Spiral-shaped MR detection pattern

Abstract

Method for generating at least one detection pattern for the detection of magnetic resonance signals, wherein at least one capture pattern is generated with a capture pattern generation unit, where at least one detection pattern has several spiral-like spokes in a k-space, where each spoke has several spiral points, where the position of the multiple spiral points is transformed from a polar coordinate system into a Cartesian coordinate system, where the transformation depends on at least one dimension of an image area.

Description

[0001] The invention relates to a method for generating at least one detection pattern for the detection of magnetic resonance signals, a detection pattern generation unit, a magnetic resonance device and a computer program product.

[0002] Magnetic resonance imaging (MRI) is an imaging technique used primarily in medical diagnostics to visualize the structure and function of tissues and / or organs in a subject, such as the body of a human or animal patient.

[0003] Typically, in a magnetic resonance device, rapidly switched gradient fields, generated by a gradient system of the magnetic resonance device, are superimposed on a static background magnetic field according to at least one detection pattern. These switching events are often also called gradient pulses.

[0004] Furthermore, high-frequency pulses (RF pulses) are radiated into the object under investigation by a high-frequency antenna unit of the magnetic resonance device, causing magnetization of the object. The temporal sequence of gradient pulses and RF pulses can be defined by a corresponding pulse sequence, often also referred to simply as the sequence. The pulse sequence is therefore particularly dependent on at least one acquisition pattern.

[0005] The magnetization process generates magnetic resonance signals, which can be detected using local coils and / or a whole-body coil. Magnetic resonance images can then be created from these detected signals.

[0006] German patent DE 10 2011 086 401 A1 discloses data acquisition in k-space with a distribution according to a spiral phyllotaxis. German patent DE 10 2014 203 068 A1 discloses spiral trajectories. German patent Steeden, JA [et al.]: Self-Navigated Tissue Phase Mapping Using a Golden-Angle Spiral Acquisition - Proof of Concept in Patients with Pulmonary Hypertension (2014), Vol. 71, pages 145-155 discloses a spiral acquisition according to the golden angle. German patent US 2007 / 0 255 130 A1 discloses a nested spiral trajectory for scanning in a plane. German patent US 5 892 358 A discloses a generalized spiral scan trajectory in k-space.

[0007] The present invention is intended to provide a method for generating at least one detection pattern, which is particularly suitable for tracking respiratory and / or cardiac movements.

[0008] The problem is solved by the features of the independent claims. Advantageous embodiments are described in the dependent claims.

[0009] Accordingly, a method for generating at least one acquisition pattern for acquiring magnetic resonance signals is proposed, wherein at least one acquisition pattern is generated using an acquisition pattern generation unit. This at least one acquisition pattern has several, i.e., two or more, spiral-like spokes in a k-space, with each spoke having several spiral points; that is, the multiple spiral points are typically located on said spokes in k-space.

[0010] The at least one detection pattern can be understood as an arrangement of detection points in a k-space, wherein the detection points comprise the multiple spiral points. A spoke can, in particular, be understood as a geometric object comprising several elements, especially spiral points, which preferably have different distances from the center point. Preferably, the spoke is not described by a straight line, but rather is spiral-shaped, i.e., the spiral points lie on a spiral. Preferably, the spiral comprises an angular range of less than 360°, i.e., the spiral completes less than one full rotation.

[0011] According to at least one acquisition pattern, magnetic resonance signals are preferably acquired using a magnetic resonance device. Images can be reconstructed from the acquired magnetic resonance signals, particularly for diagnostic purposes.

[0012] The k-space is sometimes also referred to as frequency space and / or spatial frequency space. Typically, the coordinates of k-space are encoded as a function of a gradient field. The gradient field generally modifies a resonance frequency and, in particular, the phase of a magnetization displaced by an RF pulse, depending on location. Thus, by identifying the phase and resonance frequency of the measured magnetic resonance signals, spatial information can be derived. By varying the gradient field, different points in k-space can be sampled. In this process, k-space is sampled completely or, preferably, partially.

[0013] The magnitude of the magnetization at a specific location of the object under investigation can be determined, in particular, using a Fourier transform. This transform typically calculates the signal strength in spatial space from the signal strength of the magnetic resonance signal, which is assigned to a specific frequency, namely the spatial frequency. In the case of only partial sampling, i.e., undersampling, of k-space, a direct Fourier transform is preferably not performed. Instead, a compressed sensing (CS) technique is used, for example. CS typically performs additional steps beyond the Fourier transform to compensate for information loss due to undersampling.

[0014] The k-space can thus be understood as an inverse Fourier space of the position space of the object under investigation, whereby the magnetic resonance signals can be transformed into the position space using a Fourier transform to create magnetic resonance images. The gradient field defines a point in k-space.

[0015] Advantageously, each spoke includes at least one spiral point in the center of k-space. The center of k-space typically contains the most important information about dynamic contrast changes, making the proposed method particularly well-suited for tracking respiratory and / or cardiac motion. In particular, it can enable self-navigation, eliminating the need for hemidiaphragmatic navigators, bellows, and / or external ECG signals.

[0016] Preferably, the spiral points of the spokes lie in a detection pattern plane of a three-dimensional k-space. The detection pattern plane can, for example, be a phase-coding plane, particularly a Cartesian one. The detection pattern can be used, in particular, for three-dimensional Cartesian acquisition of magnetic resonance signals.

[0017] Preferably, each spiral point is assigned a readout trajectory according to which the magnetic resonance signals are acquired, with each readout trajectory intersecting the acquisition pattern plane at the assigned spiral point. In particular, the multiple spiral points could be starting points for the readout trajectories.

[0018] A readout trajectory can be understood as a sequence of k-space points that describes the progression of a change in the gradient field. The acquisition pattern plane can, for example, be a k y / k z-plane of a three-dimensional k-space, in which the multiple spiral points lie, from where each extends into k x -Direction the selection trajectories run.

[0019] Preferably, each of the multiple spokes of a detection pattern has an offset corresponding to a golden angle relative to at least one other spoke of the same detection pattern. In particular, the starting points of the selection trajectories lie on a series of spiral spokes, each spoke having an offset of the golden angle relative to a previous spoke, i.e., the (n+1)th spoke is rotated by the golden angle relative to the nth spoke.

[0020] Under the golden angle φ golden In particular, an angle of φ can be golden,s =π (3-5 0,5 ) in radians and / or approximately φ golden,s ≈137.5° in the angular measure, which can also be called the small golden angle, and / or an angle of φgol-den,b =π (5 0,5 -1) in radians and / or approximately φ golden,b ≈222.5° can be understood as an angular measure, which can also be called the large golden angle. Repeated rotations around the golden angle result in positions that never exactly overlap. Furthermore, a rotation around the golden angle allows for a relatively uniform coverage of k-space, since the (n+1)th spoke lies approximately in the center of the largest area not yet covered by the previous n spokes.

[0021] In one embodiment of the method, the number of multiple spiral points per spoke is determined depending on a temporal resolution. The number of multiple spiral points can be derived, in particular, from a desired temporal resolution.

[0022] By using a small number of multiple spiral points, the time required to acquire the magnetic resonance signals according to at least one acquisition pattern can be kept short, thus enabling high temporal resolution.

[0023] If each spoke encompasses at least one point in the center of k-space, the temporal resolution can correspond to the time interval between repeated measurements of the k-space center. The fewer spiral points a spoke encompasses, the faster the measurement of the magnetic resonance signals associated with the spokes, and thus the repeated measurement of the k-space center, can typically be performed.

[0024] In one embodiment of the method, the number of spokes is determined based on a subscan. The number of spokes can be derived, in particular, from a desired subscan. Preferably, the number of spokes is determined after the number of multiple spiral points has been defined.

[0025] In contrast to a spiral phyllotactic scanning pattern, the number of spokes is not limited to a Fibonacci number, but can be any natural number.

[0026] In particular, the position of the multiple spiral points of a spoke can depend on the number of multiple spiral points per spoke N. p and / or a blur value ξ and / or an angle range value φ rotation and / or a golden angle φ golden and / or an angular offset value φ offset This allows the position of the multiple spiral points to be determined in a simple and efficient manner.

[0027] The angle offset value φ can be used. offset This represents an offset angle for all spokes. In particular, this allows all spokes of the same detection pattern to be offset by φ. offset to be rotated.

[0028] The angle range value φ rotation can describe an angular difference between the first and last spiral point of a spoke.

[0029] The blur value ξ is preferably randomized and / or chosen randomly. The blur value ξ can, for example, refer to a radial coordinate r and / or an angular coordinate φ. If the blur value ξ refers to the radial coordinate r, then the blur value can be expressed as ξ r The uncertainty value ξ can be denoted as ξ. If the uncertainty value refers to a radial coordinate φ, then the uncertainty value can be denoted as ξ. φ be designated.

[0030] The blur value can increase the irregularity of at least one acquisition pattern, making it particularly well-suited for compressed sensing techniques. Greater pattern irregularity can also be advantageous for direct reconstruction using Fourier transforms. For example, it is conceivable that with low undersampling, i.e., with nearly complete acquisition of k-space, high-quality magnetic resonance images can be generated even without compressed sensing techniques.

[0031] Calculating the position of a spiral point i (i∈[0,N] p [) of a single spoke s (s ∈ [0,N s [) can be expressed in polar coordinates r i,s and φ i,s for example, using the following formulas: ri,s=iNp−1+ξr,i,s φi,s=φrotation⋅1Np−1+s⋅φgolden+φoffset+ξφ,i,s

[0032] In particular, the uncertainty values ​​ξ r,i,s and / or ξ φ,i,s can also be omitted. ξ is preferred. r,i,s smaller than the radial distance between two consecutive points, for example 1 / (N p -1) according to the above formula (1). Analogously, ξ φ,i,s preferably smaller than the angular distance between two consecutive points, for example φ rotation / (N p -1) according to the above formula (2).

[0033] It is planned that the position of the multiple spiral points will be transformed from a polar coordinate system into a Cartesian coordinate system.

[0034] A polar coordinate system, also known as a circular coordinate system, is typically understood to be a coordinate system, especially a two-dimensional one, in which every point in a plane is defined by its distance from a given point and its angle to a given direction. The given point is usually called the pole. It generally corresponds to the origin in a Cartesian coordinate system. The distance from the pole is denoted, for example, by r and is called the radial coordinate and / or radius. The angle is denoted, for example, by φ and is called the angular coordinate and / or polar angle and / or azimuth.

[0035] A Cartesian coordinate system is usually understood to be an orthogonal coordinate system, especially a two-dimensional one.

[0036] The transformation depends on at least one dimension of an image area (field of view, FoV). Preferably, the transformation depends on a point density distribution.

[0037] The image area, in this context, can be understood as a region, particularly a two-dimensional one, within a k-space that corresponds to a representation of the object under investigation. This allows at least one acquisition pattern to be individually adapted to the desired investigation of the object.

[0038] The point density distribution can, for example, be understood as a distribution which determines a density of spiral points, in particular direction-dependent, depending on a distance to the center of k-space.

[0039] A conversion of polar coordinates r i,s and φ i,s in Cartesian coordinates y i,s and z i,s This can be done, for example, using the following formulas: yi,s=wy2⋅ri,s1 / vy⋅cos φi,s zi,s=wz2⋅ri,s1 / vy⋅sin φi,s

[0040] In this case, the extent of the image area is in the direction of the k y -axis of k-space through w y and in the direction of the k z -axis through w z The point density distribution is given in the direction of k. y -axis through v y and in the direction of the k z -axis through v z described.

[0041] Preferably, the position of the multiple spiral points is rasterized. This facilitates further processing and application of the at least one acquisition pattern, as it particularly enables a uniform Fourier transform.

[0042] A grid can be understood as the mapping of multiple spiral points to grid points of a grid in k-space. These grid points can be considered potential sampling points; that is, if a spiral point is mapped to a grid point, this point can be called a sampling point. A grid in k-space can be understood as a multidimensional, particularly two-dimensional, arrangement. For example, a two-dimensional grid can be defined by two k-space axes, e.g., a k y -axis and a k z The k-axis can be spanned. The k-space axes can be divided into lattice coordinates, i.e., the k-space axes can be discretized. This results, in the case of a two-dimensional lattice, in lattice points, each defined by two lattice coordinates, e.g., a k-axis. y -Grid coordinate and a k z -coordinate can be set.

[0043] The rasterization can be described, for example, by the following formulas: y˜i,s=round(yi,s) z˜i,s=round(zi,s)

[0044] In another embodiment of the method, an anisotropic image area correction is performed.

[0045] An anisotropic image region is usually present if the image region is symmetrical in one direction, e.g., k. z , has a different extent than in another direction, e.g. k y This typically stretches and / or compresses at least one of the capture patterns, which was originally generated isotropically on a unit circle, into an ellipse. Consequently, undersampling would be greater in the direction of the larger extent than in the direction of the smaller extent. This effect can be compensated for by anisotropic image area correction.

[0046] Preferably, in anisotropic image area correction, angular ranges of equal length of the original angular coordinates correspond to arc lengths of equal length of the corrected angular coordinates.

[0047] In particular, a first and a second original angular coordinate enclose a first angular range, and the second and a third original angular coordinate enclose a second angular range. The first and second angular ranges are of equal size. Preferably, the first and third angular coordinates are not identical. Furthermore, preferably, a first corrected angular coordinate is assigned to the first original angular coordinate, a second corrected angular coordinate to the second original angular coordinate, and a third corrected angular coordinate to the third original angular coordinate. The first and second corrected angular coordinates define a first arc length, and the second and third corrected angular coordinates define a second arc length, with the first and second arc lengths being of equal length.

[0048] In particular, anisotropic image area correction involves inverting the mapping of uniformly sampled polar angles to corresponding segment lengths on the circumference of an image area ellipse. For this purpose, an incomplete elliptic integral of the second kind E(φ), which is applied to the complete integral E complete Normalized over the entire ellipse, angles φ can be calculated numerically for uniformly distributed angles in the range [0,2π[. This can be described by the following formulas: E(φ')=2πEcomplete⋅∫0φ'1−k2sin2θ dθ k=1−(wzwy)2

[0049] In anisotropic image area correction, a corrected angular coordinate φ' is preferably assigned to an original angular coordinate φ of a spiral point s. This assignment can be made using a mapping table.

[0050] The assignment can be made, for example, by φ'=E -1(φ) from which the assignment table can be derived. This correction can be substituted into equations (3) and (4) by substituting the original angle φ. i,s by E -1 (φ) is replaced. For an isotropic case with w y =w z The inverse assignment yields the identity ö=E -1 (φ).

[0051] Another embodiment of the method involves checking the position of at least one of the several spiral points for duplication. Advantageously, the duplication check is performed after any anisotropic image area correction.

[0052] A direct duplication of a position exists in particular when two or more spiral points in k-space lie on the same lattice point.

[0053] When checking for duplicity, symmetry properties of k-space are preferably taken into account. For example, it is checked whether two or more spiral points in k-space lie on reflected lattice points, especially those reflected about the center of k-space. In this case, one can speak of a reflected duplicity.

[0054] Advantageously, duplication, especially direct and / or mirrored duplication, is avoided. Therefore, if duplication is present, at least one alternative position is preferably sought.

[0055] Preferably, the search for alternative positions is limited by a search radius. This allows for an efficient search. Furthermore, limiting the search radius ensures that a potential shift of a spiral point does not lead to large jumps in the gradient magnetic field. This prevents any resulting artifacts in reconstructed magnetic resonance images.

[0056] The search radius advantageously defines the area around an original grid point, for which duplicity exists, in which alternative grid points are searched for. For example, the search only considers grid points that are parallel to a grid axis, in particular to k. y -axis and / or k z -axis, and / or diagonally, in particular parallel to an angle bisector of k y - and k z -axis, directly adjacent to the original grid point.

[0057] Preferably, if at least two alternative positions are found, one of the at least two alternative positions is randomly assigned as the new position, i.e., the assignment of the new position is randomized.

[0058] For example, a preliminary sampling pattern can first be generated for each of the at least one sampling pattern and checked for duplicates. In particular, this allows any identical and / or mirrored sampling points of the at least one preliminary sampling pattern to be identified. As already explained, the sampling points can be randomly shifted to adjacent grid points. This process can be iterative and can be terminated, for example, when no more identical and / or mirrored sampling points exist or when all adjacent grid points are already occupied.

[0059] This makes it possible, in particular, to maximize a completely sampled, especially rectangular, area of ​​k-space across the multiple acquisition patterns, which is usually located in the center of k-space.

[0060] By avoiding duplication, especially randomized determination of new positions, the incoherence of at least one detection pattern can advantageously be increased.

[0061] Another embodiment of the method provides for the generation of multiple, i.e., at least two, acquisition patterns. Multiple acquisition patterns are particularly advantageous for time-resolved measurements. Time-resolved measurements can be understood, in particular, as dynamic measurements that, for example, depict a movement of the object under investigation and / or within the object under investigation.

[0062] For example, a first capture pattern can be applied at a first time point and another capture pattern at a further time point, i.e. a first capture pattern is assigned to a first time point, a second capture pattern to a second time point, and so on.

[0063] The time points can be absolute and / or relative. If the recording patterns are assigned to absolute time points, then usually the respective recording pattern is recorded in its entirety, i.e., first a complete first recording pattern at a first absolute time point, then a complete second recording pattern at a second absolute time point, and so on.

[0064] Relative time points generally refer to points in time within a periodically repeating process, such as heartbeats and / or breathing movements. For example, at a first relative time point, a spoke of a first recording pattern might be recorded, then at a second relative time point, a spoke of a second recording pattern, and so on. Subsequently, at the first relative time point again, a second spoke of the first recording pattern would be recorded, then at the second relative time point, a second spoke of the second recording pattern, and so on.

[0065] For example, when recording different cardiac phases over several heartbeats with ECG triggering, after each R-wave of the ECG signal, a spoke of the first recording pattern is captured, then a spoke of the second recording pattern, and so on. This process is repeated accordingly with the next R-wave. In this way, one cardiac phase can be recorded with each recording pattern. A relative point in time can therefore be understood, in particular, as a phase of a periodic process.

[0066] Preferably, a spoke of one, and in particular each, of the multiple acquisition patterns has an offset by a golden angle relative to a spoke of another of the multiple acquisition patterns. This allows for uniform scanning of k-space, especially over time in time-resolved measurements.

[0067] The offset of the spokes between the multiple detection patterns can be determined in particular using an angular offset value φ. off-set,p a detection pattern t is described. Here, t is preferably a natural number including zero with t∈[0,T[, where T is the number of multiple detection patterns. The angular offset value φ offset,t The angle offset value φ of a detection pattern t can be determined. offset Substitute into equation (2).

[0068] The angle offset value φ offset,p The pattern of a recording p can be expressed, for example, with the following formula: φoffset,t=t⋅Ns⋅φgolden

[0069] This ensures that the first spoke of the detection pattern t is offset from the last spoke of the detection pattern t-1 by the golden angle. This allows each spoke to be unique compared to all other spokes of all detection patterns.

[0070] The duplicity check, which has already been explained, can of course also be applied analogously to the spokes of at least some of the multiple, and especially all, acquisition patterns when there is more than one acquisition pattern. This ensures that no and / or as few identical and / or mirrored sampling points occur across all phases.

[0071] Furthermore, a detection pattern generation unit is proposed, which is configured to execute a method for generating at least one detection pattern for the detection of magnetic resonance signals. The detection pattern generation unit can, in particular, comprise one or more processors and / or a memory.

[0072] The advantages of the device according to the invention for generating at least one detection pattern for acquiring magnetic resonance signals correspond essentially to the advantages of the method according to the invention for generating at least one detection pattern for acquiring magnetic resonance signals, which are described in detail below. Features, advantages, or alternative embodiments mentioned here can also be transferred to the other claimed subject matter and vice versa.

[0073] The pattern generation unit can be designed to be integrated into a magnetic resonance device and / or include a data interface configured to transmit data to a magnetic resonance device. It is also conceivable that the pattern generation unit operates independently of a magnetic resonance device.

[0074] Furthermore, a magnetic resonance device with a detection pattern generation unit is proposed, which is configured to perform a method for generating at least one detection pattern for detecting magnetic resonance signals. The magnetic resonance device can, for example, include a system control unit for controlling the magnetic resonance device, which in turn includes the detection pattern generation unit.

[0075] Furthermore, a computer program product is proposed that comprises a program which can be directly loaded into the memory of a programmable computing unit of a magnetic resonance acquisition unit (MRA) and includes program resources, such as libraries and auxiliary functions, to execute a method for generating at least one MRA for acquiring magnetic resonance signals when the computer program product is executed in the MRA. The computer program product may comprise software with source code that still needs to be compiled and bound or that only needs to be interpreted, or executable software code that only needs to be loaded into the MRA for execution. The computer program product enables the method for generating at least one MRA for acquiring magnetic resonance signals to be executed quickly, identically, and robustly.The computer program product is configured to execute the process steps according to the invention using the acquisition pattern generation unit. The acquisition pattern generation unit must possess the necessary components, such as sufficient main memory, a suitable graphics card, or a suitable logic unit, to enable the efficient execution of the respective process steps.

[0076] The computer program product is, for example, stored on a computer-readable medium or on a network or server, from where it can be loaded into the processor of a local acquisition pattern generation unit. This processor can be directly connected to the acquisition pattern generation unit or be designed as part of the acquisition pattern generation unit. Furthermore, control information of the computer program product can be stored on an electronically readable data carrier. The control information of the electronically readable data carrier can be configured such that, when the data carrier is used in an acquisition pattern generation unit, it performs a method according to the invention. Examples of electronically readable data carriers are a DVD, a magnetic tape, or a USB flash drive on which electronically readable control information, in particular software, is stored.If this control information is read from the data carrier and stored in a pattern generation unit, all embodiments of the methods described above can be carried out according to the invention. Thus, the invention can also be based on the aforementioned computer-readable medium and / or the aforementioned electronically readable data carrier.

[0077] Further advantages, features and details of the invention will become apparent from the exemplary embodiments described below and from the drawings.

[0078] They show: Fig. 1 a magnetic resonance device according to the invention in a schematic representation, Fig. 2 a block diagram of a variant of the method according to the invention, Fig. 3 a block diagram of a possible embodiment of a step of the method according to the invention, Fig. 4. A schematic diagram of how to generate spiral points. Fig. 5. A representation of a recording pattern, Fig. 6. A representation of several recording patterns, Fig. 7 a representation of a capture pattern before anisotropic image area correction, Fig. 8 a representation of a capture pattern after anisotropic image area correction, Fig. 9 a schematic diagram for an anisotropic image area correction, Fig. 10 a representation of an assignment table for an anisotropic image area correction, Fig. 11. A schematic diagram for checking the position of a spiral point for duplicity and searching for alternative positions.

[0079] In Fig. Figure 1 schematically depicts a magnetic resonance imaging (MRI) device 10. The MRI device 10 comprises a magnetic unit 11, which includes a superconducting main magnet 12 for generating a strong and, in particular, constant main magnetic field 13. The MRI device 10 also has a patient receiving area 14 for receiving a patient 15. In the present embodiment, the patient receiving area 14 is cylindrical and is surrounded in a cylindrical shape by the magnetic unit 11 in one circumferential direction. However, a different configuration of the patient receiving area 14 is conceivable. The patient 15 can be moved into the patient receiving area 14 by means of a patient positioning device 16 of the MRI device 10. For this purpose, the patient positioning device 16 has a patient table 17 that is movably designed within the patient receiving area 14.

[0080] The magnet unit 11 further comprises a gradient coil unit 18 for generating magnetic field gradients, which are used for spatial encoding during imaging. The gradient coil unit 18 is controlled by a gradient control unit 19 of the magnetic resonance device 10. The magnet unit 11 also includes a high-frequency antenna unit 20, which in the present embodiment is designed as a body coil permanently integrated into the magnetic resonance device 10. The high-frequency antenna unit 20 is designed to excite a magnetization that arises in the main magnetic field 13 generated by the main magnet 12.The high-frequency antenna unit 20 is controlled by a high-frequency antenna control unit 21 of the magnetic resonance device 10 and emits RF pulses, in particular excitation pulses and / or refocusing pulses, according to a predetermined pulse sequence into an examination space, which is essentially formed by a patient acquisition area 14 of the magnetic resonance device 10. The high-frequency antenna unit 20 is further configured to receive magnetic resonance signals.

[0081] The magnetic resonance device 10 includes a system control unit 22 for controlling the main magnet 12, the gradient control unit 19, and the high-frequency antenna control unit 21. The system control unit 22 centrally controls the magnetic resonance device 19, for example, by executing the pulse sequence. To generate the pulse sequence, the system control unit advantageously includes a detection pattern generation unit 26 configured to perform a method for generating at least one detection pattern for acquiring magnetic resonance signals. The detection pattern generation unit 26 can, in particular, comprise a programmable computing unit (not shown here) which, in particular, has one or more processors and / or a memory.

[0082] A program can be loaded into the memory of the programmable computing unit, containing program means to execute a procedure for generating at least one acquisition pattern for acquiring magnetic resonance signals when the program is executed in the computing unit.

[0083] Furthermore, the system control unit 22 includes an evaluation unit (not shown) for evaluating medical image data acquired during the magnetic resonance examination. The magnetic resonance device 10 also includes a user interface 23, which is connected to the system control unit 22. Control information, such as imaging parameters, as well as reconstructed magnetic resonance images, can be displayed on a display unit 24, for example, on at least one monitor, of the user interface 23 for medical personnel. The user interface 23 also includes an input unit 25, by means of which information and / or parameters can be entered by the medical personnel during a measurement procedure.

[0084] In Fig. Figure 2 presents an exemplary method for generating at least one acquisition pattern for acquiring magnetic resonance signals. In step 110, at least one acquisition pattern with multiple spiral points is generated using the acquisition pattern generation unit 26. This is a preliminary acquisition pattern, as an anisotropic image area correction is performed in a subsequent step 120. After the anisotropic image area correction, the positions of the multiple spiral points are checked for duplicity and corrected if necessary in step 130.

[0085] The checking and correction of the positions of the multiple spiral points in step 130 is preferably carried out taking into account all previously generated detection patterns, i.e. if more than one detection pattern is generated in step 110, the spiral points of each detection pattern are not considered individually in step 130, but together.

[0086] In Fig. Step 110 is shown broken down into further sub-steps. In step 111, spiral points are first generated, arranged on spiral-like spokes. Examples are shown in... Fig. Figure 4 shows three spokes s0, s1, s2, each with fourteen spiral points, which are exemplified for spoke s0 by being labeled i0,0, i1,0, i2,0, i3,0, i4,0, i15,0, i6,0, i7,0, i8,0, i9,0, i10,0, i11,0, i12,0, i13,0. The spoke s0 is offset relative to spoke s1, and the spoke s1 is offset relative to spoke s2 by the golden angle φ. golden on.

[0087] The position of the spiral points i depends here on a number of spiral points per spoke N. p , an angle range value φ rotation , the golden angle φ golden , an angular offset value φ offset and an uncertainty value ξ calculated according to equations (1) and (2), where φ offset =ξ=0 was chosen.

[0088] In step 112, the position of the spiral points is transformed from a polar coordinate system to a Cartesian coordinate system. This is done, for example, using equations (3) and (4), where the transformation depends on at least one extent of an image region and / or at least one point density. In step 113, the position of the multiple spiral points is rasterized. This is done, for example, using equations (5) and (6).

[0089] Anisotropic image area correction is achieved through the Fig. 7, Fig. 8, Fig. 9 to Fig. 10 illustrated. Thus, in Fig. 7 in an uncorrected capture pattern 700 in a k y / k z -plane of a k-space is represented, along with an associated histogram showing the distribution of spiral points along the k yThe -axis shows a strong uneven distribution of the spiral points. To reduce this uneven distribution, anisotropic image area correction is performed, resulting in the corrected acquisition pattern 800, which is shown in Fig. 8 is shown.

[0090] One possible principle of anisotropic image area correction is described in Fig. Figure 9 illustrates this. On the left, an (isotropic) unit circle is depicted, on which eight original points P0, P1, P2, P3, P4, P5, P6, and P7 are plotted. Each of these original points can be assigned an original angular coordinate; for example, point P1 is assigned the angular coordinate α1, point P2 the angular coordinate α2, and point P0 the angular coordinate α0 = 0 (not shown here). The original angular coordinates α0 and α1 enclose a first angular range of size δ. The original angular coordinates α1 and α2 enclose a second angular range of the same size as the first angular range δ.

[0091] On the right-hand side, an ellipse transformed from the unit circle (anisotropic) is shown, compressed by an anisotropy factor W / W'. The original points P0, P1, P2, P3, P4, P5, P6, P7 are then corrected to P0', P1', P2', P3', P4', P5', P6', P7. The corrected point P0' is described by a first corrected angular coordinate α0'=0 (not shown here), similarly P1' by a second corrected angular coordinate α1', and P2' by a third corrected angular coordinate α2'. The first and second corrected angular coordinates α0', α1' define a first arc length, and the second and third corrected angular coordinates α1', α2' define a second arc length, with the first and second arc lengths each having the same length Δ.

[0092] Following this principle, a corrected angular coordinate α' can be assigned to an original angular coordinate α, thus correcting the acquisition pattern with an anisotropic image area correction. Advantageously, this is done using a mapping table, such as the one for an exemplary anisotropy factor in Fig. Figure 10 is shown. This mapping table thus allows for the mapping of uniform polar angles to uniform elliptical segment lengths.

[0093] In Fig. Figure 11 illustrates a check for duplicity of the position of at least one of the multiple spiral points. Here, k-space 200 is rasterized by a grid 210, meaning the multiple spiral points lie on grid points of grid 210. In this example, grid point 201 with the coordinates (k y ,k z )=(3,3) can be checked for duplicity.

[0094] In this example, let's assume that grid points 203 are already occupied, i.e., they are already being sampled by spiral points. The check therefore reveals that the grid point (3,3) to be checked is already occupied, i.e., it is already being sampled by another spiral point.

[0095] Consequently, a duplication exists here, so an alternative location is sought. This search is limited by a search radius of 202, meaning that only directly adjacent grid points are considered in this case. Parallel to k y -axis, these are the grid points (2,3) and (4,3), parallel to the k y -axis, these are the grid points (3,2) and (3,4), parallel to an angle bisector of k y - and k z The -axis these are the grid points (2,4) and (4,2) as well as (2,2) and (4,4).

[0096] Just like the point (3,3), the grid points (2,3) and (4,3) are eliminated in this search, as they are already occupied. When checking for duplicity, symmetry properties of k-space 200 are taken into account, for example, when applying a partial Fourier method. In particular, when searching for alternative positions, those grid points whose point-reflected grid points 204 across the center 206 of k-space are already occupied are eliminated. The grid points 205 remain as candidates for an alternative position. One of these, e.g., (3,4), is randomly selected as the new grid point.

[0097] Fig. Figure 5 shows an example of a detection pattern 220 that can result from an embodiment of the proposed method. Here, the detection pattern has eight spokes s0, s1, s2, s3, s4, s5, s6, s7, each with fourteen spiral points. However, more than one detection pattern can also be generated, as shown by way of example in Figure 5. Fig. Figure 6 is shown. By using suitable offset angles between each detection pattern, the spokes can be evenly distributed over the k-space 200 and no spoke is advantageously scanned more than once.

[0098] In particular, spoke s8 of the recording pattern 230 is offset by the golden angle relative to spoke s7 of the recording pattern 220. Furthermore, spoke s16 of the recording pattern 240 is also offset by the golden angle relative to spoke s15 of the recording pattern 230.

[0099] Finally, it should be noted once again that the methods described in detail above, as well as the depicted pattern generation unit and magnetic resonance device, are merely exemplary embodiments which can be modified in various ways by those skilled in the art without departing from the scope of the invention. Furthermore, the use of the indefinite articles "a" or "an" does not preclude the possibility that the features in question may be present multiple times. Likewise, the term "unit" does not preclude the possibility that the components in question consist of several interacting sub-components, which may also be spatially distributed.

Claims

[1] Method for generating at least one detection pattern for the detection of magnetic resonance signals, wherein at least one capture pattern is generated with a capture pattern generation unit, where at least one detection pattern has several spiral-like spokes in a k-space, where each spoke has several spiral points, where the position of the multiple spiral points is transformed from a polar coordinate system into a Cartesian coordinate system, where the transformation depends on at least one dimension of an image area. [2] Method according to claim 1, wherein at least one of the spiral points of each spoke lies in the center of k-space. [3] Method according to claim 2, wherein the spiral points of the spokes lie in a detection pattern plane of a three-dimensional k-space. [4] Method according to any of the preceding claims, wherein each spiral point is assigned a readout trajectory according to which the magnetic resonance signals are acquired, wherein each readout trajectory intersects the acquisition pattern plane at the assigned spiral point. [5] Method according to any of the preceding claims, wherein each of the multiple spokes of a detection pattern has an offset by a golden angle relative to at least one further spoke of the same detection pattern. [6] Method according to one of the preceding claims, wherein the number of multiple spiral points per spoke is determined depending on a temporal resolution. [7] Method according to any of the preceding claims, wherein a number of spokes is determined depending on a subscan. [8] Method according to one of the preceding claims, wherein the position of the multiple spiral points of a spoke depends on a number of spiral points per spoke and / or a fuzzyness value and / or an angle range value and / or a golden angle and / or an angle offset value. [9] Method according to any of the preceding claims, wherein the transformation depends on at least one point density. [10] Method according to one of the preceding claims, wherein the position of the multiple spiral points is rasterized. [11] Method according to any of the preceding claims, wherein an anisotropic image area correction is performed. [12] Method according to claim 11, where a first and a second original angular coordinate enclose a first angular range, where the second and a third original angular coordinate enclose a second angular range, where the first and second angle ranges are of equal size, where the first original angular coordinate is assigned a first corrected angular coordinate, the second original angular coordinate a second corrected angular coordinate, and the third original angular coordinate a third corrected angular coordinate. wherein a first and the second corrected angular coordinate define a first arc length and the second and the third corrected angular coordinate define a second arc length, where the first and the second arc lengths are of equal length. [13] Method according to one of claims 11 or 12, wherein a corrected angular coordinate is assigned to an original angular coordinate of a spiral point. [14] Method according to any one of claims 11 to 13, wherein the assignment is carried out using an assignment table. [15] Method according to one of the preceding claims, wherein the position of at least one of the multiple spiral points is checked for duplicity. [16] Method according to claim 15, wherein symmetry properties of k-space are taken into account. [17] Method according to one of claims 15 or 16, wherein, in the case of duplicity, at least one alternative position is sought. [18] Method according to claim 17, wherein the search for alternative locations is limited by a search radius. [19] Method according to one of claims 17 or 18, wherein, when at least two alternative positions are found, one of the at least two alternative positions is randomly selected. [20] Method according to any of the preceding claims, wherein multiple detection patterns are generated. [21] Method according to claim 20, wherein a spoke of one of the multiple detection patterns has an offset by a golden angle relative to a spoke of another detection pattern. [22] Pattern generation unit comprising means configured to perform a method according to any one of claims 1 to 21. [23] Magnetic resonance device with a detection pattern generation unit according to claim 22. [24] Computer program product comprising a program that can be directly loaded into a memory of a programmable computing unit of a pattern generation unit, comprising programming means to execute a method according to any one of claims 1 to 21 when the program is executed in the computing unit of the pattern generation unit.

Images