Magnetic resonance equipment active noise reduction method based on sequence electromagnetic interference sampling

Abstract

The invention relates to a magnetic resonance equipment active noise reduction method based on sequence electromagnetic interference sampling, and belongs to the technical field of nuclear magnetic resonance. According to the method, an extra electromagnetic interference sampling imaging sequence is adopted, that is, after magnetic resonance signals are collected during sequence operation, electromagnetic interference signals are collected at the remaining repetition time, so that two sets of k-space data are obtained at the same time, and the k-space data are the magnetic resonance signal k-space data and the electromagnetic interference k-space data respectively. And calculating a correlation coefficient matrix by adopting a least square method or a neural network. And for fixed-frequency interference or residual electromagnetic interference signals due to correlation insufficiency, filtering by adopting a transform domain subtraction mode, i.e., subtracting the magnetic resonance signal k space after active noise reduction and the electromagnetic interference k space in a transform domain so as to eliminate electromagnetic interference in a specific mode. According to the invention, the electromagnetic interference signal in the magnetic resonance radio frequency receiving coil can be effectively filtered.

Description

Technical Field

[0001] The invention belongs to the technical field of nuclear magnetic resonance and relates to an active noise reduction method for magnetic resonance equipment based on sequential electromagnetic interference sampling. Background Art

[0002] In the application of low-field magnetic resonance imaging systems, a large and closed RF shield is often required to eliminate external electromagnetic interference signals during scanning in order to obtain good image quality. However, such shields not only require strict installation and a large footprint, but are also difficult to use in bedside magnetic resonance imaging (such as in intensive care units and operating rooms).

[0003] The existing active noise reduction methods for mobile low-field magnetic resonance imaging systems rely heavily on the correlation between the noise detection channel and the RF receiving coil. That is, when a single or several noise detection channels cannot detect or fit the synchronous electromagnetic interference signal in the receiving coil, the active noise reduction system cannot work properly. For electromagnetic interference signals of fixed frequency, although the traditional active noise reduction algorithm based on least squares fitting can eliminate the interference signal to a certain extent, the image artifacts introduced by the fixed frequency electromagnetic interference can still be observed in the reconstructed image. For electromagnetic interference signals of multiple frequencies, the traditional active noise reduction algorithm calculates the channel correlation coefficient through the edge k-space signals (including a small amount of magnetic resonance signals) of the receiving coil and the noise detection coil, and then eliminates the electromagnetic interference signal in the receiving coil through the k-space signals of the remaining noise detection coils. However, it is not the best practice to express the correlation between coils through the correlation coefficient obtained from a small amount of data. At the same time, the traditional method often fails when the correlation between coils is poor.

[0004] Therefore, there is an urgent need for a new active noise reduction method that can be used in mobile low-field magnetic resonance imaging systems to solve the above problems. Summary of the invention

[0005] In view of this, the purpose of the present invention is to provide an active noise reduction method for a magnetic resonance device based on sequential electromagnetic interference sampling, which adopts a noise detection coil combined with an additional electromagnetic interference sampling method in an imaging sequence to achieve effective filtering of electromagnetic interference signals in a magnetic resonance radio frequency receiving coil.

[0006] In order to achieve the above object, the present invention provides the following technical solutions:

[0007] A method for active noise reduction of a magnetic resonance device based on sequential electromagnetic interference sampling specifically comprises the following steps:

[0008] S1: using an additional electromagnetic interference sampling imaging sequence, specifically: using a single radio frequency receiving coil and a multi-channel noise detection coil, after collecting magnetic resonance signals during the sequence running, using the remaining repetition time TR to collect electromagnetic interference signals, so as to simultaneously obtain two sets of k-space data, namely, magnetic resonance signal k-space data and electromagnetic interference k-space data, and calculate the correlation coefficient matrix of the two space data;

[0009] S2: combining the k-space data of the magnetic resonance signal detected by the noise detection coil and the k-space data of the electromagnetic interference with the correlation coefficient matrix, and calculating the electromagnetic interference signal I and the electromagnetic interference signal II in the radio frequency coil;

[0010] S3: Subtract the magnetic resonance signal k-space data and electromagnetic interference k-space data collected by the RF receiving coil from the previously obtained electromagnetic interference signal I and electromagnetic interference signal II, respectively, to obtain preliminary denoised k-space data and residual electromagnetic interference signal; and perform subtraction in the transform domain, and then obtain the final denoised k-space data through inverse transformation.

[0011] Furthermore, in step S1, the correlation coefficient matrix of the two spatial data is obtained by adopting the least square method or the neural network training method.

[0012] Further, in step S1, the least square method in the frequency domain is used to calculate the correlation coefficient to obtain the relationship between the RF receiving and noise detection coils; assuming that the number of noise detection coils is C and the number of sub-bands is f, the transfer coefficient matrix between each noise channel and the RF receiving channel is This can be achieved by the least squares method in the complex field:

[0013]

[0014] in, are the electromagnetic interference k-space data (f-th sub-band) collected by the c-th channel noise detection coil and the RF receiving coil, respectively. N is the number of sampling points. The superscripts “H” and “-1” represent conjugate transpose and inverse matrix operations, respectively.

[0015] Further, step S3 specifically includes: after obtaining the transfer coefficient of the system Afterwards, the electromagnetic interference in the magnetic resonance signal k-space can be obtained through the transfer coefficient matrix Suppression; frequency domain magnetic resonance signal after noise reduction It can be expressed as:

[0016]

[0017] in, The k-space data (f-th sub-band) of the magnetic resonance signal collected by the noise detection coil of the c-th channel and the radio frequency receiving coil are respectively; the time domain magnetic resonance signal is finally obtained by inverse Fourier transform;

[0018] The residual electromagnetic interference signal can also be calculated by the above method.

[0019] The beneficial effects of the present invention are:

[0020] (1) The present invention adopts an imaging sequence with additional electromagnetic interference sampling, and completes the sampling of the magnetic resonance signal k-space and the electromagnetic interference k-space by destroying the gradient after the magnetic resonance echo sampling is completed while keeping the total imaging time unchanged.

[0021] (2) The present invention utilizes electromagnetic interference filtering based on transform domain subtraction, and utilizes the similarity of electromagnetic interference characteristics in the magnetic resonance signal k-space and the electromagnetic interference k-space to perform a difference between the two groups of k-space signals in the transform domain to eliminate residual electromagnetic interference artifacts.

[0022] Other advantages, objectives and features of the present invention will be described in the following description to some extent, and to some extent, will be obvious to those skilled in the art based on the following examination and study, or can be taught from the practice of the present invention. The objectives and other advantages of the present invention can be realized and obtained through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to make the purpose, technical solutions and advantages of the present invention more clear, the present invention will be described in detail below in conjunction with the accompanying drawings, wherein:

[0024] Figure 1 It is a schematic diagram of the structure of a mobile unshielded low-field magnetic resonance imaging system;

[0025] Figure 2 for imaging sequences with additional EMI sampling;

[0026] Figure 3 This is a flow chart of an active noise reduction algorithm for magnetic resonance equipment based on sequential electromagnetic interference sampling according to the present invention;

[0027] Figure 4 This is a comparison chart of the active noise reduction algorithms. DETAILED DESCRIPTION

[0028] The following describes the embodiments of the present invention by specific examples, and those skilled in the art can easily understand other advantages and effects of the present invention from the contents disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the illustrations provided in the following embodiments only illustrate the basic concept of the present invention in a schematic manner, and the following embodiments and features in the embodiments can be combined with each other without conflict.

[0029] See also Figure 1 to Figure 4 The present invention proposes an active noise reduction method for magnetic resonance equipment based on sequence electromagnetic interference sampling. First, a scheme of sequence additional electromagnetic interference sampling is adopted, that is, after collecting magnetic resonance signals during sequence operation, the electromagnetic interference signals are collected using the remaining repetition time (TR) to simultaneously obtain two sets of k-space data (magnetic resonance signal k-space and electromagnetic interference k-space). At this time, the correlation between coils can be calculated by the complete electromagnetic interference k-space data collected by the receiving coil and the noise detection coil. Then, the correlation coefficient matrix is ​​calculated by the least square method or the combination of neural networks. Furthermore, for fixed frequency interference or residual electromagnetic interference signals due to insufficient correlation, the transform domain subtraction method is used to filter them out, that is, the magnetic resonance signal k-space after active noise reduction and the electromagnetic interference k-space are subtracted in the transform domain to eliminate the electromagnetic interference of a specific mode.

[0030] The structure of the mobile unshielded low-field magnetic resonance imaging system used in the method of the present invention is as follows: Figure 1 As shown in the figure, the system mainly includes the main magnet, coils, peripheral equipment and mechanical support structure. The main magnet part mainly includes a bipolar magnet to generate a 50mT background main magnetic field and other auxiliary components (pole shoes, anti-eddy current plates, shim rings, etc.). The coil part includes RF transmitting and receiving coils to achieve the excitation and detection of magnetic resonance signals; gradient coils, which are used for spatial encoding of signals and shim field in imaging; noise detection coils ( Figure 1 Only one is drawn in the figure), which is used to detect electromagnetic interference in space. Peripheral equipment includes RF power amplifier, gradient power amplifier, magnetic resonance imaging spectrometer and RF receiving amplifier module (including coil matching circuit, preamplifier and other circuits). The system is powered by 220V / 50Hz AC power. After the sequence parameters are set, the imaging spectrometer controls the RF and gradient power amplifiers to stimulate the hydrogen proton signals in the imaging area to generate spatially encoded magnetic resonance signals; at the same time, the RF receiving and noise detection coils send the detection signals to the imaging spectrometer through the RF receiving module, and finally complete the signal processing and image reconstruction in the computer.

[0031] The imaging sequence of additional electromagnetic interference sampling used in the embodiment of the present invention is as follows: Figure 2As shown in the figure, taking the three-dimensional gradient echo sequence with spoiled gradient as an example, after collecting the echo signal, the RF receiving coil applies spoiled gradient in advance through the gradient coil to disperse the remaining magnetic resonance signal, and then samples the additional electromagnetic interference signal once in the remaining repetition time TR (excluding the magnetic resonance signal). For a single RF receiving coil or noise detection coil, two sets of k-space data are obtained after the sequence is completed, namely the magnetic resonance signal k-space and the electromagnetic interference k-space, as shown in Figure 2 The same electromagnetic interference sampling method can also be applied to imaging sequences with longer TR times, such as three-dimensional fast spin echo sequences.

[0032] After completing the acquisition of two sets of k-space data, the active noise reduction algorithm based on additional electromagnetic interference sampling proposed in the present invention is as follows: Figure 3 As shown. The algorithm first uses the electromagnetic interference k-space data collected by the multi-channel (1-N) noise detection coil and the RF receiving coil to obtain the correlation coefficient matrix by the least square method or neural network training. Then, the magnetic resonance signal k-space data detected by the noise detection coil and the electromagnetic interference k-space data are combined with the correlation coefficient matrix to calculate the electromagnetic interference signal 1 and electromagnetic interference signal 2 in the RF coil (such as Figure 3 As shown). Further, the magnetic resonance signal k-space data and electromagnetic interference k-space data collected by the RF receiving coil are subtracted from the previously obtained electromagnetic interference signal 1 and electromagnetic interference signal 2, respectively, to obtain the preliminary noise-reduced k-space data and residual electromagnetic interference signal. Finally, the two sets of signals are subtracted in the transform domain and then inversely transformed to obtain the final noise-reduced k-space data.

[0033] Taking the calculation of k-space data after preliminary noise reduction as an example, the least squares method in the frequency domain is used to calculate the correlation coefficient matrix TF to obtain the relationship between the RF receiving and noise detection coils. Without loss of generality, assuming that the number of noise detection coils is C and the number of sub-bands is f, the transfer coefficient matrix TF of each noise channel and the RF receiving channel is c f This can be achieved by the least squares method in the complex field:

[0034]

[0035] in, are the electromagnetic interference k-space data (f-th sub-band) collected by the c-th channel noise detection coil and the RF receiving coil, respectively. N is the number of sampling points. The superscripts “H” and “-1” represent conjugate transpose and inverse matrix operations, respectively.

[0036] In order to obtain the transfer coefficient of the system After that, the electromagnetic interference in the nuclear magnetic signal k-space can be Suppression. Frequency domain magnetic resonance signal after noise reduction It can be expressed as:

[0037]

[0038] in, The k-space data (f-th sub-band) of the nuclear magnetic resonance signal collected by the noise detection coil of the c-th channel and the radio frequency receiving coil are respectively obtained. The time domain magnetic resonance signal is finally obtained by inverse Fourier transform. The residual electromagnetic interference signal can also be calculated by the above method.

[0039] Comparison algorithm effect Figure 4 As shown, compared with the traditional active noise reduction method, the algorithm of the present invention can more effectively remove the highlight artifacts in the image.

[0040] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the purpose and scope of the technical solution, which should be included in the scope of the claims of the present invention.

Claims

1. A method for active noise reduction of magnetic resonance equipment based on sequential electromagnetic interference sampling, characterized in that: The method specifically comprises the following steps: S1: using an additional electromagnetic interference sampling imaging sequence, specifically: using a single radio frequency receiving coil and a multi-channel noise detection coil, after collecting magnetic resonance signals during the sequence running, using the remaining repetition time TR to collect electromagnetic interference signals, so as to simultaneously obtain two sets of k-space data, namely, magnetic resonance signal k-space data and electromagnetic interference k-space data, and calculate the correlation coefficient matrix of the two space data; S2: combining the k-space data of the magnetic resonance signal detected by the noise detection coil and the k-space data of the electromagnetic interference with the correlation coefficient matrix, and calculating the electromagnetic interference signal I and the electromagnetic interference signal II in the radio frequency coil; S3: Subtract the magnetic resonance signal k-space data and electromagnetic interference k-space data collected by the RF receiving coil from the previously obtained electromagnetic interference signal I and electromagnetic interference signal II, respectively, to obtain preliminary denoised k-space data and residual electromagnetic interference signal; and perform subtraction in the transform domain, and then obtain the final denoised k-space data through inverse transformation.

2. The method for active noise reduction of magnetic resonance equipment based on sequential electromagnetic interference sampling according to claim 1, characterized in that: In step S1, the correlation coefficient matrix of the two spatial data is obtained by using the least square method or neural network training method.

3. The method for active noise reduction of magnetic resonance equipment based on sequential electromagnetic interference sampling according to claim 2, characterized in that: In step S1, the correlation coefficient is calculated using the least square method in the frequency domain to obtain the relationship between the radio frequency receiving and noise detection coils; Assuming that the number of noise detection coils is C and the number of sub-bands is f, the transfer coefficient matrix TF between each noise channel and the RF receiving channel is c f , implemented by the least squares method in the complex field: in, are the electromagnetic interference k-space data collected by the noise detection coil and the RF receiving coil of the c-th channel, respectively. N is the number of sampling points. The superscripts "H" and "-1" represent the conjugate transpose and inverse matrix operations, respectively.

4. The method for active noise reduction of magnetic resonance equipment based on sequential electromagnetic interference sampling according to claim 3, characterized in that: Step S3 specifically includes: after obtaining the transfer coefficient of the system Afterwards, the electromagnetic interference in the magnetic resonance signal k-space is transferred through the transfer coefficient matrix Suppression; frequency domain magnetic resonance signal after noise reduction It is expressed as: in, They are the k-space data of the magnetic resonance signal collected by the noise detection coil and the radio frequency receiving coil of the c-th channel respectively; the time domain magnetic resonance signal is finally obtained by inverse Fourier transform; The residual electromagnetic interference signal is also calculated by the above method.

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