual map and g-factor map are shown in Fig. 15b and Fig. 15c, respectively. It can be seen from the results of human brain that the method proposed in this application can not only achieve high-speed accelerated scanning at high resolution, but also eliminate imaging artifacts caused by wave-CAIPI technology.
  • FIG. 16 is a schematic structural diagram of an embodiment of the magnetic resonance imaging apparatus provided by the present application.
  • the magnetic resonance imaging apparatus 100 of this embodiment may include a processor 101 and a memory 102 that are connected to each other.
  • the memory 102 is used to store the 3D undersampling data, the 2D mapping data and the sensitivity map of the target object acquired based on the first 3D magnetic resonance imaging sequence; wherein, the phase direction of the first 3D magnetic resonance imaging sequence has a first sinusoidal gradient field with a second sinusoidal gradient field in the slice selection direction, the durations of the first sinusoidal gradient field and the second sinusoidal gradient field are within the readout plateau duration of the readout gradient field applied in the readout direction, and the first sinusoidal gradient
  • the 0-order moment of the field and the second sinusoidal gradient field are both 0, the phase difference between the first sinusoidal gradient field and the second sinusoidal gradient field is ⁇ /2; the two-dimensional mapping data and the three-dimensional undersampled data have the same field of view.
  • the processor 101 is configured to obtain three-dimensional under-sampling data of the target object; calculate and obtain a three-dimensional point spread function based on the three-dimensional under-sampling data or two-dimensional mapping data; obtain a sensitivity map of the target object; The data is subjected to image reconstruction to obtain a reconstructed magnetic resonance image.
  • the processor 101 may be an integrated circuit chip, which has signal processing capability.
  • the processor 101 may also be a general purpose processor, digital signal processor (DSP), application specific integrated circuit (ASIC), field programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic device, discrete hardware components .
  • DSP digital signal processor
  • ASIC application specific integrated circuit
  • FPGA field programmable gate array
  • a general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
  • FIG. 17 is a schematic structural diagram of an embodiment of the computer storage medium provided by the present application.
  • a computer program 201 is stored in the computer storage medium 200 of this embodiment, which can be executed to implement the methods in the above-mentioned embodiments.
  • the computer storage medium 200 in this embodiment may be a medium that can store program instructions, such as a U disk, a removable hard disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a magnetic disk, or an optical disk.
  • program instructions such as a U disk, a removable hard disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a magnetic disk, or an optical disk.
  • the server can send the stored program instructions to other devices to run, or can also run the stored program instructions by itself.
  • the disclosed method and apparatus may be implemented in other manners.
  • the apparatus implementations described above are only illustrative, for example, the division of modules or units is only a logical function division, and there may be other divisions in actual implementation, for example, multiple units or components may be combined or Can be integrated into another system, or some features can be ignored, or not implemented.
  • the shown or discussed mutual coupling or direct coupling or communication connection may be through some interfaces, indirect coupling or communication connection of devices or units, and may be in electrical, mechanical or other forms.
  • Units described as separate components may or may not be physically separated, and components shown as units may or may not be physical units, that is, may be located in one place, or may be distributed to multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution in this implementation manner.
  • each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically alone, or two or more units may be integrated into one unit.
  • the above-mentioned integrated units may be implemented in the form of hardware, or may be implemented in the form of software functional units.
  • the integrated unit if implemented as a software functional unit and sold or used as a stand-alone product, may be stored in a computer-readable storage medium.
  • the technical solutions of the present application can be embodied in the form of software products in essence, or the parts that contribute to the prior art, or all or part of the technical solutions, and the computer software products are stored in a storage medium , including several instructions to make a computer device (which may be a personal computer, a server, or a network device, etc.) or a processor (processor) to execute all or part of the steps of the methods of the various embodiments of the present application.
  • the aforementioned storage medium includes: U disk, mobile hard disk, Read-Only Memory (ROM, Read-Only Memory), Random Access Memory (RAM, Random Access Memory), magnetic disk or optical disk and other media that can store program codes .

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Abstract

本申请公开了一种磁共振成像方法、装置及计算机存储介质。所述方法包括：获取基于第一三维磁共振成像序列采集的目标对象的三维欠采样数据；其中，第一三维磁共振成像序列在相位方向具有第一正弦梯度场，在选层方向具有第二正弦梯度场，且第一正弦梯度场和第二正弦梯度场的0阶矩均为0，第一正弦梯度场与第二正弦梯度场的相位相差π/2；基于三维欠采样数据或目标对象的二维映射数据计算得到三维点扩散函数；基于目标对象的三维低分辨率全采样数据计算得到目标对象的灵敏度图；使用三维点扩散函数、灵敏度图对三维欠采样数据进行图像重建，得到重建磁共振图像。通过上述方式，本申请能够高速加倍扫描的同时避免重建磁共振图像中伪影的产生。

Description

磁共振成像方法、装置及计算机存储介质 【技术领域】
本申请涉及图像处理技术领域，特别是涉及一种磁共振成像方法、磁共振成像装置及计算机存储介质。
【背景技术】
磁共振成像(MRI,Magnetic Resonance Imaging)技术由于其无辐射、分辨率高等优点被广泛的应用于临床医学与医学研究。
磁共振成像扫描速度慢，过长的扫描时间在引起病患不适的同时，容易在重建磁共振图像中引入运动伪影，从而影响重建磁共振图像质量，如何加快磁共振成像的速度一直是研究热点和难点。
近年来，并行成像技术的提出极大地减少了磁共振的扫描时间，如整体自动校准部分并行采集技术(Generalized Autocalibrating Partially Parallel Acquisitions，GRAPPA)和灵敏度编码技术(Sensitivity Encoding，SENSE)和波浪可控混叠并行成像技术(wave Controlled Aliasing In Parallel Imaging，wave-CAIPI)等，此类快速成像技术均利用接收线圈在空间中的灵敏度差异对欠采样数据进行重建，从而替代了一部分梯度编码。但是，该方法得到的重建图像的信噪比随加速倍数的增加而下降，以及重建磁共振图像中存在混叠伪影等问题。
【发明内容】
为解决上述技术问题，本申请提供一种磁共振成像方法。该方法包括：获取基于第一三维磁共振成像序列采集的目标对象的三维欠采样数据；其中，第一三维磁共振成像序列在相位方向具有第一正弦梯度场，在选层方向具有第二正弦梯度场，第一正弦梯度场和第二正弦梯度场的持续时间在读出方向施加的读出梯度场的读出平台持续时间内，且第一正弦梯度场和第二正弦梯度场的0阶矩均为0，第一正弦梯度场与第二正弦梯度场的相位相差π/2；基于三维欠采样数据或目标对象的二维映射数据计算得到三维点扩散函数；其中，二维映射数据与三维欠采样数 据的视野相同；基于目标对象的三维低分辨率全采样数据计算得到目标对象的灵敏度图；使用三维点扩散函数、灵敏度图对三维欠采样数据进行图像重建，得到重建磁共振图像。
为解决上述技术问题，本申请提供一种磁共振成像装置。该装置包括处理器和存储器，处理器耦接存储器，在工作时执行指令，以配合存储器实现上述的磁共振成像方法。
为解决上述技术问题，本申请提供一种计算机存储介质。计算机存储介质存储有计算机程序，计算机程序能够被处理器执行以实现上述的磁共振成像方法。
本申请通过在第一三维磁共振成像序列中的相位方向施加有第一正弦梯度场、在选层方向施加有第二正弦梯度场，第一正弦梯度场和第二正弦梯度场的施加时间在读出方向施加的读出梯度场的读出平台持续时间内，且第一正弦梯度场和第二正弦梯度场的0阶矩均为0，从而不影响在一个重复时间内目标对象基于第一三维磁共振成像序列所产生的信号。并且，采集目标对象的三维欠采样数据，能够加快对目标对象的扫描速度。基于二维映射数据计算三维点扩散函数，进一步能够减少对目标对象的扫描时间，提高成像效率。
【附图说明】
图1是本申请提供的磁共振成像方法第一实施例的流程示意图；
图2是本申请提供的第一三维磁共振成像序列的一实施例的时序图；
图3是本申请提供的第一正弦梯度场和第二正弦梯度场的一实施方式的时序图；
图4是本申请提供的第一正弦梯度场和第二正弦梯度场的另一实施方式的时序图；
图5是本申请提供的第一正弦梯度场和第二正弦梯度场的又一实施方式的时序图；
图6是本申请提供的第一正弦梯度场和第二正弦梯度场的再一实施方式的时序图；
图7是本申请提供的第一正弦梯度场和第二正弦梯度场的再一实施方式的时序图；
图8是本申请提供的第一正弦梯度场和第二正弦梯度场的再一实施方式的时序图；
图9是本申请提供的可控混叠的快速并行成像技术对磁共振信号进行欠采样的示意图；
图10是本申请提供的第二三维磁共振成像序列一实施方式的时序图；
图11是本申请提供的第三三维磁共振成像序列一实施方式的时序图；
图12是本申请提供的第四三维磁共振成像序列一实施方式的时序图；
图13是本申请提供的第五三维磁共振成像序列一实施方式的时序图；
图14是本申请提供的仿体2×2倍加速测试结果；
图15为本申请提供的磁共振成像方法应用于三维平衡稳态自由旋进序列中人脑成像结果；
图16是本申请提供的磁共振成像装置一实施例的结构示意图；
图17是本申请提供的计算机存储介质一实施例的结构示意图。
【具体实施方式】
为使本领域的技术人员更好地理解本申请的技术方案，下面结合附图和具体实施方式对本申请所提供的磁共振成像方法、磁共振成像装置及计算机存储介质做进一步详细描述。
磁共振并行成像方法是一类加速MRI扫描速度的方法，如灵敏度编码技术(SENSE,sensitivity encoding)和整体自动校准部分并行采集技术(GRAPPA,generalized autocalibrating partially parallel acquisitions)等。该类方法通过减少采集的数据量，并利用多通道线圈所包含的冗余信息对三维欠采样数据进行重建，从而到达快速扫描的目的。
波浪可控混叠并行成像技术(wave-CAIPI,wave Controlled Aliasing In Parallel Imaging)是一种用于加快三维磁共振扫描速度的并行成像技术，该技术在MRI信号采集的同时(施加读出梯度场的同时)，利用MRI梯度线圈在选层和相位方向分别施加相位差为π/2的正弦梯度场，并采用可控混叠的快速并行成像技术(2D CAIPIRINHA,two-dimension Controlled Aliasing In Parallel Imaging Results In Higher Acceleration)对数据进行欠采样，使得欠采样所导致的混叠伪影沿读出、选层和相位方向进行分散，降低各像素点中图像混叠伪影的程度，从而极大的降低了并行成像重建中的几何因子(g-factor,geometry factor)信噪比丢失，达到高倍加速的目的。目前，wave-CAIPI技术已被应用到快速自旋回波(TSE,Turbo Spin Echo)、磁化准备快速梯度回波(MP-RAGE,Magnetization-Prepared RApid Gradient Echo)和短磁化矢量可视化(ViSTa,Visualization of Short Transverse relaxation time component)等序列当中，实现了高加速倍数和高分辨率的三维MRI成像。
Wave-CAIPI技术能够将混叠伪影更为均为的分散到整个成像视野(FOV,Field-Of-View)中，从而降低g-factor信噪比丢失，达到高倍加速扫描的目的。而所施加的正弦梯度场在选层或相位方向的0阶矩不为零，会扰乱MRI序列原有的信号，导致伪影的产生。
为解决上述问题，本申请提供如下实施例：
请参阅图1，图1是本申请提供的磁共振成像方法第一实施例的流程示意图。本实施例包括如下步骤：
S101：获取基于第一三维磁共振成像序列采集的目标对象的三维欠采样数据。
其中，第一三维磁共振成像序列是指利用波浪梯度可控混叠并行成像技术对第七三维磁共振成像序列进行调整得到的。
具体地，在第七三维磁共振成像序列的基础上，第一三维磁共振成像序列在相位方向还包括第一正弦梯度场，在选层方向还包括第二正弦梯度场。即，核磁共振***基于第一三维磁共振成像序列向目标对象发出射频脉冲和梯度脉冲，相当于核磁共振***即基于向目标对象发出第 七三维磁共振成像序列的射频脉冲和梯度脉冲，又向目标对象发出第一正弦梯度场和第二正弦梯度场。
第一正弦梯度场和第二正弦梯度场的持续时间在读出方向施加的读出梯度场的读出平台持续时间内，并且第一正弦梯度场和第二正弦梯度场的0阶矩均为0。因此，不影响在一个重复时间内目标对象基于第七三维磁共振成像序列所产生的信号，从而不会引入额外的伪影。
本实施例中，第七三维磁共振成像序列可以是三维平衡稳态自由旋进(balanced Steady-State Free Precession，bSSFP)序列、三维梯度回波(Gradient Echo，GRE)序列、快速自旋回波(Turbo Spin Echo，TSE)序列、磁化准备快速梯度回波(Magnetization-Prepared RApid Gradient Echo，MP-RAGE)序列或短磁化矢量可视化(Visualization of Short Transverse relaxation time component，ViSTa)序列等，本申请对此不做限制。
示例性地，请参阅图2，图2是本申请提供的第一三维磁共振成像序列的一实施例的时序图。其中，第七三维磁共振成像序列为bSSFP序列。
本实施例中，第一正弦梯度场和第二正弦梯度场的0阶矩均为0是指第一三维磁共振成像序列中，第一正弦梯度场与时间轴形成的多个封闭区域中，位于时间轴上方的封闭区域的面积与位于时间轴下方的封闭区域的面积相等；第二正弦梯度场同理。
在相位方向施加第一正弦梯度场的第一持续时间为整数倍的正弦周期，例如1倍、2倍、5倍、10倍等。在选层方向施加第二正弦梯度场的第二持续时间也为整数倍的正弦周期，例如1倍、2倍、5倍、10倍或20倍等。第一持续时间和第二持续时间小于或等于读出梯度场的读出平台持续时间D R。第一持续时间可以小于第二持续时间，且第一持续时间和第二持续时间可根据读出梯度场的读出平台持续时间、正弦周期进行调整，本申请对此不做限制。
进一步地，第一正弦梯度场与第二正弦梯度场的正弦频率相同，第一正弦梯度场与第二正弦梯度场的相位相差π/2。
第一正弦梯度场的第一施加时间可以早于第二正弦梯度场的第二 施加时间奇数倍的四分之一正弦周期，例如1倍、3倍、5倍或7倍等。也即第一施加时间可以早于第二施加时间四分之一正弦周期、四分之三正弦周期、四分之五正弦周期或四分之七正弦周期等。当然，第一施加时间也可以晚于第二施加时间奇数倍的四分之一正弦周期。
第一正弦梯度场和第二正弦梯度场的形式有多种，请参阅图3-图8，图3是本申请提供的第一正弦梯度场和第二正弦梯度场的一实施方式的时序图；图4是本申请提供的第一正弦梯度场和第二正弦梯度场的另一实施方式的时序图；图5是本申请提供的第一正弦梯度场和第二正弦梯度场的又一实施方式的时序图；图6是本申请提供的第一正弦梯度场和第二正弦梯度场的再一实施方式的时序图；图7是本申请提供的第一正弦梯度场和第二正弦梯度场的再一实施方式的时序图；图8是本申请提供的第一正弦梯度场和第二正弦梯度场的再一实施方式的时序图。图3-图8中第一施加时间、第二施加时间以及第一正弦梯度场和第二正弦梯度场的正弦周期数量仅是示意性的，本申请不限于此。
可以理解，本实施例中第一正弦梯度场和第二正弦梯度场可以为正弦梯度场或余弦梯度场经过相位移动、截断及其组合等操作得到的，如图3-图8中中第一正弦梯度场所示。例如图5中，第一正弦梯度场可以看做是将余弦波截断半个周期(-π/4～π/4)得到的，也即第一正弦梯度场初始施加方向与第二正弦梯度场的初始施加方向相反。
可以使用公式表示第一正弦梯度场和第二正弦梯度场，本实施例以图3为例。
第一正弦梯度场公式表示如下：
Figure PCTCN2020107359-appb-000001
第二正弦梯度场公式表示如下：
Figure PCTCN2020107359-appb-000002
其中，t为时间，A为正弦梯度场幅度值，D C为一个正弦周期的持 续时间，D R为读出梯度场的读出平台持续时间。a为正奇数，b为正自然数，c为正自然数，d为正自然数，那么bD C为第一持续时间，dD C为第二持续时间，bD C与cD C均小于D R。t＝0为读出平台的开始时间，此处表示原点。
在第一正弦梯度场和第二正弦梯度场的作用下，读出的K空间轨迹就是沿读出方向的螺旋形式。如此可以理解为施加了一个三维点扩散函数，使目标对象的每个体素沿着读出方向产生扩散，因而在并行成像采得图像的混叠部分，混叠体素之间的线圈敏感度差异也增大，从而使得重建时g因子达到一个极接近于1的水平，能够减少噪声的放大。在读出梯度场的读出平台持续时间内施加第一正弦梯度场且第一正弦梯度场和第二正弦梯度场的0阶矩均为0，能够消除第一正弦梯度场和第二正弦梯度场在一个重复时间内对目标对象基于第一磁共振成像序列产生的磁共振信号的干扰，从而避免在重建磁共振图像中引入额外的伪影。
进一步地，波浪梯度可控混叠快速并行成像技术在传统多层同时激发的基础上，使用数据欠采样策略在目标对象基于第一三维磁共振成像序列产生的磁共振信号进行欠采样，得到三维欠采样数据。数据欠采样策略也即保持K空间覆盖范围不变，而增大相邻相位编码线和相邻选层编码线之间的距离。K空间中增加相位编码间隔和增加选层编码间隔意味着在图像域中缩小了成像视野，即降采样后的K空间直接反傅里叶变换到图像域，将会出现图像的混叠。这些混叠伪影需要由后续的重建算法去除，例如使用灵敏度图对三维欠采样数据进行重建，详细内容将在后续步骤中进行描述。
数据欠采样策略可以是可控混叠的快速并行成像技术、并行成像中灵敏度编码技术或整体自动校准部分并行采集技术等，本申请对此不做限制。
本实施例以可控混叠的快速并行成像技术(Two-Dimension Controlled Aliasing In Parallel Imaging Results In Higher Acceleration，2D CAIPIRINHA)对磁共振信号欠采样为例进行说明。不同于传统并行成像方法的数据采集策略，可控混叠的快速并行成像技术能够将欠采样所 导致的混叠同时分散到相位和选层方向，更有效的利用了视野中的背景区域，增大了混叠像素点间的灵敏度差异，从而达到降低几何因子和减少重建伪影的目的。
示例性地，请参阅图9，图9是本申请提供的可控混叠的快速并行成像技术对磁共振信号进行欠采样的示意图。图9中，垂直于本平面方向(同时垂直于相位方向和选层方向)为读出方向，黑色虚线交点为全采样所需采集的读出线，本实施例所采用的欠采样策略所需采集的读出线由加粗实心原点表示。图7所示为2×2倍欠采样(相位方向2倍欠采样，选层方向2倍欠采样)，总加速倍数为4，所需采集时间＝重复时间(TR)×相位编码线数(Np)×选层编码线数(Ns)/4。
S102：基于三维欠采样数据或目标对象的二维映射数据计算得到三维点扩散函数。
三维点扩散函数用于对K空间采样轨迹进行校正。
计算三维点扩散函数的方法有多种，例如可以基于三维欠采样数据计算得到。具体可以是通过联合估计法对三维欠采样数据进行计算，迭代优化得到三维点扩散函数。
计算三维点扩散函数还可以是通过采集二维映射数据并计算得到。
其中，二维映射数据包括第一二维映射数据、第二二维映射数据、第三二维映射数据以及第四二维映射数据。第一二维映射数据、第二二维映射数据、第三二维映射数据以及第四二维映射数据均与三维欠采样数据的视野相同。
请参阅图10-图13，图10是本申请提供的第二三维磁共振成像序列一实施方式的时序图；图11是本申请提供的第三三维磁共振成像序列一实施方式的时序图；图12是本申请提供的第四三维磁共振成像序列一实施方式的时序图；图13是本申请提供的第五三维磁共振成像序列一实施方式的时序图。图10-图13中的序列仅作为示意，本申请不限于此。
第一二维映射数据是基于第二三维磁共振成像序列对应的脉冲对目标对象作用采集到的；第二二维映射数据是基于第三三维磁共振成像 序列对应的脉冲对目标对象作用采集到的；第三二维映射数据是基于第四三维磁共振成像序列对应的脉冲对目标对象作用采集到的；第四二维映射数据是基于第五三维磁共振成像序列对应的脉冲对目标对象作用采集到的。
其中，第二三维磁共振成像序列的相位方向包括第一正弦梯度场和第一梯度场，如图10所示；第三三维磁共振成像序列的相位方向包括第一梯度场，且不包括第一正弦梯度场，如图11所示。第四三维磁共振成像序列的选层方向包括第二正弦梯度场和第一梯度场，如图12所示；第五三维磁共振成像序列的选层方向包括第一梯度场，且不包括第二正弦梯度场，如图13所示。并且，第一梯度场与第七梯度场的选层方向的梯度场相同，如此能够提高基于二维映射数据对三维低分辨率全采样数据轨迹矫正的准确度。当然，图10和图12中第一梯度场的时序图仅作为示意，第一梯度场还可以是其他梯度场。
综上，采集第一二维映射数据和第二二维映射数据所需时间共为2×重复时间(TR)×相位编码线数(Np)；采集第三二维映射数据和第四二维映射数据所需时间共为2×重复时间(TR)×选层编码线数(Ns)。由于上述映射数据所采集的是二维数据，因此所需扫描时间较短，能够提高对目标对象的扫描效率。
基于相位方向上的第一二维映射数据和第二二维映射数据，可以求取相位方向的二维点扩散函数。具体地，将第一二维映射数据除以第二二维映射数据，得到相位方向的二维点扩散函数。公式表示如下：
PSF y(k x,y)＝waveP y(k x,y)/P y(k x,y)
其中，waveP y(k x,y)为相位方向任意点(k x,y)的第一二维映射数据，P y(k x,y)为相位方向任意点(k x,y)的第二二维映射数据，PSF y(k x,y)为相位二维点扩散函数PSF y中任意点(k x,y)的点扩散函数值。
基于选层方向上的第三二维映射数据和第四二维映射数据，可以求取选层方向的二维点扩散函数。具体地，将第三二维映射数据除以第四二维映射数据，得到选层方向的二维点扩散函数。公式表示如下：
PSF z(k x,z)＝waveP z(k x,z)/P z(k x,z)
其中，waveP z(k x,z)为选层方向任意点(k x,z)的第三二维映射数据，P z(k x,z)为选层方向任意点(k x,z)的第四二维映射数据，PSF z(k x,z)为选层方向的二维点扩散函数PSF z中任意点(k x,z)的点扩散函数值。
在相位二维点扩散函数和选层二维点扩散函数确定后，基于这两个二维点扩散函数可以求取三维点扩散函数。公式表示为：
PSF yz(k x,y,z)＝PSF z(k x,z)·PSF y(k x,y)
其中，PSF yz(k x,y,z)为三维点扩散函数PSF yz中任意三维点(k x,y,z)的三维点扩散函数值。
相较于通过三维映射数据确定三维点扩散函数，采集相位方向和选层方向上的二维映射数据可以大大降低映射数据采集的时间，进而减少磁共振成像数据采集时间。
S103：基于目标对象的三维低分辨率全采样数据计算得到目标对象的灵敏度图。
为了加快磁共振图像的数据采集速度，本实施例采用可控混叠的快速并行成像技术对数据进行欠采样。由欠采样所导致的混叠，需要利用灵敏度图进行分离。
灵敏度图可以通过三维低分辨率全采样数据计算得到。
具体地，获取基于第六三维磁共振成像序列采集的目标对象的三维低分辨率全采样数据。然后基于三维低分辨率全采样数据计算得到灵敏度图。灵敏度图例如是使用特征值迭代自稳定并行成像重建技术对三维低分辨率全采样数据进行计算得到的。
其中，三维低分辨率全采样数据与三维欠采样数据的视野相同。
当然，第六三维磁共振成像序列还可以是快速自旋回波序列或三维平衡稳态自由旋进序列等。
S104：使用三维点扩散函数、灵敏度图对三维欠采样数据进行图像重建，得到重建磁共振图像。
通过三维点扩散函数对三维欠采数据进行K空间轨迹的校正，通过灵敏度图将每一层图像从混叠图像中分离出来可得到重建磁共振图像。磁共振重建图像可由以下公式计算得到：
Figure PCTCN2020107359-appb-000003
其中，wave(x,y,z)为三维欠采样数据，M为基于2D CAIPIRINHA的混叠矩阵，F x和
Figure PCTCN2020107359-appb-000004
为沿读出方向的一维傅里叶变换和逆变换，recon(x,y,z)为重建磁共振图像，PSF yz(k x,y,z)为三维点扩散函数，C(x,y,z)为灵敏度图。
上述方法步骤顺序为本实施例的可选方法步骤顺序，可以理解的是，三维点扩散函数、灵敏度图和三维欠采数据的获取顺序可以任意组合。
本实施例中，通过将波浪可控混叠并行成像技术应用于第一三维磁共振成像序列中，并在读出梯度场的读出平台持续时间内施加第一正弦梯度场，且第一正弦梯度场和第二正弦梯度场的0阶矩均为0，能够加速磁共振扫描的同时，降低第一正弦梯度场和第二正弦梯度场在一个重复时间内对目标对象基于第一磁共振成像序列产生的磁共振信号的干扰，从而避免在重建磁共振图像中引入额外的伪影。
为证实本申请的技术方案的可行性和技术效果，在3T磁共振***(MAGNETOM,Siemens AG,Erlangen,Germany)上对进行了仿体和人脑测试。
请参阅图14，图14是本申请提供的仿体2×2倍加速测试结果。图14中，14a为基于全采样三维平衡稳态自由旋进序列的重建图像；14b为基于wave-CAIPI技术应用于bSSFP序列的重建图像；图14c为基于本申请提供的磁共振成像方法得到的重建图像。共同的扫描参数为：回波时间＝3.23ms，重复时间＝6.45ms，翻转角＝30°，带宽＝300Hz/pixel，体素尺寸＝1×1×1mm3，扫描矩阵尺寸＝160×160×72。wave-CAIPI技术应用于三维平衡稳态自由旋进序列的选层方向的正弦梯度场周期数量＝11、相位方向的正弦梯度场周期数量＝11.5、幅度值＝6mT/m，加速倍数＝2×2；本申请提供的磁共振成像方法中，第一正弦梯度场的正弦周期数量＝10、第二正弦梯度场的正弦周期数量＝11、幅度值＝6mT/m，加速倍数＝2×2。可以看到wave-CAIPI技术用于加速bSSFP序列时会引入严重的带状伪影，而利用申请提供的0阶矩为0的第一征正弦梯度场和第二正弦梯度 场加速bSSFP序列时没有伪影产生。
请参阅图15，图15为本申请提供的磁共振成像方法应用于三维平衡稳态自由旋进序列中人脑成像结果，扫描参数如下：回波时间＝3.36ms，重复时间＝6.72ms，翻转角＝30°，带宽＝299Hz/pixel，体素尺寸＝0.8×0.8×0.8mm3，扫描矩阵尺寸＝288×288×240，第一正弦梯度场的周期数量＝4，第二正弦梯度场周期数量＝5、幅度值＝12.5mT/m，加速倍数＝4×3。其中，图15a为冠状位、矢状位和横断位的人脑重建图像，其对应的残差图和g-factor分之一图分别显示与图15b和图15c中。由人脑结果可知，本申请所提出方法不仅能够在实现高分辨率下的高倍加速扫描，同时消除了wave-CAIPI技术所导致的成像伪影。
上述磁共振成像方法的实施例由磁共振成像装置实现，因而本申请还提出磁共振成像装置，请参阅图16，图16是本申请提供的磁共振成像装置一实施例的结构示意图。本实施例磁共振成像装置100可以包括相互连接的处理器101和存储器102。其中，存储器102用于存储基于第一三维磁共振成像序列采集的目标对象的三维欠采样数据、二维映射数据以及灵敏度图；其中，第一三维磁共振成像序列的相位方向具有第一正弦梯度场，在选层方向具有第二正弦梯度场，第一正弦梯度场和第二正弦梯度场的持续时间在读出方向施加的读出梯度场的读出平台持续时间内，且第一正弦梯度场和第二正弦梯度场的0阶矩均为0，第一正弦梯度场与第二正弦梯度场的相位相差π/2；二维映射数据与三维欠采样数据的视野相同。处理器101用于获取目标对象的三维欠采样数据；基于三维欠采样数据或二维映射数据计算得到三维点扩散函数；获取目标对象的灵敏度图；使用三维点扩散函数、灵敏度图对三维欠采样数据进行图像重建，得到重建磁共振图像。
其中，处理器101可以是一种集成电路芯片，具有信号的处理能力。处理器101还可以是通用处理器、数字信号处理器(DSP)、专用集成电路(ASIC)、现场可编程门阵列(FPGA)或者其他可编程逻辑器件、分立门或者晶体管逻辑器件、分立硬件组件。通用处理器可以是微处理器或者该处理器也可以是任何常规的处理器等。
对于上述实施例的方法，其可以计算机程序的形式存在，因而本申请提出一种计算机存储介质，请参阅图17，图17是本申请提供的计算机存储介质一实施例的结构示意图。本实施例计算机存储介质200中存储有计算机程序201，其可被执行以实现上述实施例中的方法。
本实施例计算机存储介质200可以是U盘、移动硬盘、只读存储器(ROM，Read-Only Memory)、随机存取存储器(RAM，Random Access Memory)、磁碟或者光盘等可以存储程序指令的介质，或者也可以为存储有该程序指令的服务器，该服务器可将存储的程序指令发送给其他设备运行，或者也可以自运行该存储的程序指令。
在本申请所提供的几个实施例中，应该理解到，所揭露的方法和装置，可以通过其它的方式实现。例如，以上所描述的装置实施方式仅仅是示意性的，例如，模块或单元的划分，仅仅为一种逻辑功能划分，实际实现时可以有另外的划分方式，例如多个单元或组件可以结合或者可以集成到另一个***，或一些特征可以忽略，或不执行。另一点，所显示或讨论的相互之间的耦合或直接耦合或通信连接可以是通过一些接口，装置或单元的间接耦合或通信连接，可以是电性，机械或其它的形式。
作为分离部件说明的单元可以是或者也可以不是物理上分开的，作为单元显示的部件可以是或者也可以不是物理单元，即可以位于一个地方，或者也可以分布到多个网络单元上。可以根据实际的需要选择其中的部分或者全部单元来实现本实施方式方案的目的。
另外，在本申请各个实施例中的各功能单元可以集成在一个处理单元中，也可以是各个单元单独物理存在，也可以两个或两个以上单元集成在一个单元中。上述集成的单元既可以采用硬件的形式实现，也可以采用软件功能单元的形式实现。
集成的单元如果以软件功能单元的形式实现并作为独立的产品销售或使用时，可以存储在一个计算机可读取存储介质中。基于这样的理解，本申请的技术方案本质上或者说对现有技术做出贡献的部分或者该技术方案的全部或部分可以以软件产品的形式体现出来，该计算机软件 产品存储在一个存储介质中，包括若干指令用以使得一台计算机设备(可以是个人计算机，服务器，或者网络设备等)或处理器(processor)执行本申请各个实施方式方法的全部或部分步骤。而前述的存储介质包括：U盘、移动硬盘、只读存储器(ROM，Read-Only Memory)、随机存取存储器(RAM，Random Access Memory)、磁碟或者光盘等各种可以存储程序代码的介质。
以上所述仅为本申请的实施方式，并非因此限制本申请的专利范围，凡是利用本申请说明书及附图内容所作的等效结构或等效流程变换，或直接或间接运用在其他相关的技术领域，均同理包括在本申请的专利保护范围内。

Claims (10)

  1. 一种磁共振成像方法，其特征在于，所述方法包括：
    获取基于第一三维磁共振成像序列采集的目标对象的三维欠采样数据；其中，所述第一三维磁共振成像序列在相位方向具有第一正弦梯度场，在选层方向具有第二正弦梯度场，所述第一正弦梯度场和所述第二正弦梯度场的持续时间在读出方向施加的读出梯度场的读出平台持续时间内，且所述第一正弦梯度场和所述第二正弦梯度场的0阶矩均为0，所述第一正弦梯度场与所述第二正弦梯度场的相位相差π/2；
    基于所述三维欠采样数据或所述目标对象的二维映射数据计算得到三维点扩散函数；其中，所述二维映射数据与所述三维欠采样数据的视野相同；
    基于所述目标对象的三维低分辨率全采样数据计算得到所述目标对象的灵敏度图；
    使用所述三维点扩散函数、所述灵敏度图对所述三维欠采样数据进行图像重建，得到重建磁共振图像。
  2. 根据权利要求1所述的方法，其特征在于，所述第一正弦梯度场与所述第二正弦梯度场的正弦频率相同。
  3. 根据权利要求1所述的方法，其特征在于，所述二维映射数据包括基于第二三维磁共振成像序列采集到的所述目标对象的第一二维映射数据、基于第三三维磁共振成像序列采集到的所述目标对象的第二二维映射数据、基于第四三维成像序列采集到的所述目标对象的第三二维映射数据，以及基于第五三维成像序列采集到的所述目标对象的第四二维映射数据；其中，所述第二三维磁共振成像序列的相位方向包括所述第一正弦梯度场和第一梯度场，所述第三三维磁共振成像序列的相位方向包括所述第一梯度场，所述第四三维磁共振成像序列的选层方向包括所述第二正弦梯度场和所述第一梯度场，所述第五三维磁共振成像序列的选层方向包括所述第一梯度场；
    所述基于所述目标对象的二维映射数据计算得到三维点扩散函数，包括：
    将所述第一二维映射数据除以所述第二二维映射数据，得到相位方向的二维点扩散函数；
    将所述第三二维映射数据除以所述第四二维映射数据，得到选层方向的二维点扩散函数；
    基于所述相位方向的二维点扩散函数和所述选层方向的二维点扩散函数， 得到所述三维点扩散函数。
  4. 根据权利要求1所述的方法，其特征在于，所述获取所述目标对象的灵敏度图，包括：
    获取基于第六三维磁共振成像序列采集的所述目标对象的低分辨率三维全采样数据，所述低分辨率三维全采样数据与所述三维欠采样数据的所述视野相同；
    基于所述低分辨率三维全采样数据计算得到所述灵敏度图。
  5. 根据权利要求4所述的方法，其特征在于，所述基于所述低分辨率三维全采样数据计算得到所述灵敏度图，包括：
    使用特征值迭代自稳定并行成像重建技术对所述低分辨率三维全采样数据进行计算，得到所述灵敏度图。
  6. 根据权利要求4所述的方法，其特征在于，所述第六三维磁共振成像序列为三维梯度回波序列、快速自旋回波序列或三维平衡稳态自由旋进序列。
  7. 根据权利要求1所述的方法，其特征在于，所述三维欠采样数据是使用数据欠采样策略对所述目标对象基于所述第一三维磁共振成像序列产生的磁共振信号进行采集的，所述数据欠采样策略为可控混叠的快速并行成像技术、并行成像中灵敏度编码技术或整体自动校准部分并行采集技术。
  8. 根据权利要求1所述的方法，其特征在于，所述第一三维磁共振成像序列是通过在第七三维磁共振成像序列的基础上，在相位方向施加所述第一正弦梯度场，在选层方向施加所述第二正弦梯度场后得到的，所述第七三维磁共振成像序列为三维平衡稳态自由旋进序列、三维梯度回波序列、快速自旋回波序列、磁化准备快速梯度回波序列、磁化强度预备梯度回波序列或短磁化矢量可视化序列。
  9. 一种磁共振成像装置，其特征在于，所述装置包括处理器和存储器，所述处理器耦接所述存储器，在工作时执行指令，以配合所述存储器实现如权利要求1至8任一项所述的磁共振成像方法。
  10. 一种计算机存储介质，其特征在于，所述计算机存储介质存储有计算机程序，所述计算机程序能够被处理器执行以实现如权利要求1至8中任一项所述的磁共振成像方法。
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