Reconstruction of MR images using Wave-Caipi

Abstract

Method (S0-S7) for MR-based reconstruction of images of a patient in which monitoring (S0) whether a value of a patient's movement during an MR recording in at least one direction of movement exceeds a respective threshold value (S1), and, If this is not the case, an image reconstruction, in particular using a Wave-CAIPI method, is carried out on the basis of identical calibrated PSF subfunctions for all k-space lines (S2-S3), while if this is the case, - multiple bins (B 0.0 -B 3.3 ; B -i / +j ) are provided (S4), the successive value ranges of the patient movement in at least one direction of movement (x, y; θ z ) are equivalent to, - the k-space lines to the bins (B 0.0 -B 3.3 ; B -i / +j ) based on a movement value (Δx, Δy; θ z) (S5), - for at least two bins (B 0.0 -B 3.3 ; B -i / +j ) a calibration of PSF subfunctions is carried out on the basis of the k-space lines assigned to these bins (S6) and - an image reconstruction, in particular by means of a Wave-CAIPI method, is carried out in such a way that for the respective k-space lines the bins (B 0.0 -B 3.3 ; B -i / +j ) associated PSF subfunctions can be used (S7).

Description

[0001] The invention relates to a method for MR-based reconstruction of images of a patient, in which image reconstruction is performed using a wave-CAIPI method based on identical calibrated PSF subfunctions for all k-space lines. The invention further relates to an MR system configured to perform the method.

[0002] In medical technology, magnetic resonance imaging (MRI), also known as magnetic resonance tomography (MRI), is characterized by high soft tissue contrast. During an MRI scan, high-frequency excitation pulses are radiated into a patient using an MRI scanner. This triggers magnetic resonance signals in the patient. The magnetic resonance signals are received as measurement data, for example, in the form of k-space lines, by one or more MRI antennas and used to reconstruct images.

[0003] Various MR imaging techniques are known. For example, F. Breuer et al., "Controlled Aliasing in Parallel Imaging Results in Higher Acceleration (CAIPIRINHA)" (MAGNETOM Flash 1 / 2012, pages 135 to 142), provides a brief introduction to the so-called CAIPIRINHA imaging technique.

[0004] B. Bilgic et al., “Wave-CAIPI for Highly Accelerated 3D Imaging,” Magnetic Resonance in Medicine 73: 2152-2162 (2015) and Stephen F. Cauley et al., “Autocalibrated Wave-CAIPI Reconstruction; Joint Optimization of k-Space Trajectory and Parallel Imaging Reconstruction,” Magnetic Resonance in Medicine 78: 1093-1099 (2017), describe the so-called “Wave-CAIPI” technique, which enables higher acceleration factors compared to other parallel imaging techniques by using coil sensitivity profiles in all spatial directions during an image reconstruction process. This spreading is achieved by incorporating modulated phase-encoding gradient waveforms during the readout gradient (see, for example, Cauley, Fig. 1a).

[0005] The effect of these so-called wave gradients on a magnetization m at a spatial location (x, y, z) can be multiplied by a point spread function (PSF), in particular a wave point spread function, P e.g. in the hybrid k x -yz space can be described as: wave(x,y,z)=Fx−1P[kx,y,z] (Fx m[x,y,z]), See analogously, for example, Bilgic's formula [8]. Wave(x, y, z) can be referred to as a "wave function" or "wave trajectory."

[0006] Here represent F x -1 and F x an inverse or a forward Fourier transform. The PSF function P(k x , y, z) describes the effect of sine / cosine wave gradients on the image phase in k x , ie, the coordinate in k-space in the x-direction, which is proportional to the readout time (see e.g. Cauley, Fig. 2a).

[0007] According to Daniel Polak et al.: “Highly-Accelerated Volumetric Brain Examination Using Optimized Wave-CAIPI Encoding,” J. Magn. Reson. Imaging; 2019; vol. 50; pages 961 to 974, the wave function can be written even more generally as wavei(x,y,z)=M∑x^P[x^,x,y,z] CI m[x−x^,y,z] see equation (2) there.

[0008] P(k x , y, z) is, for example, divided into a y-part P y = P(k x , y) and a z-component P z = P(k x , z). These “PSF subfunctions” P y and P z are typically in the form of matrices, which, when multiplied, form the PSF function P(k x , y, z). For image reconstruction, the PSF subfunctions P y and P z applied to the k-space lines or k-space trajectories obtained from the MR scan according to the above method. However, P can also be split into other components.

[0009] Furthermore, aliased wave acquisitions can be unaliased by solving a so-called SENSE problem, e.g., as described in Bilgic et al. Ideally, the PSF subfunctions P y and P z It can be sinusoidal or cosinusoidal, which, after the Fourier transformation, results in a modulation transfer function (MTF) with only one frequency component. In practice, the frequency spectrum of P y and P z However, due to deviations from an ideal gradient path, e.g. due to eddy currents, gradient delays, etc., an image reconstruction using the “ideal” P y and P z This then disadvantageously results in image blur in the resulting image.

[0010] Therefore, optimized or “actual” PSF subfunctions P y and P zby performing calibration measurements before the actual MR acquisition to determine the optimized PSF subfunctions. In Bilgic et al., the PSF subfunctions P y and P z determined by three reference scans: a scan in which all wave gradients are switched off, a scan in which only the PSF subfunction P y is switched on and a scan in which only the PSF subfunction P z is switched on.

[0011] In DE102018218471B3, it is proposed to determine the PSF subfunctions by measuring a central k-space line with and without wave coding outside the isocenter in the direction of the orthogonal spatial direction and to interpolate the PSF subfunctions from this.

[0012] Cauley et al. have developed an iterative approach for automatic calibration in which the frequency parameters of P y and P zvaries and the result of the image reconstruction is measured at some test locations by calculating the root mean square error (RMSE). When the RMSE approaches a local minimum, it is assumed that the best optimized PSF subfunctions P y and P z has been found. The optimized PSF subfunctions P y and P z are then applied to all k-space lines used for image reconstruction.

[0013] The calibration methods described above provide consistent results when the patient is stationary. In principle, these approaches, as well as all other approaches for determining optimal PSF subfunctions, can be combined with the procedure described below and are referred to there as "PSF calibration."

[0014] However, when the Wave-CAIPI method is combined with PSF calibration or a prospective motion correction method, such as a camera-based or a navigator-based method, it fails. This is because prospective motion correction methods compensate for patient motion by: (a) adjusting the receive and transmit frequencies to compensate for translational patient motion, and (b) rotating the relative gradient amplitudes to compensate for rotational patient motion. The latter, in particular, affects the wave reconstruction because the PSF subfunctions, e.g., P y and P z , depend on the absolute gradient amplitudes and orientations. This can disadvantageously produce undesirable image artifacts.

[0015] In F. Chen et al.: Autocalibrating Motion-Corrected Wave-Encoding for Highly. In: Magn Reson Med., November 2017, pp. 1757-1766 and US 2018 / 0 143 277 A1, a motion correction technique is disclosed according to which acquired MR signals are corrected based on a localized estimate of translational motion.

[0016] It is the object of the present invention to at least partially overcome the disadvantages of the prior art and in particular to provide a possibility to take patient movements into account when applying a Wave-CAIPI method and in particular to reduce image artifacts generated by patient movements.

[0017] This object is achieved according to the features of the independent claims. Preferred embodiments can be found in particular in the dependent claims.

[0018] The object is achieved by a method for MR-based reconstruction of images of a patient, in which it is monitored whether a value of a movement of the patient during an MR recording in at least one direction of movement exceeds a respective threshold value, and, if this is not the case, an image reconstruction, in particular by means of a Wave-CAIPI method, is carried out on the basis of identical calibrated PSF subfunctions for all k-space lines, while if this is the case, - several bins are provided corresponding to successive ranges of values of the patient movement in at least one direction of movement, - the k-space lines are assigned to the bins based on a motion value determined during their respective acquisition, - a PSF calibration is performed for at least two bins based on the k-space lines assigned to these bins and - an image reconstruction, in particular by means of a Wave-CAIPI method, is carried out in such a way that the PSF subfunctions associated with the assigned bins are used for the respective k-space lines.

[0019] This offers the particular advantage of combining a Wave-CAIPI method with PSF calibration with predictive motion correction, thus achieving improved image quality of the reconstructed image even in patients with higher levels of motion. Furthermore, the above method can be implemented with limited computational effort.

[0020] The method can be used to acquire at least one image (“MR image”) of a patient (“MR image” or “MR scan”) using an MR device based on the principle of magnetic resonance imaging.

[0021] Monitoring whether a patient's movement exceeds a respective threshold in at least one direction of movement during an MR acquisition can involve checking whether at least one threshold has been exceeded during the MR acquisition (e.g., in real time). Alternatively, the MR acquisition can be performed first, and only then can it be checked whether at least one threshold has been exceeded. In both cases, it is advantageous to store the determined (e.g., measured) movement data linked to the corresponding k-space lines.

[0022] The monitoring of the patient movement value is done by any basically known method, e.g. by means of at least one optical sensor (e.g. a camera, IR sensors, etc.) and / or by means of a navigator-based method.

[0023] The patient movement may be due to breathing, coughing, tickling, startle movement, etc.

[0024] In particular, the value can be an absolute value or a direction-dependent value.

[0025] Thresholds for different motion directions can be the same or different. In particular, they can be different to account for the different effects of motion in different directions on the Wave-CAIPI method.

[0026] A bin can be, in particular, a data group and / or a data class. "Binning" can be understood, in particular, as the assignment of k-space lines to one or more bins.

[0027] Monitoring whether a value of a patient's movement in at least one direction of movement exceeds a respective threshold can, in one development, comprise branching to the bin-dependent PSF calibration if even just one threshold is reached or exceeded. Another development can comprise branching to the bin-dependent PSF calibration only if multiple thresholds are reached or exceeded, in particular if these are reached or exceeded simultaneously. Yet another development can comprise branching to the bin-dependent PSF calibration if a value calculated from values belonging to multiple directions of movement reaches or exceeds the associated threshold.

[0028] In one variant, the reference point for the movement value is the patient's position assumed at the beginning of the MR acquisition, not the patient's position at the beginning of the k-space line acquisition. In this variant, the movement value corresponds specifically to the difference from the initial value at the beginning of the MR acquisition. In another variant, the movement value corresponds to the value during the k-space line acquisition, specifically to the difference from the initial value at the beginning of the k-space line acquisition.

[0029] The movement value can correspond to a maximum value during the acquisition of a k-space line. Alternatively, the movement value can correspond to an average value during the acquisition of a k-space line.

[0030] The respective thresholds are typically chosen such that, if all thresholds are not reached (i.e., the patient has moved only slightly), the effect of prospective motion correction on the Wave-CAIPI method with PSF calibration is sufficiently small. In this case, a conventional, generally known image reconstruction is performed using the Wave-CAIPI method with PSF calibration. This includes, in particular, calculating PSF subfunctions using PSF calibration, which are then applied to all k-space lines used for image reconstruction in the subsequent Wave-CAIPI method.

[0031] If, however, the patient's movement value reaches or exceeds the threshold in at least one direction of movement (i.e., the patient has moved significantly in at least one direction of movement), the k-space lines or trajectories are assigned to one of the bins according to the movement value determined during their acquisition. A PSF calibration is then performed for at least one of the bins. The Wave-CAIPI method is then implemented in such a way that bin-dependent PSF subfunctions are applied to the k-space lines belonging to the respective bin. In other words, the Wave-CAIPI method is applied to the k-space lines in the same way as before, but with the difference that the PSF subfunctions used for a specific k-space line have previously been determined based on the bin to which this k-space line has been assigned.

[0032] The fact that the bins correspond to consecutive value ranges at least in one direction of movement implies, in particular, that the value ranges follow one another without gaps. Furthermore, the assignment of the k-space lines to the bins is advantageously unambiguous, i.e., each k-space line can be assigned to exactly one bin. The value ranges of the bins therefore advantageously do not overlap, which can also be expressed by the bins having disjoint value ranges.

[0033] The (value) width and / or number of bins for a direction of movement can generally be set arbitrarily. For example, it can be set based on the maximum value of the movement in a certain direction of movement: the larger this maximum value, the larger the width and / or the higher the number of bins can be. A further development is that the width of the bins is constant and is specified in particular for a direction of movement. The number N of bins for a direction of movement is then calculated from the quotient of the maximum value divided by the specified width of the bins. If, on the other hand, the number N of bins is specified for a direction of movement, the width of the bins is calculated from the quotient of the maximum value divided by N. However, the bins for a direction of movement can also have a variable width.

[0034] In one embodiment, the movement in at least one direction of movement comprises a rotational movement about at least one spatial axis, in particular the body axis. Thus, the rotational movement can correspond to a rotation Δθ x around the transverse axis x, a rotation Δθ y around the sagittal axis y and / or a rotation Δθ z about the longitudinal axis z. Each of the rotational movements can be associated with a respective threshold value Tθx, Tθy, or Tθy, at least two of which can be different.

[0035] Each of the translational movements Δx, Δy and / or Δz can be assigned a respective threshold value Tx, Ty or Tz, of which at least two can be different.

[0036] In an additional or alternative embodiment, the movement in at least one direction of movement comprises a translational movement along at least one spatial axis. The spatial axis can, in particular, be a body axis of the patient, so that the translational movement can be, for example, a translational movement Δx along its transverse axis x, a translational movement Δy along its sagittal axis y, and / or a translational movement Δz along its longitudinal axis z.

[0037] The use of Cartesian spatial axes has the advantage that they are orthogonal to each other. However, other coordinate systems can also be used, in particular a polar coordinate system {z, r, θ z}, e.g. with a translational movement Δz along the longitudinal axis (especially longitudinal axis) z, a rotation Δθ z around the longitudinal axis z and / or a translational movement Δr along the radial direction.

[0038] In general, at least one direction of motion used to monitor patient movement during the MR acquisition can correspond to at least one direction of motion for which the bins are provided. This can be the case, for example, when monitoring for a translational movement Δz along the patient's longitudinal axis z. Bins can then be provided that distinguish at least two value ranges in the z direction.

[0039] Alternatively or additionally, at least one movement direction used to monitor the patient movement during the MR acquisition may differ from at least one movement direction for which the bins are provided: For example, monitoring of the patient movement during the MR acquisition may be based on the rotation Δθ zaround the patient's longitudinal axis z, while the bins provided to account for this rotation differentiate the movement in the x- and y-directions. This takes advantage of the fact that the rotation Δθ z can be clearly converted into translational movements Δx and Δy. Thus, the patient's movement is simply expressed or taken into account in different coordinate systems when monitoring during the MR acquisition and when providing the bins.

[0040] One embodiment allows a bin to encompass a range of values in which the patient movement value in at least one direction of movement is consistently below the respective threshold. In other words, the threshold value has not been reached or exceeded for any of the considered directions of movement in the k-space lines assigned to this bin. This advantageously also specifically considers those k-space lines in which the patient did not move significantly during the acquisition. This bin can also be referred to as the "neutral bin."

[0041] One embodiment provides multiple bins with consecutive value ranges only for those movement directions where the patient's movement has exceeded the corresponding threshold. This allows for a reduction in the computational effort required to perform the PSF calibrations.

[0042] It is an advantageous design for particularly high image quality that a PSF calibration is carried out for each bin.

[0043] One embodiment involves performing a PSF calibration for only a portion of the bins, and interpolating or extrapolating the PSF subfunctions of the remaining bins from the iteratively calibrated PSF subfunctions. This allows for a reduction in the computational effort required to obtain optimized PSF subfunctions for all bins, since interpolation or extrapolation requires significantly less computational effort than iterative PSF calibration. The interpolation or extrapolation can, for example, include or be a linear interpolation.

[0044] In one embodiment, at least two of the bins for which an iterative PSF calibration is performed are bins whose associated directions of motion are orthogonal to each other. This facilitates the interpolation or extrapolation of the PSF subfunctions of other bins, for example, by allowing the PSF subfunctions of the other bins to be determined by linear combination of the PSF subfunctions calculated by PSF calibration. Orthogonal directions of motion include, for example, translational movements along the axes of a Cartesian coordinate system, translational and rotational movements along or around the same axis, etc.

[0045] In other words, the optimized PSF subfunctions for the respective bins can be obtained either by respective PSF calibration for all bins or by PSF calibration for at least two bins and interpolation or extrapolation of the PSF subfunctions of the other bins from the PSF subfunctions of the calibrated bins.

[0046] One embodiment of the method is that one of the bins for which a PSF calibration is performed is the bin to which the most k-space lines have been assigned. This has the advantage of allowing image artifacts to be avoided particularly reliably. This bin can also be referred to as the "main bin."

[0047] A further development is that one of the bins for which a PSF calibration is performed is the neutral bin, because this advantageously allows a particularly accurate calculation of a "slope" for extrapolation or interpolation from the difference to the other bins. This also has the advantage of reliably avoiding image artifacts.

[0048] The method according to the invention achieves the further advantage that—in contrast to Bilgic et al.—the reference scans can be performed after MR imaging. Three reference scans can still be performed, but their orientation is now selected based on the orientation of the main bin (to which most k-space lines have been assigned). This can, in particular, include setting the center coordinate(s) of the main bin as the zero coordinate(s), thus setting the main bin as the (new) neutral bin. This provides the advantage that a particularly large number of lines undergo correct PSF calibration.

[0049] Another refinement is to check whether a specified proportion (e.g., at least 90%) of the k-space lines lie in the main bin (i.e., that only minimal positional scatter occurred during the MR acquisition). If this is the case, a conventional CAIPI procedure is performed without coordinate binning. The zero position can then correspond, for example, to the averaged position of the k-space lines, the center of the main bin, etc.

[0050] In general, the above method, which uses motion or coordinate binning, can be applied to all suitable CAIPI methods without coordinate binning.

[0051] The object is also achieved by an MR system, wherein the MR system is configured to perform the method as described above. It advantageously comprises at least one MR device for performing an MR scan on a patient, a means for determining patient movement during the MR scan, and a data processing device for image reconstruction using a Wave-CAIPI method with iterative calibration based on the k-space lines resulting from the MR scan.

[0052] The MR device may, for example, comprise or be a body coil, such as a head coil or a thorax coil, but also any other body coil such as a neck coil, extremity coil, etc.

[0053] The above-described properties, features and advantages of this invention, as well as the manner in which they are achieved, will become clearer and more readily understood in connection with the following schematic description of an embodiment, which is explained in more detail in connection with the drawings. Fig. 1 shows a possible sequence of the method according to the invention; Fig. Figure 2 shows a sketch of a possible bin scheme; Fig. 3 shows another possible sequence of the method according to the invention; and Fig. Figure 4 shows a sketch of another possible bin scheme.

[0054] Fig. Figure 1 shows a possible procedure for MR image reconstruction based on the Wave-CAIPI method with PSF calibration and predictive motion correction.

[0055] In a first step S0, an MR image of a patient is taken using a magnetic resonance imaging system (MR system 1). The MR system 1 is configured in a generally known manner to detect a patient's movement, for example, using at least one optical sensor 2 (e.g., a camera, IR sensors, etc.) and / or a navigator-based method. Patient movements can be detected directly on the patient or indirectly via movements of markers, etc., arranged with body coils and / or on the patient. Rotational movements and longitudinal movements of the patient can be detected as movements, in particular.

[0056] In a step S1, after the MR acquisition has been performed, the MR system 1 (e.g., an associated data processing device, not shown) checks whether a (e.g., absolute) value of a patient movement in at least one direction of movement has reached or exceeded a corresponding threshold value. The following description refers to monitoring for a rotation Δθ z of the patient around their longitudinal axis z. This has a particularly strong influence on the PSF calibration. However, other directions of movement can be monitored alternatively or additionally, e.g., a translation Δz along the longitudinal axis z.

[0057] If this is not the case (“N”) and the patient has not turned or has turned only slightly, the process branches to steps S2 and S3, which perform a conventional image reconstruction using the k-space lines derived from the MR image on the basis of the Wave-CAIPI method with PSF calibration, as described, for example, in Bilgic et al. and Cauley et al. This can be done, for example, by first performing a PSF calibration in step S2 based on all k-space lines generated by the MR image. The result of the PSF calibration is the set of PSF subfunctions optimized by calibration (e.g., P y and P z ) is available. In a subsequent step S3, an MR image is reconstructed using the Wave-CAIPI method, using this one set of optimized PSF subfunctions.

[0058] However, if only one value of the rotation Δθ zof the patient during the MR acquisition is equal to or greater than the threshold value Tθz (“J”), the process branches to steps S4 to S7.

[0059] In step S4, several so-called bins are determined or defined, to which the k-space lines are assigned depending on the value of the rotation Δθ z of the patient while clearly assigned.

[0060] Fig. Figure 2 shows a possible bin scheme. This is based on the values of the rotation Δθ z of the patient are converted into corresponding values in the Cartesian (x,y) coordinate plane. This results in the respective maximum values of the movement Δxmax and Δymax along the x-axis and the y-axis, respectively. Bins B i.j are then defined as two-dimensional sub-areas of the surface in the (x,y)-plane within Δx = [0; Δxmax] and Δy = [0; Δymax]. For the purposes of this example, 16 bins B i.jwith value ranges i = 0, ..., 3 in x-direction and value ranges j = 0, ..., 3 in y-direction, i.e. with N x = 4 value ranges in x-direction and N y = 4 value ranges in the y-direction. This can also be expressed as follows: for y = const. N x = 4 bins in the x-direction, analogously for x = const. N y = 4 bins in y-direction.

[0061] The k-space lines are assigned to these bins B i.j depending on the values Δx and Δy determined during their acquisition. For example, for a specific k-space line, the corresponding rotation value Δθ z corresponding Cartesian values Δx and Δy have been calculated, which lie in the range [Δx2; Δx3[ and [Δy1; Δy2[ respectively, this k-space line is assigned to bin B 2.1 assigned.

[0062] The Bin B 0.0 can correspond to the neutral bin, but does not have to.

[0063] The value ranges of bins Bi.j can be the same width in the x-direction and / or y-direction, but need not be. The number N x different from the number N y be elected.

[0064] Returning to Fig. 1 In step S5, the k-space lines of the MR image are assigned to bins B i.j assigned.

[0065] In step S6, for all bins B i.j a PSF calibration based on these bins B i.j associated k-space lines k x (B i.j ) carried out.

[0066] In step S7, an image reconstruction is subsequently carried out using a Wave-CAIPI method such that for the respective k-space lines k x (B i.j ) or the wave functions related to them for the assigned bins B i.j calculated calibrated PSF subfunctions P x (B i.j ) and P y (B i.j ) be used.

[0067] Fig. 3 shows another possible sequence of the procedure.

[0068] Here, instead of step S6, where for all bins B i.j a respective PSF calibration is carried out in a step S6a only for some of the bins B i.j a PSF calibration is performed, while the PSF subfunctions of the remaining bins B i.j be interpolated or extrapolated from it in a step S6b.

[0069] Again referring back to Fig. 2, the PSF calibrations can be carried out, for example, in such a way that they are carried out for at least one of the bins B 1.0 , B 2.0 or B 3.0 (which include a noticeable movement of the patient practically only along the x-axis) and one of the bins B 0.1 , B 0.2 or B 0.3(which involve a noticeable movement of the patient practically only along the orthogonal y-axis). This has the advantage that the optimized PSF subfunction of the other bins B i.j can be interpolated or extrapolated by a simple linear combination of the PSF subfunctions calculated by PSF calibration. However, other bins B i.j be used, especially if they do not all have the same index i or j.

[0070] However, for other bins B i.j a respective PSF calibration must be carried out, as this will ensure the accuracy of the interpolation or extrapolation of the PSF subfunctions for the other bins B i.j can be increased.

[0071] Thus, it is advantageous for improved image quality if in step S6a also for the bin B i.j which has the most k-space lines, a PSF calibration is performed.

[0072] It may also be advantageous for improved image quality if, in step S6a, additionally or alternatively for Bin B 0.0 a PSF calibration is carried out, because then a “slope” for an extrapolation or interpolation in the x and y directions can be calculated particularly precisely from the difference to the other bins.

[0073] In step S7, an image reconstruction is then carried out using a Wave-CAIPI method such that for the respective k-space lines k x (B i.j ) for the assigned bins B i.j optimized (calibrated or interpolated or extrapolated) PSF subfunctions can be used.

[0074] Fig. Figure 4 shows a sketch of another possible binning scheme. Here, the bins are determined only by the rotation values Δθ z= [θ3n; θ4p], which is particularly simple and sufficiently accurate when patient rotations have the main influence on the PSF change. Here, rotation values θin with i = 1, ..., 3 represent counterclockwise rotations and rotation values θjp with j = 1, ..., 3 represent clockwise rotations. Values θin and θjp with i = j can be the same or different. In this case, Bin B0 is purely exemplary by Δθ z = 0. This bin scheme can be used analogously to the bin scheme from Fig. 2 can be used.

[0075] Although the invention has been illustrated and described in detail by the embodiment shown, the invention is not limited thereto and other variations can be derived therefrom by a person skilled in the art without departing from the scope of the invention.

[0076] Thus, the above method is generally not limited to the formulation of the wave function or wave trajectory in Cartesian coordinates described above, but can also be applied to non-Cartesian wave functions or wave trajectories as long as the conditions specified in Bilgic et al. and Cauley et al. are met.

Claims

[1] Method (S0-S7) for MR-based reconstruction of images of a patient in which monitoring (S0) whether a value of a patient's movement during an MR recording in at least one direction of movement exceeds a respective threshold value (S1), and, If this is not the case, an image reconstruction, in particular using a Wave-CAIPI method, is carried out on the basis of identical calibrated PSF subfunctions for all k-space lines (S2-S3), while if this is the case, - multiple bins (B 0.0 -B 3.3 ; B -i / +j ) are provided (S4), the successive value ranges of the patient movement in at least one direction of movement (x, y; θ z ) are equivalent to, - the k-space lines to the bins (B 0.0 -B 3.3 ; B -i / +j ) based on a movement value (Δx, Δy; θ z) (S5), - for at least two bins (B 0.0 -B 3.3 ; B -i / +j ) a calibration of PSF subfunctions is carried out on the basis of the k-space lines assigned to these bins (S6) and - an image reconstruction, in particular by means of a Wave-CAIPI method, is carried out in such a way that for the respective k-space lines the bins (B 0.0 -B 3.3 ; B -i / +j ) associated PSF subfunctions can be used (S7). [2] Method (S0-S7) according to claim 1, wherein the movement (Δx, Δy; Δθ z ) in at least one direction of movement (x, y; θ z ) corresponds to a translational movement (Δx, Δy) along at least one spatial axis (x, y), in particular body axis (x, y). [3] Method (S0-S7) according to one of the preceding claims, in which the movement (Δx, Δy; Δθ z ) in at least one direction of movement (x, y; θ z) a rotational movement (Δθ z ) around at least one spatial axis, in particular body axis (z). [4] Method (S0-S7) according to one of the preceding claims, in which a bin (B 0.0 ; B0) covers a range of values where the value of the movement (Δx, Δy; Δθ z ) in at least one direction of movement (x, y; θ z ) is consistently below the respective threshold. [5] Method (S0-S7) according to one of the preceding claims, in which several bins (B 0.0 -B 3.3 ; B -i / +j ) with consecutive ranges of values only for such directions of movement (x, y; θ z ) are provided, where the movement (Δx, Δy; Δθ z ) of the patient has exceeded the corresponding threshold. [6] Method (S0-S7) according to one of the preceding claims, in which only for a part of the bins (B 0.0 -B 3.3 ; B_ i / +j) a PSF calibration is carried out and the PSF subfunctions of the remaining bins (B 0.0 -B 3.3 ; B -i / +j ) can be interpolated or extrapolated from the calibrated PSF subfunctions. [7] Method (S0-S7) according to claim 6, wherein one of the bins (B 0.0 -B 3.3 ; B -i / +j ) for which an iterative calibration is performed, the bin (B 0.0 -B 3.3 ; B -i / +j ) to which most k-space lines have been assigned. [8] Method (S0-S7) according to one of claims 6 or 7, wherein at least two of the bins (B 0.0 -B 3.3 ) for which a PSF calibration is performed, bins (B 0.0 -B 3.3 ) whose corresponding directions of movement (x, y) are orthogonal to each other. [9] Method (S0-S7) according to one of the preceding claims, in which for all bins (B 0.0 -B 3.3 ; B -i / +j) a PSF calibration is carried out. [10] MR system (1, 2), wherein the MR system (1, 2) is configured to carry out the method (S0-S7) according to one of the preceding claims and comprises at least one MR device (1) for carrying out an MR recording on a patient (S0), a means (2) for determining a movement of the patient and a data processing device for image reconstruction by means of a Wave-CAIPI method with iterative calibration based on the k-space lines (S2-S7) resulting from the MR recording. [11] MR system (1, 2) according to claim 10, wherein the MR device (1) comprises a body coil, in particular a head coil.

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