Motion correction in magnetic resonance imaging

Abstract

A method for reconstructing dynamic image data is described. In the method, raw data is acquired in a time-dependent manner from an examination region, wherein at least some of the raw data is assigned various values of movement parameters. First time-dependent image data based on acquired raw data is reconstructed. Furthermore, deformation fields based on the first image data are determined as a function of at least two time-dependent movement parameters. Based on the deformation fields, the raw data and the first image data, corrected image data is then generated. Furthermore, a reconstruction apparatus is described. Moreover, a magnetic resonance imaging system is described.

Claims

1. A method for reconstructing dynamic magnetic resonance image data by a magnetic resonance imaging system, the method comprising: acquiring time-dependent magnetic resonance raw data from an examination region at a plurality of different times, wherein at least some of the acquired time-dependent magnetic resonance raw data is assigned to various values of at least two time-dependent movement parameters, and wherein the at least two time-dependent movement parameters comprise a time and a movement state of respiration or a movement state of a heart; reconstructing first time-dependent image data based on the acquired time-dependent magnetic resonance raw data; ascertaining deformation fields based on the first time-dependent image data as a function of the at least two time-dependent movement parameters; generating synthetic raw data for different values of the at least two time-dependent movement parameters based on the reconstructed first time-dependent image data and the ascertained deformation fields; and generating corrected image data based on the generated synthetic raw data.

2. The method of claim 1, wherein the generating of the corrected image data takes place based on an iterative reconstruction in which the deformation fields are used to generate corrected raw data.

3. The method of claim 2, wherein the acquiring of the time-dependent magnetic resonance raw data comprises a Cartesian scanning of magnetic resonance raw data.

4. The method of claim 3, wherein the ascertaining of the deformation fields comprises a registering of the first time-dependent image data with at least partially different values of the time-dependent movement parameters.

5. The method of claim 1, wherein the acquiring of the time-dependent magnetic resonance raw data comprises a Cartesian scanning of magnetic resonance raw data.

6. The method of claim 1, wherein the ascertaining of the deformation fields comprises a registering of the first time-dependent image data with at least partially different values of the time-dependent movement parameters.

7. The method of claim 1, further comprising: comparing the synthetic raw data and the acquired time-dependent magnetic resonance raw data; detecting a false assignment of the acquired time-dependent magnetic resonance raw data to the at least two time-dependent movement parameters; and reassigning the time-dependent magnetic resonance raw data to changed values of the at least two time-dependent movement parameters based on the synthetic raw data.

8. The method of claim 7, wherein the reassigning to the changed values of the at least two time-dependent movement parameters takes place as a function of which synthetic raw data points of the synthetic raw data are closest to acquired magnetic resonance raw data points of the acquired time-dependent magnetic resonance raw data in a distance measurement or by correlation.

9. The method of claim 8, wherein the reassigning of the time-dependent magnetic resonance raw data is first performed on a subset of the acquired time-dependent magnetic resonance raw data and then the corrected image data is reconstructed based on all the acquired time-dependent magnetic resonance raw data.

10. The method of claim 9, wherein the subset of the acquired time-dependent magnetic resonance raw data is a subset in a fully sampled direction of the acquired time-dependent magnetic resonance raw data.

11. The method of claim 1, wherein acquired time-dependent magnetic resonance raw data categorized in at least one time-dependent movement parameter of the at least two time-dependent movement parameters are discarded and the corrected image data is only generated as a function of a subset of the at least two time-dependent movement parameters.

12. An image reconstruction apparatus of a magnetic resonance imaging system, the image reconstruction apparatus comprising: an input interface configured to generate time-dependent magnetic resonance raw data from an examination region, wherein at least some of the time-dependent magnetic resonance raw data is associated with different values of at least two time-dependent movement parameters, and wherein the at least two time-dependent movement parameters comprise a time and a movement state of respiration or a movement state of a heart; a reconstruction unit configured to reconstruct first time-dependent image data based on the time-dependent magnetic resonance raw data; a deformation field determination unit configured to determine deformation fields based on first time-dependent image data as a function of the at least two time-dependent movement parameters; and a correction unit configured to: (1) generate synthetic raw data for different values of the at least two time-dependent movement parameters based on the reconstructed first time-dependent image data and the determined deformation fields, and (2) generate corrected image data based on the generated synthetic raw data.

13. A magnetic resonance imaging system comprising: an image reconstruction apparatus comprising: an input interface configured to generate time-dependent magnetic resonance raw data from an examination region, wherein at least some of the time-dependent magnetic resonance raw data is associated with different values of at least two time-dependent movement parameters, wherein the at least two time-dependent movement parameters comprise a time and a movement state of respiration or a movement state of a heart; a reconstruction unit configured to reconstruct first time-dependent image data based on the time-dependent magnetic resonance raw data; a deformation field determination unit configured to determine deformation fields based on first time-dependent image data as a function of the at least two time-dependent movement parameters; and a correction unit configured to: (1) generate synthetic raw data for different values of the at least two time-dependent movement parameters based on the reconstructed first time-dependent image data and the determined deformation fields, and (2) generate corrected image data based on the generated synthetic raw data.

14. The method of claim 1, further comprising: assigning the acquired time-dependent magnetic resonance raw data to individual movement states, prior to the reconstructing of the first time-dependent image data.

15. The method of claim 2, wherein the iterative reconstruction comprises: ascertaining whether the corrected image data complies with a quality criterion; and when the corrected image data does not comply with the quality criterion, iteratively repeating ascertaining new deformation fields based on the corrected image data, generating new synthetic raw data, and generating new corrected image data until the new corrected image data complies with the quality criterion.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

(1) The disclosure is explained again in more detail hereinafter with reference to the attached figures with the aid of exemplary embodiments, in which:

(2) FIG. 1 depicts a flow chart which illustrates a method for reconstructing dynamic image data according to an exemplary embodiment.

(3) FIG. 2 depicts a flow chart which illustrates a method for reconstructing dynamic image data according to a second exemplary embodiment.

(4) FIG. 3 depicts a block diagram which illustrates an image reconstruction apparatus according to an exemplary embodiment.

(5) FIG. 4 depicts a diagrammatic view of a magnetic resonance imaging system according to an exemplary embodiment.

DETAILED DESCRIPTION

(6) FIG. 1 depicts a flow chart 100 which illustrates the method for reconstructing dynamic image data according to an exemplary embodiment.

(7) In act 1.I, raw data RD from an examination region is first recorded. The examination region behaves dynamically during the acquisition of raw data RD, e.g., at least some of the raw data RD is assigned to different values of movement parameters BP.sub.t. In act 1.II, first time-dependent image data BD1 is reconstructed on the basis of recorded raw data RD.

(8) In act 1.III, deformation fields DF are determined on the basis of first image data BD1. The deformation fields DF depend on at least two time-dependent movement parameters, for example, the time t and the respiratory movement state AZ.

(9) In act 1.IV, synthetic raw data RD.sub.s is generated with the aid of the first image data and the deformation fields DF.

(10) Furthermore, in act 1.V, corrected image data BD.sub.k is reconstructed on the basis of synthetic raw data RD.sub.s. In act 1.VI, it is ascertained whether the corrected image data BD.sub.k complies with a quality criterion crit. For example, the corrected image data BD.sub.k is inspected for artifacts. If the quality criterion has not yet been met, (which is characterized by n in FIG. 1), act 1.III is returned to, in which deformation fields DF, now however based on corrected image data BD.sub.k, are generated again. Then the method is continued with acts 1.IV to 1.VI. In the event that act 1.VI ascertained that the quality criterion crit was met for the corrected images BD.sub.k, (characterized by y in FIG. 1), then act 1.VII is commenced, in which the last generated image data BD.sub.k is adopted as final image data BD.

(11) FIG. 2 depicts a flow chart 200 which illustrates the method for reconstructing dynamic image data according to a second exemplary embodiment.

(12) In act 2.I, magnetic resonance raw data RD is first acquired from an examination region FoV of a patient. In addition, in act 2.II, Navigator raw data NV-RD is acquired and reconstructed to form Navigator image data NV-BD. The Navigator image data NV-BD characterizes a movement state of the examination region FoV for imaging. Based on the now known movement states and the raw data RD, in act 2.III raw data RD is now assigned to individual movement states, raw data RD.sub.1 assigned according to movement state is therefore generated.

(13) In act 2.IV, image data BD is reconstructed on the basis of raw data RD.sub.1 assigned according to movement states. In the process, items of raw data, which are assigned to different times but the same movement states, are combined with one another. Furthermore, in act 2.V, a complete set of raw data with additional synthesized RD.sub.s is generated in the k-space for each movement state n and each time t, which replaces the raw data missing due to sub-sampling in raw data acquisition. In act 2.VI, the acquired raw data RD is then reassigned to the individual movement states by comparing the assignment of the acquired raw data RD and/or the classified raw data RD.sub.1 to the assignment of the synthesized raw data RD.sub.s. If applicable, corrected and/or reclassified raw data RD.sub.k is generated. Act 2.VII checks whether an abort criterion crit is met. In the event that the abort criterion has not yet been met, which is characterized by n in FIG. 2, act 2.IV is returned to and image data BD is reconstructed again based on the raw data RD.sub.k corrected in act 2.VI. Subsequently, acts 2.V and 2.VI are performed again. If an abort criterion crit is met in act 2.VII, for example, if a counting index has reached a maximum number of iterations for performance, which is characterized by y in FIG. 2, then act 2.VIII is commenced.

(14) In act 2.VIII, image data BD.sub.n,t is reconstructed on the basis of corrected raw data RD.sub.k ascertained in act 2.VI which is classified according to movement state n and time t, wherein the images of different movement states are generated using deformation fields DF. In other words, the deformation fields DF are used to register image data of different movement states on top of one another in order to also obtain an adequate database for each of the movement states in a sub-sampling of individual movement states. For example, a matrix representing the identity may be used as an initial deformation field DF.sub.0. Subsequently, in act 2.IX deformation fields DF.sub.n,t between different movement states and different times are ascertained on the basis of reconstructed image data BD.sub.n,t. If an abort criterion crit is not met, (which is characterized by n in FIG. 2), in act 2.X, there is a return to act 2.VIII and image data BD.sub.n,t classified according to movement state and time is reconstructed in turn, but this time using the newly generated deformation fields DF.sub.n,t between different movement states n and different times t. If an abort criterion crit is met for iteration in act 2.X, (which is characterized by y in FIG. 2), then act 2.XI is commenced, in which the last reconstructed image data BD.sub.n,t is output as final image data BD.

(15) FIG. 3 illustrates an image reconstruction apparatus 30 according to an exemplary embodiment. The image reconstruction apparatus 30 includes an input interface 31 which is configured to receive raw data RD acquired in a time-dependent manner. At least some of the raw data RD is assigned to different values of movement parameters BP.sub.t. The raw data RD is transmitted to a reconstruction unit 32, which reconstructs first time-dependent image data BD.sub.1 on the basis of the acquired raw data RD. The image data BD.sub.1 is forwarded to a deformation field determination unit 33, which determines deformation fields DF based on the first image data BD.sub.1 as a function of at least two time-dependent movement parameters BP.sub.t. The determined deformation fields DF and the received raw data RD and the reconstructed image data BD.sub.1 are transmitted to a correction unit 34, which determines corrected image data BD.sub.k based on the deformation fields DF, the raw data and the first image data BD1.

(16) The correction unit 34 includes a synthesization unit 34a, which generates synthesized raw data RD.sub.s based on the deformation fields DF, the raw data RD, and the image data BD1. Part of the correction unit 34 is also an image data reconstruction unit 34b, which reconstructs corrected image data BD.sub.k based on synthesized raw data RD.sub.s. The corrected image data BD.sub.k is transmitted to a testing unit 34c, which is configured to test the corrected image data BD.sub.k with regard to the occurrence of artifacts. If the tested image data BD.sub.k does not yet meet a predetermined quality criterion, the corrected image data BD.sub.k is sent back to the deformation field determination unit 33, which generates corrected deformation fields DF based on corrected image data BD.sub.k which, together with the corrected image data BD.sub.k, are in turn transmitted to the correction unit 34 from which corrected image data BD.sub.k is then generated again. If this complies with the aforementioned quality criterion, the last generated corrected image data BD.sub.k is established as the final image data BD and output by way of an output interface 35.

(17) FIG. 4 diagrammatically outlines a magnetic resonance system and/or a magnetic resonance imaging system 1. This includes the actual magnetic resonance scanner 2 with a measuring area 8 and/or patient tunnel therein. A couch 7 may be moved into this patient tunnel 8 such that during an examination an examination object O (e.g., patient/subject) lying thereon may be accommodated in a particular position inside the magnetic resonance scanner 2 relative to the magnet system and high frequency system arranged therein and/or may also be moved between different positions during a measurement.

(18) Components of the magnetic resonance scanner 2 include a basic field magnet 3, a gradient system 4 with gradient coils to create any magnetic field gradients in x, y, and z direction, and a whole-body radiofrequency coil 5. Magnetic resonance signals induced in the examination object O may be received by way of the whole-body coil 5 with which the radio frequency signals for inducing the magnetic resonance signals may also be emitted. These signals may be received with local coils 6 placed on or under the examination object O. In principle, all these components are known to a person skilled in the art and therefore only outlined diagrammatically in FIG. 4.

(19) The whole-body radiofrequency coil 5 may have a number N of individual antenna rods which are separately controllable as individual transmit channels S1, . . . , SN from a control device 10, e.g., the magnetic resonance imaging system 1 is a pTX-capable system. However, it is expressly pointed out that the method is also applicable to traditional magnetic resonance imaging devices with only one transmit channel.

(20) The control device 10 may be a control computer that includes a plurality of individual computersif necessary, also spatially separated and connected to one another by way of suitable bus systems and/or cables or the like. This control device 10 is connected by way of a terminal interface 17 to a terminal 20, by way of which an operator may control the entire system 1. In the present case, this terminal 20 has a computer 21 with a keyboard 28, one or more monitors 27, and further input devices, (e.g., a mouse or the like), thus providing the operator with a graphic user interface.

(21) The control device 10 has, inter alia, a gradient control unit 11 that may in turn include a plurality of subcomponents. The individual gradient coils are switched via this gradient control unit 11 with the control signals SGx, SGy, SGz. These are gradient pulses set at exactly scheduled time positions and with a predetermined temporal progression during a measurement to, for example, scan the examination object O and the assigned k-space in individual layers SL according to a control sequence AS.

(22) Furthermore, the control device 10 has a radio-frequency transmitter/receiver unit 12. This RF transmitter/receiver unit 12 likewise includes a plurality of subcomponents to emit high frequency pulses in each case separately and parallel to the individual transmit channels S.sub.1, . . . S.sub.N, e.g., in this case to the individually controllable antenna rods of the body coil 5. Magnetic resonance signals may also be received via the transmitter/receiver unit 12. In this exemplary embodiment, however, this occurs with the aid of the local coils 6. The raw data RD received with these local coils 6 is read out and processed by an RF receiver unit 13. The magnetic resonance signals received from these or from the whole-body coil 5 by the RF transmitter/receiver unit 12 are transferred as raw data RD to an image reconstruction apparatus 30, which reconstructs the image data BD in the manner described in connection with FIG. 3 and stores it in a storage unit 16 and/or transfers it to the terminal 20 by way of the interface 17 so that the operator may view it. The image data BD may also be stored and/or displayed and evaluated at other sites via a network NW. Provided that the local coils 6 have a suitable switching unit, the local coils may also be connected to an RF transmitter/receiver unit 12 to also use the local coils for transmission, in particular in pTX mode.

(23) The gradient controller 11, the RF transmitter/receiver unit 12, and the receiver unit 13 for the local coils 6 are activated, in each case coordinated by a measurement control unit 15. By corresponding commands, this provides that a desired gradient pulse train GP is emitted by appropriate gradient control signals SGx, SGy, SGz, and activates the RF transmitter/receiver unit 12 in parallel such that a multi-channel pulse train MP is emitted, e.g., that the appropriate radio-frequency pulses are provided in parallel on the individual transmit channels S.sub.1, . . . S.sub.N to the individual transmission rods of the whole-body coil 5. Furthermore, it is provided that the magnetic resonance signals to the local coils 6 are read out and processed by the RF receiver unit 13 and/or any signals to the whole-body coil 5 are read out and processed by the RF transmitter/receiver unit 12 at the appropriate time. The measurement control unit 15 specifies the corresponding signals, in particular, the multi-channel pulse train MP to the high frequency transmitter/receiver unit 12, and the gradient pulse train GP to the gradient control unit 11, according to a predetermined control protocol P. All the control data, which is adjusted during a measurement according to a predetermined control sequence AS, is stored in this control protocol P.

(24) A plurality of control protocols P may be stored in a storage unit 16 for various measurements. These could be selected by the operator by way of the terminal 20, and if applicable, varied to then have an appropriate control protocol P available for the currently desired measurement with which the measurement control unit 15 may work. Otherwise, the operator may also call up control protocols P via a network NW, for example, from a manufacturer of the magnetic resonance system and then modify and use these, if need be.

(25) The process of such a magnetic resonance measurement and the aforementioned components for activation are known to the person skilled in the art, however, and so they are not discussed in further detail here. Otherwise, such a magnetic resonance scanner 2 and the associated control device 10 may still have a plurality of further components which are likewise not described in detail here. It is noted at this point that the magnetic resonance scanner 2 may also be designed differently, for example, with a laterally open patient area, and that in principle the high frequency whole-body coil need not be designed as a birdcage antenna.

(26) Finally, it is noted once again that in the case of the method and devices described above, they are exemplary embodiments of the disclosure and that the disclosure may be varied by the person skilled in the art without departing from the scope of the disclosure, insofar as it is specified by the claims. The method and the reconstruction apparatus were therefore primarily explained with the aid of a magnetic resonance system for recording medical image data. However, the disclosure is not limited to the application in the medical field but the disclosure may in principle also be applied to magnetic resonance systems for recording dynamic images for other purposes. For the sake of completeness, it is also noted that the use of the indefinite article a and/or an does not exclude the features concerned also being present several times. Likewise, the term unit does not exclude this including a plurality of components which may likewise also be spatially distributed.

(27) It is to be understood that the elements and features recited in the appended claims may be combined in different ways to produce new claims that likewise fall within the scope of the present disclosure. Thus, whereas the dependent claims appended below depend from only a single independent or dependent claim, it is to be understood that these dependent claims may, alternatively, be made to depend in the alternative from any preceding or following claim, whether independent or dependent, and that such new combinations are to be understood as forming a part of the present specification.

(28) While the present disclosure has been described above by reference to various embodiments, it may be understood that many changes and modifications may be made to the described embodiments. It is therefore intended that the foregoing description be regarded as illustrative rather than limiting, and that it be understood that all equivalents and/or combinations of embodiments are intended to be included in this description.