阅读说明：本技术 去除信号中干扰的方法和装置、磁共振系统和存储介质 (Method and device for removing interference in signal, magnetic resonance system and storage medium ) 是由 黄艳图 汪坚敏 李志宾 于 2019-08-22 设计创作，主要内容包括：本发明实施例中公开了去除目标运动信号中干扰的方法和装置、磁共振系统和存储介质,方法包括：针对复数个通道接收的目标运动信号,利用一抗干扰矩阵进行干扰消除,得到去干扰信号；其中,所述抗干扰矩阵通过如下方法得到：针对所述目标运动信号,获取一设定时间段内复数个通道接收的数据,所述数据构成一参考矩阵；根据当前干扰信号的频率以及所述数据的样本数,得到一频率相关矩阵；利用所述频率相关矩阵和所述参考矩阵,计算得到一干扰系数矩阵；对所述干扰系数矩阵进行特征值和特征向量分解,并将一能量最大的特征向量去除,生成一抗干扰矩阵。本发明实施例中的技术方案能够去除目标运动信号中的干扰信号。(The embodiment of the invention discloses a method and a device for removing interference in a target motion signal, a magnetic resonance system and a storage medium, wherein the method comprises the following steps: aiming at target motion signals received by a plurality of channels, an anti-interference matrix is utilized to carry out interference elimination to obtain interference-removed signals; the anti-interference matrix is obtained by the following method: acquiring data received by a plurality of channels in a set time period aiming at the target motion signal, wherein the data form a reference matrix; obtaining a frequency correlation matrix according to the frequency of the current interference signal and the number of samples of the data; calculating to obtain an interference coefficient matrix by using the frequency correlation matrix and the reference matrix; and decomposing the eigenvalue and the eigenvector of the interference coefficient matrix, and removing the eigenvector with the largest energy to generate an anti-interference matrix. The technical scheme in the embodiment of the invention can remove the interference signal in the target motion signal.)

1. A method for removing interference from a target motion signal, comprising:

aiming at each target motion signal received by a plurality of channels, utilizing at least one anti-interference matrix to carry out interference elimination to obtain a target motion interference elimination signal (107); wherein the at least one interference rejection matrix is obtained by:

aiming at the target motion signal, acquiring data received by a plurality of channels within a set time period when the sequence pulse is not operated, wherein the data form a reference matrix (101);

obtaining a frequency correlation matrix (102) according to the frequency of the current interference signal and the number of data samples in the set time period;

calculating to obtain an interference coefficient matrix (103) by using the frequency correlation matrix and the reference matrix;

and decomposing the eigenvalue and the eigenvector of the interference coefficient matrix, and removing the eigenvector with the energy of one eigenvector accounting for more than a set threshold value in the total energy of all eigenvectors or the eigenvector with the largest energy to generate an anti-interference matrix (104).

2. The method of claim 1, wherein there are other unprocessed interference signals;

the method further comprises the following steps: determining a current interference signal, and performing interference elimination on the reference matrix by using the interference rejection matrix to obtain a new reference matrix (106); and returning to the step of obtaining a frequency correlation matrix according to the frequency of the current interference signal and the number of data samples in the set time period.

3. The method according to claim 1, wherein the current interference signal is a fixed frequency signal;

the obtaining a frequency correlation matrix according to the frequency of the current interference signal and the data amount in the set time period includes:

according to the harmonic frequency range of the fixed frequency of the current interference signal, selecting a set harmonic frequency range, determining the total row number of the matrix according to the selected harmonic frequency range, determining the total column number of the matrix according to the sample number of the data in the set time period, and obtaining a frequency correlation matrix according to the total row number and the total column number.

4. The method according to claim 1, wherein the current interference signal is a varying frequency signal;

the obtaining a frequency correlation matrix according to the frequency of the current interference signal and the data amount in the set time period includes:

and determining the total row number of the matrix according to the frequency variation range of the current interference signal and the minimum frequency resolution determined according to the number of samples per second, determining the total column number of the matrix according to the number of samples of the data in the set time period, and obtaining a frequency correlation matrix according to the total row number and the total column number.

5. The method for removing the interference in the target motion signal according to any one of claims 1 to 4, further comprising:

determining the total number of rows of a matrix according to the frequency variation range of the target motion signal and the minimum frequency resolution determined according to the number of samples per second, determining the total number of columns of the matrix according to the number of samples of data in the set time period, and obtaining a frequency correlation matrix according to the total number of rows and the total number of columns;

calculating to obtain a target coefficient matrix by using the frequency correlation matrix and the reference matrix;

decomposing eigenvalues and eigenvectors of the target coefficient matrix, and taking the eigenvector with the largest energy as a target motion eigenvector, wherein the eigenvalue corresponding to the target motion eigenvector is a target motion eigenvalue;

after the generating an interference rejection matrix, the method further comprises: taking the eigenvector with the maximum energy after decomposing the eigenvalue and the eigenvector of the interference coefficient matrix as an interference eigenvector, and taking the eigenvalue corresponding to the interference eigenvector as an interference eigenvalue;

judging whether the ratio of the interference characteristic value to the target motion characteristic value is smaller than a set first threshold value or not, if so, considering that the interference signal is far smaller than the target motion signal, neglecting the interference signal, and abandoning the anti-interference matrix; or, judging whether the product of the transposition of the interference characteristic vector and the target motion characteristic vector is larger than a set second threshold value, if so, considering that the interference characteristic vector is similar to the target motion characteristic vector, eliminating the interference signal to influence the target motion signal, and discarding the anti-interference matrix.

6. An apparatus for removing interference from a target motion signal, comprising:

an interference cancellation module (410) for performing interference cancellation using at least one interference rejection matrix for each target motion signal received by the plurality of channels; and

an immunity matrix generation module (420) for generating the at least one immunity matrix; the immunity matrix generation module (420) comprises:

the data acquisition submodule (421) is used for acquiring data received by a plurality of channels within a set time period when the sequence pulse is not operated, and the data form a reference matrix;

a first matrix generation submodule (422) for obtaining a frequency correlation matrix according to the frequency of the current interference signal and the number of data samples in the set time period;

the second matrix generation submodule (423) is used for calculating to obtain an interference coefficient matrix by utilizing the frequency correlation matrix and the reference matrix;

the decomposition submodule (424) is used for decomposing the eigenvalue and the eigenvector of the interference coefficient matrix to obtain an eigenvector matrix;

and a third matrix generation submodule (425) for removing the eigenvector with the energy of one eigenvector in the eigenvector matrix, the proportion of the energy of the eigenvector in the total energy of all the eigenvectors being greater than a set threshold value or the eigenvector with the largest energy, and generating an anti-interference matrix.

7. The apparatus for removing interference in target motion signal according to claim 6, wherein there are a plurality of interference signals; the apparatus further comprises: the first judgment processing submodule (426) is used for judging whether other unprocessed interference signals exist or not, if other unprocessed interference signals exist, the current interference signals are determined, and the interference matrix is used for eliminating interference on the reference matrix to obtain a new reference matrix; triggering the first matrix generation submodule to execute; and if no other interference signal exists, ending the process.

8. The apparatus for removing interference from target motion signals according to claim 6, wherein the first matrix generation sub-module (422) selects a set harmonic frequency range according to the harmonic frequency range of the fixed frequency of the current interference signal when the current interference signal is a fixed frequency signal, determines a total number of rows of matrices according to the selected harmonic frequency range, determines a total number of columns of matrices according to the number of samples of data within the set time period, and obtains a frequency correlation matrix according to the total number of rows and the total number of columns; when the current interference signal is a change frequency signal, determining the total row number of the matrix according to the frequency change range of the current interference signal and the minimum frequency resolution determined according to the number of samples per second, determining the total column number of the matrix according to the number of samples of data in the set time period, and obtaining a frequency correlation matrix according to the total row number and the total column number.

9. The apparatus for removing interference from target motion signal as claimed in any one of claims 6 to 8, wherein the first matrix generation sub-module (422) is further configured to determine a total number of rows of matrix according to the frequency variation range of the target motion signal and the minimum frequency resolution determined according to the number of samples per second, determine a total number of columns of matrix according to the number of samples of data in the set time period, and obtain a frequency-dependent matrix according to the total number of rows and the total number of columns;

the second matrix generation submodule (423) is further used for calculating a target coefficient matrix by using the frequency correlation matrix and the reference matrix;

the decomposition submodule (424) is further used for decomposing the eigenvalue and the eigenvector of the target coefficient matrix to obtain a target eigenvector matrix;

the immunity matrix generation module (420) further comprises:

a selecting submodule (427) for taking the feature vector with the maximum energy in the target feature vector matrix as a target motion feature vector, wherein the feature value corresponding to the target motion feature vector is a target motion feature value; taking the eigenvector with the maximum energy after decomposing the eigenvalue and the eigenvector of the interference coefficient matrix as an interference eigenvector, and taking the eigenvalue corresponding to the interference eigenvector as an interference eigenvalue; and

a second determination processing sub-module (428) configured to, when the third matrix generation sub-module generates an interference matrix, determine whether a ratio of the interference eigenvalue to the target motion eigenvalue is smaller than a set first threshold, if so, determine that the interference signal is far smaller than the target motion signal, the interference signal is negligible, and discard the interference rejection matrix; or, judging whether the product of the transposition of the interference characteristic vector and the target motion characteristic vector is larger than a set second threshold value, if so, considering that the interference characteristic vector is similar to the target motion characteristic vector, eliminating the interference signal to influence the target motion signal, and discarding the anti-interference matrix.

10. An apparatus for removing interference from a target motion signal, comprising: at least one memory (51) and at least one processor (52), wherein:

the at least one memory (51) is for storing a computer program;

the at least one processor (52) is configured to invoke a computer program stored in the at least one memory (51) to perform the method of removing interference in an object motion signal according to any one of claims 1 to 5.

11. A magnetic resonance imaging system comprising an apparatus for removing interference in a target motion signal as claimed in any one of claims 6 to 10.

12. A computer-readable storage medium having stored thereon a computer program; computer program capable of being executed by a processor and implementing a method for removing interference in a target motion signal according to any one of claims 1 to 5.

Technical Field

The present invention relates to the field of magnetic resonance imaging technology, and in particular, to a method and an apparatus for removing interference in a target motion signal, a magnetic resonance imaging system, and a computer-readable storage medium.

Background

Magnetic Resonance Imaging (MRI) is a technique for imaging using a Magnetic resonance phenomenon. The principles of magnetic resonance imaging mainly include: the atomic nucleus containing odd number of protons, such as hydrogen atomic nucleus widely existing in human body, has a spin motion as if it is a small magnet, and the spin axes of the small magnets are not regular, if an external magnetic field is applied, the small magnets will be rearranged according to the magnetic lines of the external magnetic field, specifically, arranged in two directions parallel or antiparallel to the magnetic lines of the external magnetic field, the direction parallel to the magnetic lines of the external magnetic field is called positive longitudinal axis, the direction antiparallel to the magnetic lines of the external magnetic field is called negative longitudinal axis, the atomic nucleus has only longitudinal magnetization component, and the longitudinal magnetization component has both direction and amplitude. The magnetic resonance phenomenon is that nuclei in an external magnetic field are excited by Radio Frequency (RF) pulses of a specific Frequency, so that the spin axes of the nuclei deviate from the positive longitudinal axis or the negative longitudinal axis to generate resonance. After the spin axes of the excited nuclei are offset from the positive or negative longitudinal axis, the nuclei have a transverse magnetization component.

After the emission of the radio frequency pulse is stopped, the excited atomic nucleus emits an echo signal, absorbed energy is gradually released in the form of electromagnetic waves, the phase and the energy level of the electromagnetic waves are restored to the state before the excitation, and the image can be reconstructed by further processing the echo signal emitted by the atomic nucleus through space coding and the like.

In order to obtain clear clinical diagnostic images during magnetic resonance imaging, it is required that the scanned object must remain stationary during the scan, especially for certain motion sensitive sequences. It is clear that some movements of the scanning object, such as movements caused by breathing, heartbeat, etc., are unavoidable. To minimize the effects of motion, methods are employed to detect such motion, such as respiratory belt, PACE (PACE), etc., by capturing such motion, magnetic resonance imaging sequences and signal acquisitions may be triggered or gated at times of minimal motion, such as the plateau of patient inspiration or expiration, etc. In the process, high-quality images can be obtained only under the condition that the control of related target motion signals such as respiratory waves is accurate. The above target motion signal such as respiration may be referred to as a navigator signal for magnetic resonance imaging, such as a respiration navigator signal or a heartbeat navigator signal.

Taking respiratory navigation as an example, respiratory motion of a patient can currently be detected by various sensors, which may be integrated in a local coil. The respiration sensor comprises a transmitting antenna through which Radio Frequency (RF) signals (outside the MRI band) are transmitted and, after attenuation and reflection by the body, are received by a local coil. The received signal amplitude/phase varies with the patient's movement. By analyzing the received signals, the breathing movement of the human body can be detected.

Since the principle of the above-mentioned respiration signal detection is to detect the motion of a conductive object using a radio frequency signal, other motions such as heartbeat and metal vibration (e.g., 1Hz vibration of a gas pipeline) can be detected in this manner as well. And other detected motion signals will interfere with the respiratory signal, so that the navigation capability of the respiratory signal is reduced, and the imaging quality of the image is influenced. This type of interference can be defined as two types. First, the interference frequency is uncertain, such as a heartbeat. Second, the interference frequency is determined, which is typically caused by the system itself vibrating at a fixed frequency. For example, in magnet designs, a cold head works with the magnet to exchange "cold" air from the compressor with "hot" air from the magnet to keep the magnet cool. The cold head operates at a certain frequency, for example 1 Hz. When the cold head works, 1Hz vibration of the metal gas pipeline can be caused. These signals all interfere with the breathing signal.

To solve this particular disturbance, for example a vibration signal of 1Hz, a better fixation of the pipe as a whole is required. For example, thick foams and ribbons are used. This requires good construction at the system site, but in fact, performance is difficult to guarantee at different sites.

Disclosure of Invention

In view of the above, the embodiments of the present invention provide a method for removing interference from a target motion signal, and on the other hand, provide an apparatus, a magnetic resonance imaging system, and a computer-readable storage medium for removing interference from a target motion signal, so as to remove the interference from the target motion signal and further reproduce a target motion navigation signal required for scan navigation.

The method for removing the interference in the target motion signal provided by the embodiment of the invention comprises the following steps: aiming at each target motion signal received by a plurality of channels, utilizing at least one anti-interference matrix to carry out interference elimination to obtain a target motion interference elimination signal; wherein the at least one interference rejection matrix is obtained by: aiming at the target motion signal, acquiring data received by a plurality of channels within a set time period when the sequence pulse is not operated, wherein the data form a reference matrix; obtaining a frequency correlation matrix according to the frequency of the current interference signal and the number of data samples in the set time period; calculating to obtain an interference coefficient matrix by using the frequency correlation matrix and the reference matrix; and decomposing the eigenvalue and the eigenvector of the interference coefficient matrix, and removing the eigenvector with the energy of one eigenvector accounting for more than a set threshold value in the total energy of all the eigenvectors or the eigenvector with the largest energy to generate an anti-interference matrix.

In one embodiment, there are also other unprocessed interference signals; the method further comprises the following steps: determining a current interference signal, and eliminating interference on the reference matrix by using the anti-interference matrix to obtain a new reference matrix; and returning to the step of obtaining a frequency correlation matrix according to the frequency of the current interference signal and the number of data samples in the set time period.

In one embodiment, the current interference signal is a fixed frequency signal; the obtaining a frequency correlation matrix according to the frequency of the current interference signal and the data amount in the set time period includes: according to the harmonic frequency range of the fixed frequency of the current interference signal, selecting a set harmonic frequency range, determining the total row number of the matrix according to the selected harmonic frequency range, determining the total column number of the matrix according to the sample number of the data in the set time period, and obtaining a frequency correlation matrix according to the total row number and the total column number.

In one embodiment, the current interference signal is a varying frequency signal; the obtaining a frequency correlation matrix according to the frequency of the current interference signal and the data amount in the set time period includes: and determining the total row number of the matrix according to the frequency variation range of the current interference signal and the minimum frequency resolution determined according to the number of samples per second, determining the total column number of the matrix according to the number of samples of the data in the set time period, and obtaining a frequency correlation matrix according to the total row number and the total column number.

In one embodiment, further comprising: determining the total number of rows of a matrix according to the frequency variation range of the target motion signal and the minimum frequency resolution determined according to the number of samples per second, determining the total number of columns of the matrix according to the number of samples of data in the set time period, and obtaining a frequency correlation matrix according to the total number of rows and the total number of columns; calculating to obtain a target coefficient matrix by using the frequency correlation matrix and the reference matrix; decomposing eigenvalues and eigenvectors of the target coefficient matrix, and taking the eigenvector with the largest energy as a target motion eigenvector, wherein the eigenvalue corresponding to the target motion eigenvector is a target motion eigenvalue; after the generating an interference rejection matrix, the method further comprises: taking the eigenvector with the maximum energy after decomposing the eigenvalue and the eigenvector of the interference coefficient matrix as an interference eigenvector, and taking the eigenvalue corresponding to the interference eigenvector as an interference eigenvalue; judging whether the ratio of the interference characteristic value to the target motion characteristic value is smaller than a set first threshold value or not, if so, considering that the interference signal is far smaller than the target motion signal, neglecting the interference signal, and abandoning the anti-interference matrix; or, judging whether the product of the transposition of the interference characteristic vector and the target motion characteristic vector is larger than a set second threshold value, if so, considering that the interference characteristic vector is similar to the target motion characteristic vector, eliminating the interference signal to influence the target motion signal, and discarding the anti-interference matrix.

The device for removing the interference in the target motion signal provided by the embodiment of the invention comprises the following components: the interference elimination module is used for eliminating interference by utilizing at least one anti-interference matrix aiming at each target motion signal received by the plurality of channels; the anti-jamming matrix generating module is used for generating the at least one anti-jamming matrix; the anti-jamming matrix generation module comprises: the data acquisition submodule is used for acquiring data received by a plurality of channels within a set time period when the sequence pulse is not operated, and the data form a reference matrix; the first matrix generation submodule is used for obtaining a frequency correlation matrix according to the frequency of the current interference signal and the number of data samples in the set time period; the second matrix generation submodule is used for calculating to obtain an interference coefficient matrix by utilizing the frequency correlation matrix and the reference matrix; the decomposition submodule is used for decomposing the eigenvalue and the eigenvector of the interference coefficient matrix to obtain an eigenvector matrix; and the third matrix generation submodule is used for removing the characteristic vector with the proportion of the energy of one characteristic vector in the characteristic vector matrix in the total energy of all the characteristic vectors being larger than a set threshold value or the characteristic vector with the maximum energy to generate an anti-interference matrix.

In one embodiment, there are a plurality of interfering signals; the apparatus further comprises: the first judgment processing submodule is used for judging whether other unprocessed interference signals exist or not, if other unprocessed interference signals exist, the current interference signals are determined, and the interference matrix is used for eliminating interference on the reference matrix to obtain a new reference matrix; triggering the first matrix generation submodule to execute; and if no other interference signal exists, ending the process.

In one embodiment, when a current interference signal is a fixed frequency signal, the first matrix generation submodule selects a set harmonic frequency range according to a harmonic frequency range of a fixed frequency of the current interference signal, determines a total number of rows of a matrix according to the selected harmonic frequency range, determines a total number of columns of the matrix according to a number of samples of data in the set time period, and obtains a frequency correlation matrix according to the total number of rows and the total number of columns; when the current interference signal is a change frequency signal, determining the total row number of the matrix according to the frequency change range of the current interference signal and the minimum frequency resolution determined according to the number of samples per second, determining the total column number of the matrix according to the number of samples of data in the set time period, and obtaining a frequency correlation matrix according to the total row number and the total column number.

In one embodiment, the first matrix generation sub-module is further configured to determine a total number of rows of the matrix according to the frequency variation range of the target motion signal and a minimum frequency resolution determined according to the number of samples per second, determine a total number of columns of the matrix according to the number of samples of the data in the set time period, and obtain a frequency correlation matrix according to the total number of rows and the total number of columns; the second matrix generation submodule is further used for calculating to obtain a target coefficient matrix by utilizing the frequency correlation matrix and the reference matrix; the decomposition submodule is further used for decomposing the eigenvalue and the eigenvector of the target coefficient matrix to obtain a target eigenvector matrix; the anti-jamming matrix generation module further comprises: a selecting submodule, configured to use a feature vector with the largest energy in the target feature vector matrix as a target motion feature vector, where a feature value corresponding to the target motion feature vector is a target motion feature value; taking the eigenvector with the maximum energy after decomposing the eigenvalue and the eigenvector of the interference coefficient matrix as an interference eigenvector, and taking the eigenvalue corresponding to the interference eigenvector as an interference eigenvalue; and a second judgment processing submodule, configured to, when the third matrix generation submodule generates an interference matrix, judge whether a ratio of the interference eigenvalue to the target motion eigenvalue is smaller than a set first threshold, if so, consider that the interference signal is far smaller than the target motion signal, where the interference signal is negligible, and discard the interference rejection matrix; or, judging whether the product of the transposition of the interference characteristic vector and the target motion characteristic vector is larger than a set second threshold value, if so, considering that the interference characteristic vector is similar to the target motion characteristic vector, eliminating the interference signal to influence the target motion signal, and discarding the anti-interference matrix.

The device for removing the interference in the target motion signal provided by the embodiment of the invention is characterized by comprising the following components: at least one memory and at least one processor, wherein: the at least one memory is for storing a computer program; the at least one processor is configured to invoke a computer program stored in the at least one memory to perform the method for removing the interference in the target motion signal according to any of the embodiments described above.

The magnetic resonance imaging system provided in the embodiment of the present invention includes the apparatus for removing the interference in the target motion signal in any of the above embodiments.

A computer-readable storage medium provided in an embodiment of the present invention, on which a computer program is stored; the computer program can be executed by a processor and implements the method for removing the interference in the target motion signal according to any one of the embodiments.

It can be seen from the above scheme that, in the embodiment of the present invention, data received by a plurality of channels within a set time period when a sequence pulse is not operated are collected in advance to form a reference matrix, a frequency correlation matrix is generated according to the frequency characteristics of each interference signal, an interference coefficient matrix corresponding to the interference signal is generated by using the frequency correlation matrix and the reference matrix, and an interference matrix is generated after a feature vector with the largest energy is removed by performing eigenvalue and eigenvector decomposition on the interference coefficient matrix; when a plurality of interference signals exist, the previous reference matrix can be multiplied by the obtained interference rejection matrix (that is, the interference signals of which the interference rejection matrix is calculated are eliminated from the reference matrix) to be used as a reference matrix of a new interference signal, then the interference rejection matrix corresponding to the new interference signal is calculated by adopting the same method, and then the interference elimination can be carried out on each target motion signal received by multiple channels by utilizing the interference rejection matrix, so that the corresponding interference can be eliminated.

In addition, the frequency correlation matrix is constructed by utilizing the harmonic frequency range of the interference signal with fixed frequency, and the frequency correlation matrix is constructed by utilizing the frequency change range of the interference signal with changed frequency, so that the frequency correlation matrix related to the characteristics of the interference signal can be obtained to the maximum extent, and the accuracy of calculating the anti-interference matrix is further improved.

Furthermore, a frequency correlation matrix of the target motion signal is constructed according to the frequency variation range of the target motion signal, a corresponding target coefficient matrix is obtained, after eigenvalue and eigenvector decomposition is carried out on the target coefficient matrix, the direction of the eigenvector where the target motion signal is located, i.e. the direction of the eigenvector with the largest energy can be obtained according to the energy of each eigenvector, and then corresponding comparison is carried out on the eigenvalue or eigenvector corresponding to the target motion signal and the interference signal respectively, so that interference with small influence can be ignored, and the processing complexity is reduced; and when it is determined that the elimination of an interference signal affects the target motion signal, the interference signal is not eliminated, so as to ensure the reception of the target motion signal as much as possible.

Drawings

The foregoing and other features and advantages of the invention will become more apparent to those skilled in the art to which the invention relates upon consideration of the following detailed description of a preferred embodiment of the invention with reference to the accompanying drawings, in which:

fig. 1A and fig. 1B are exemplary flowcharts of a method for removing interference in a target motion signal according to an embodiment of the present invention.

FIG. 2 is a diagram illustrating a harmonic frequency range of an interference signal with a fixed frequency of 1Hz according to an example of the present invention.

FIG. 3 is a signal flow diagram illustrating an embodiment of the method of FIG. 1.

Fig. 4A is an exemplary block diagram of an apparatus for removing interference in a target motion signal according to an embodiment of the present invention.

Fig. 4B is an exemplary block diagram of another apparatus for removing interference in a target motion signal according to an embodiment of the present invention.

Fig. 5 is an exemplary block diagram of another apparatus for removing interference from a target motion signal according to an embodiment of the present invention.

Fig. 6 is a schematic diagram of interference elimination after the scheme of removing interference in the target motion signal in the embodiment of the present invention is performed on the interference signal shown in fig. 2.

Fig. 7A and 7B are waveform diagrams of data received by a plurality of channels before and after performing a scheme for removing interference in a target motion signal in an embodiment of the present invention. Fig. 7A is a waveform diagram before the scheme in the embodiment of the present invention is performed, and fig. 7B is a waveform diagram after the scheme in the embodiment of the present invention is performed.

Wherein the reference numbers are as follows:

Detailed Description

In the embodiment of the present invention, considering that for a same signal, when a plurality of channels are used to simultaneously acquire the same signal, the signals acquired by the plurality of channels are necessarily strongly correlated, from the perspective of matrix analysis, the signals acquired by the plurality of channels may form an omnidirectional eigenvector, and most of the energy of the signal is distributed on a smaller number of eigenvectors, such as one or two eigenvectors. Therefore, in the embodiment of the present invention, a frequency correlation matrix corresponding to each interference signal may be constructed for frequencies of different interference signals, an interference coefficient matrix of each interference signal may be constructed according to the frequency correlation matrix of each interference signal and a reference signal acquired through multiple channels, and an eigenvector decomposition may be performed on the interference coefficient matrix of each interference signal, respectively, so that the direction of the eigenvector with the largest energy is the interference eigen direction of the corresponding interference signal, and an interference matrix is constructed by removing the eigenvector in the direction, so as to perform interference cancellation on each target motion signal received by multiple channels by using the corresponding interference matrix, thereby obtaining a target motion signal from which interference of different frequencies is removed, and further obtaining a corresponding navigation signal, etc.

In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail by referring to the following examples.

Fig. 1A and fig. 1B are exemplary flowcharts of a method for removing interference in a target motion signal according to an embodiment of the present invention, and the method may include the following steps, as shown in fig. 1A and fig. 1B:

step 101, for a target motion signal, obtaining data received by a plurality of channels within a set time period when a sequence pulse is not executed, where the data constitutes a reference matrix, for example, if i can be initially set to 1, the reference matrix can be marked as R_i-1I.e. R_i-1Is R₀。

In the embodiment of the invention, a plurality of sensors are used as a plurality of channels to receive the target motion signals. Wherein the sensor may be any type of sensor. For example, it may be an optical sensor including a camera, a temperature sensor, a sound sensor, an X-ray sensor, a radio frequency coil (such as a magnetic resonance receiving coil), or the like.

The signals received by the sensor may include a desired signal, i.e., the target motion signal, which is some motion signal used for scanning navigation, such as a respiration signal or a heartbeat signal, and one or more undesired signals. The unwanted signal is also an interfering signal. For example, if the target motion signal is a respiration signal, the heartbeat signal, the vibration signal, and the like are interference signals; if the target motion signal is a heartbeat signal, the respiration signal, the vibration signal and the like are interference signals.

In step 101, the data received by the plurality of channels is digitized data s (t), which may be directly received digitized data s (t), or digitized data s (t) obtained by performing analog-to-digital conversion on the received analog data, or digitized data s (t) without preprocessing, or digitized data s (t) obtained by preprocessing. The preprocessing can include downsampling, smoothing, interpolation, multiplication matrix and the like, and the preprocessing can be performed in an FPGA, a DSP or a CPU.

The data received by the plurality of channels in the time period set in step 101 may be T seconds, i.e. T₀–t_TData of time period S (t), assuming S (t)₀)S(t₁)…S(t_T) Is a row vector, then R₀The matrix can be represented as: r₀＝{S(t₀),S(t₁),…,S(t_T)}. For example, in one embodiment, T may be a time greater than 2-3 target motion cycles, for example, for a target motion being breathing, times of 10 seconds, 11 seconds, 12 seconds, 13 seconds, 14 seconds, 15 seconds, and more may be selected.

Step 102, obtaining a frequency correlation matrix W according to the frequency of the current interference signal and the number of data samples in the set time period.

In this step, different implementation processes may exist for different types of interference signals, and the following describes in detail the interference signal with fixed frequency and the interference signal with variable frequency respectively:

1) the current interference signal is a fixed frequency signal:

a1, selecting a set harmonic frequency range J according to the harmonic frequency range of the fixed frequency of the current interference signal, and determining the total number of rows of the matrix to be 2J or J according to the selected harmonic frequency range J.

Assuming that the fixed frequency of the current interference signal is 1Hz, the harmonic frequency range thereof can be as shown in fig. 2, and in the present embodiment, the harmonic frequency range is selected to 10 th according to an empirical value, i.e., the harmonic frequency range J is 10.

B1, determining the total matrix column number K-T-N according to the sample number T-N of the data in the set time period T, wherein N is the number of samples per second.

C1, obtaining a frequency correlation matrix W according to the total row number 2J (or J) and the total column number K.

Let J be 1,2, …, J, K be 1,2, …, K be T N, and then the frequency correlation matrix W can be obtained by the following equation (1) or (2).

In the above formula (1), the frequency correlation matrix W is a matrix of 2J × K. For the case where the harmonic frequency range J is 10, it may include sine waves and cosine waves of 1Hz to 10 Hz.

In the above formula (2), the frequency correlation matrix W is a matrix of J × K size.

2) The current interference signal is a varying frequency signal:

a2, according to the frequency variation range F of the current interference signal_start-F_endAnd determining the total number of rows of the matrix to be 2J or J according to the minimum frequency resolution delta f determined according to the number of samples N per second to be 1/N.

In this step, the frequency variation range is usually 0.7-2 Hz when the interference signal is a heartbeat signal, and the frequency variation range is usually 0.1-1 Hz when the interference signal is a respiration signal.

The total number of rows of the matrix can be determined by the following equations (3) to (5).

J_start＝floor(F_start/Δf)+1 (3)

J_end＝floor(F_end/Δf)+1 (4)

J＝J_end-J_start+1 (5)

Where floor () is a floor function used to round down.

B2, determining the total matrix column number K-T-N according to the sample number T-N of the data in the set time period T, wherein N is the number of samples per second.

C2, obtaining a frequency correlation matrix W according to the total row number 2J (or J) and the total column number K.

Let J equal J_start,J_start+1,J_start+2,…,J_endK is 1,2, …, K is T N, and then the frequency correlation matrix W can be obtained by the following equation (6) or (7).

In the above formula (6), the frequency correlation matrix W is a matrix of 2J × K.

In the above formula (7), the frequency correlation matrix W is a matrix of J × K size.

Step 103, using the frequency correlation matrix W and the reference matrix R_i-1And calculating to obtain an interference coefficient matrix C.

In this step, the interference coefficient matrix C can be calculated by using the following formula (8):

C＝W*R_i-1 (8)

104, decomposing the eigenvalue and the eigenvector of the interference coefficient matrix C, removing the eigenvector with the energy of the eigenvector accounting for more than a set threshold value in the total energy of all the eigenvectors or the eigenvector with the largest energy, and generating an anti-interference matrix M_i。

For the interference coefficient matrix C in step 104, the eigenvector matrix E can be obtained by performing the following processing (9) in step 105.

[V,E]＝eig(C’*C) (9)

Where C' is the complex conjugate transpose of C, and E is the eigenvector matrix represented by the column vector assuming V is ascending order.

The interference rejection matrix M can be obtained by performing the processing corresponding to the following expression (10) or (11) for the feature vector matrix E_i。

M_i＝E*O (10)

M_i＝E*O*E^-1 (11)

Wherein E is^-1And O is a matrix of the unit matrix I, wherein one or more row or column elements corresponding to the eigenvectors with the ratio of the eigenvector energy in the eigenvector matrix E to the total energy of all the eigenvectors being larger than a set threshold value are replaced by 0. For example, assuming that the ratio of the energy of the eigenvector in the last column in the eigenvector matrix E to the total energy of all eigenvectors reaches a set threshold,for example, 90%, O may be set to I, and then O may be set to O (m, m) to 0, that is, assuming that the eigenvalues are arranged in ascending order, the O matrix is obtained after the last row and the last column in the identity matrix are set to 0. Alternatively, if the matrix is obtained by replacing the row or column element corresponding to the eigenvector with the largest energy by 0, then after E × O, the eigenvector with the largest energy in E may be set to 0, and the removal of the eigenvector with the largest energy in E may be completed.

If there is only one interference signal, directly executing step 107; otherwise, if there are multiple interference signals, step 105 can be continued as shown in fig. 1B.

Step 105, judging whether other unprocessed interference signals exist, if so, executing step 106; otherwise step 107 is performed.

Step 106, determining a current interference signal, and eliminating interference on the reference matrix by using the interference-free matrix to obtain a new reference matrix; and returns to perform step 102 above.

When specifically implemented, R can be_i＝R_i-1*M_iI +1, and returns to perform the above step 102.

It can be seen that the above steps 101 to 104 or steps 101 to 106 are mainly used to calculate at least one interference rejection matrix, and after obtaining the at least one interference rejection matrix, the interference suppression processing in step 107 below can be performed on each target motion signal received by the plurality of channels in the scanning imaging process.

Step 107, utilizing at least one anti-interference matrix M for each target motion signal received by the plurality of channels in the scanning imaging process_iAnd L, performing interference cancellation to obtain a target motion interference-removed signal, wherein i is 1,2, …. Wherein, L is the number of the anti-interference matrixes and is an integer greater than or equal to 1.

In this step, the target motion signals s (t) received by the plurality of channels and the anti-interference matrix M calculated in step 105 are obtained_iThe interference cancellation signal p (t) can be obtained by performing the processing in the following equation (12).

P(t)＝S(t)*M₁*M₂*…*M_L (12)

Further, considering that there is a possibility that these interference signals are small and therefore negligible relative to the target motion signal, and there is a possibility that characteristics are similar to the target motion signal, and when such interference signals are eliminated, a certain influence may be caused on the target motion signal, so the embodiment may further include the following processing:

a3, frequency variation range F according to the target motion signal_start-F_endAnd determining the total number of rows of the matrix according to the minimum frequency resolution delta f determined by the number of samples N per second, which is 1/N.

In this step, the total number of rows of the matrix can be determined from the above equations (3) to (5) by using an algorithm in accordance with the aforementioned step a 2.

B3, determining the total matrix column number K-T-N according to the sample number T-N of the data in the set time period T, wherein N is the number of samples per second.

C3, obtaining a frequency correlation matrix W according to the total row number 2J (or J) and the total column number K_re。

In this step, the frequency-dependent matrix W can be obtained from the above equation (6) or (7) using an algorithm consistent with the aforementioned step C2_re。

C4, using the frequency correlation matrix W_reAnd said reference matrix R_i-1Calculating to obtain a target coefficient matrix C_re。

In this step, the interference coefficient matrix C can be calculated by using the following formula (13):

C_re＝W_re*R_i-1 (13)

c5, and the target coefficient matrix C_reDecomposing the eigenvalue and the eigenvector, and taking the eigenvector with the largest energy as the target motion eigenvector e_reThe target motion feature vector e_reThe corresponding characteristic value is a target motion characteristic value v_re。

Accordingly, an interference rejection matrix M is generated in step 105_iThereafter, it may further include: performing eigenvalue summation on the interference coefficient matrix CThe eigenvector with the maximum energy after the eigenvector decomposition is taken as the interference eigenvector e_iTaking the eigenvalue corresponding to the interference eigenvector as an interference eigenvalue v_i. Then judging the interference characteristic value v_iAnd the target motion characteristic value v_reRatio v of_i/v_reWhether the interference signal is smaller than a set first threshold value or not, if so, the interference signal is considered to be far smaller than the target motion signal, the interference signal can be ignored, the anti-interference matrix is abandoned, and in the concrete implementation, the anti-interference matrix M can be also made_iI (identity matrix); or judging the interference characteristic vector e_iTranspose e of (e)_i' with the target motion feature vector e_reProduct e of_i’*e_reWhether the interference characteristic vector e is larger than a set second threshold value or not, and if so, considering the interference characteristic vector e_iAnd the target motion feature vector e_reSimilarly, eliminating the interference signal may affect the target motion signal, and the rejection of the anti-interference matrix may also be implemented by making the anti-interference matrix M_iEqual to the identity matrix I. In one example, the first threshold may be 0.1, and the second threshold may be 0.8 or 0.9, etc.

FIG. 3 is a signal flow diagram illustrating an embodiment of the method of FIG. 1. The meaning of each symbol in fig. 3 is the same as that of the same symbol shown in fig. 1, and is not described again.

The method for removing the interference in the target motion signal in the embodiment of the present invention is described in detail above, and the apparatus for removing the interference in the target motion signal in the embodiment of the present invention is described in detail below. The device for removing the interference in the target motion signal in the embodiment of the invention can be used for implementing the method for removing the interference in the target motion signal in the embodiment of the invention. For details that are not disclosed in the embodiment of the apparatus of the present invention, reference may be made to corresponding descriptions in the embodiment of the method of the present invention, and details are not repeated here.

Fig. 4A is an exemplary block diagram of an apparatus for removing interference in a target motion signal according to an embodiment of the present invention. As shown in fig. 4A, the apparatus may include, as shown in a solid line portion in fig. 4A: an interference cancellation module 410 and an interference rejection matrix generation module 420. The anti-jamming matrix generating module 420 may include: the data acquisition submodule 421, the first matrix generation submodule 422, the second matrix generation submodule 423, the decomposition submodule 424, and the third matrix generation submodule 425. In the presence of multiple interference signals, the apparatus may further include a first determination processing sub-module 426, as shown by the dotted line portion in fig. 4A.

The interference cancellation module 410 is configured to perform interference cancellation using at least one interference rejection matrix for each target motion signal received by the plurality of channels.

The immunity matrix generation module 420 is configured to generate the at least one immunity matrix.

The data acquisition submodule 421 is configured to acquire data received by a plurality of channels within a set time period when the sequence pulse is not running, where the data form a reference matrix R_i-1，i＝1。

The first matrix generation submodule 422 is configured to obtain a frequency correlation matrix W according to the frequency of the current interference signal and the number of data samples in the set time period.

The second matrix generation sub-module 423 is for utilizing the frequency correlation matrix W and the reference matrix R_i-1And calculating to obtain an interference coefficient matrix C.

The decomposition submodule 424 is configured to perform eigenvalue and eigenvector decomposition on the interference coefficient matrix C to obtain an eigenvector matrix.

The third matrix generation submodule 425 is configured to remove the eigenvector with the energy ratio of the eigenvector in the eigenvector matrix among the total energy of all the eigenvectors larger than the set threshold or the eigenvector with the largest energy, and generate an interference rejection matrix M_i。

The first determining and processing sub-module 426 is configured to determine whether there are any other unprocessed interference signals, determine a current interference signal if there are any other unprocessed interference signals, perform interference cancellation on the reference matrix by using the interference rejection matrix to obtain a new reference matrix, and enable the reference matrix to be used in a specific implementationR_i＝R_i-1*M_iI is i + 1; and triggers the first matrix generation sub-module 422 to execute; and if no other unprocessed interference signals exist, ending the process.

In the embodiment of the present invention, the interference signal may be a fixed frequency signal or a variable frequency signal. Correspondingly, when the current interference signal is a fixed frequency signal, the first matrix generation sub-module 422 selects a set harmonic frequency range according to the harmonic frequency range of the fixed frequency of the current interference signal, determines a total number of matrix rows according to the selected harmonic frequency range, determines a total number of matrix columns according to the number of samples of data in the set time period, and obtains a frequency correlation matrix W according to the total number of rows and the total number of columns; when the current interference signal is a change frequency signal, determining the total row number of the matrix according to the frequency change range of the current interference signal and the minimum frequency resolution determined according to the number of samples per second, determining the total column number of the matrix according to the number of samples of data in the set time period, and obtaining a frequency correlation matrix W according to the total row number and the total column number.

Fig. 4B is an exemplary block diagram of another apparatus for removing interference from a target motion signal according to an embodiment of the present invention. As shown in fig. 4B, the apparatus may further include a selecting sub-module 427 and a second judgment processing sub-module 428 on the basis of the apparatus shown in fig. 4A.

Correspondingly, the first matrix generation sub-module 422 is further configured to determine a total number of rows of the matrix according to the frequency variation range of the target motion signal and the minimum frequency resolution determined according to the number of samples per second, determine a total number of columns of the matrix according to the number of samples of the data in the set time period, and obtain a frequency-dependent matrix W according to the total number of rows and the total number of columns_re。

The second matrix generation sub-module 423 is further configured to utilize the frequency correlation matrix W_reAnd said reference matrix R_i-1Calculating to obtain a target coefficient matrix C_re。

The decomposition submodule 424 is further used for solving the target coefficient matrix C_rePerforming eigenvalues and eigenvectorsAnd decomposing to obtain a target characteristic vector matrix.

The selecting submodule 427 is used for taking the feature vector with the maximum energy in the target feature vector matrix as the target motion feature vector e_reThe target motion feature vector e_reThe corresponding characteristic value is a target motion characteristic value v_re(ii) a The eigenvector with the maximum energy after decomposing the eigenvalue and the eigenvector of the interference coefficient matrix C is taken as the interference eigenvector e_iTaking the eigenvalue corresponding to the interference eigenvector as an interference eigenvalue v_i。

The second determining sub-module 428 is configured to determine the interference eigenvalue v after the third matrix generation sub-module 425 generates an interference rejection matrix_iAnd the target motion characteristic value v_reIf so, the interference signal is considered to be far smaller than the target motion signal, the interference signal can be ignored, and the anti-interference matrix is discarded_iI (identity matrix); or judging the interference characteristic vector e_iTranspose e of (e)_i' with the target motion feature vector e_reIf the product of (a) is greater than a set second threshold, and if so, considering the interference eigenvector e_iAnd the target motion feature vector e_reSimilarly, eliminating the interference signal may affect the target motion signal and discarding the anti-interference matrix, and in particular, the M may be enabled_i＝I。

Fig. 5 is an exemplary block diagram of an apparatus for removing interference in a target motion signal according to another embodiment of the present invention. As shown in fig. 5, the apparatus may include: at least one memory 51 and at least one processor 52. In addition, some other components may be included, such as a communications port, etc. These components communicate over a bus.

Wherein the at least one memory 51 is adapted to store a computer program. In one embodiment, the computer program may be understood to include the respective modules of the apparatus for removing interference in a target motion signal shown in any one of fig. 4A and 4B. Further, the at least one memory 51 may also store an operating system and the like. Operating systems include, but are not limited to: an Android operating system, a Symbian operating system, a Windows operating system, a Linux operating system, and the like.

The at least one processor 52 is configured to invoke the computer program stored in the at least one memory 51 to perform the method for removing the interference in the target motion signal according to the embodiment of the present invention. The processor 52 may be a CPU, processing unit/module, ASIC, logic module, or programmable gate array, etc. Which can receive and transmit data through the communication port.

The magnetic resonance imaging system provided in the embodiment of the present invention may include the apparatus for removing the interference in the target motion signal shown in any one of fig. 4A and 4B and fig. 5.

It should be noted that not all steps and modules in the above flows and structures are necessary, and some steps or modules may be omitted according to actual needs. The execution order of the steps is not fixed and can be adjusted as required. The division of each module is only for convenience of describing adopted functional division, and in actual implementation, one module may be divided into multiple modules, and the functions of multiple modules may also be implemented by the same module, and these modules may be located in the same device or in different devices.

It is understood that the hardware modules in the above embodiments may be implemented mechanically or electronically. For example, a hardware module may include a specially designed permanent circuit or logic device (e.g., a special purpose processor such as an FPGA or ASIC) for performing specific operations. A hardware module may also include programmable logic devices or circuits (e.g., including a general-purpose processor or other programmable processor) that are temporarily configured by software to perform certain operations. The implementation of the hardware module in a mechanical manner, or in a dedicated permanent circuit, or in a temporarily configured circuit (e.g., configured by software), may be determined based on cost and time considerations.

In addition, a computer-readable storage medium is provided in the embodiments of the present invention, and has a computer program stored thereon, where the computer program can be executed by a processor and implements the method for removing interference in a target motion signal described in the embodiments of the present invention. Specifically, a system or an apparatus equipped with a storage medium on which a software program code that realizes the functions of any of the embodiments described above is stored may be provided, and a computer (or a CPU or MPU) of the system or the apparatus is caused to read out and execute the program code stored in the storage medium. Further, part or all of the actual operations may be performed by an operating system or the like operating on the computer by instructions based on the program code. The functions of any of the above-described embodiments may also be implemented by writing the program code read out from the storage medium to a memory provided in an expansion board inserted into the computer or to a memory provided in an expansion unit connected to the computer, and then causing a CPU or the like mounted on the expansion board or the expansion unit to perform part or all of the actual operations based on the instructions of the program code. Examples of the storage medium for supplying the program code include floppy disks, hard disks, magneto-optical disks, optical disks (e.g., CD-ROMs, CD-R, CD-RWs, DVD-ROMs, DVD-RAMs, DVD-RWs, DVD + RWs), magnetic tapes, nonvolatile memory cards, and ROMs. Alternatively, the program code may be downloaded from a server computer via a communications network.

Fig. 6 is a schematic diagram of interference elimination after the scheme of removing interference in the target motion signal in the embodiment of the present invention is performed on the interference signal shown in fig. 2. It can be seen that the 1Hz fixed frequency interference signal is substantially eliminated.

Fig. 7A and 7B are waveform diagrams of data received by a plurality of channels before and after performing a scheme for removing interference in a target motion signal in an embodiment of the present invention. Fig. 7A is a waveform diagram before the scheme in the embodiment of the present invention is performed, and fig. 7B is a waveform diagram after the scheme in the embodiment of the present invention is performed. It can be seen that these interferences are substantially eliminated after the implementation of the scheme in the embodiments of the present invention.

It can be seen from the above scheme that, in the embodiment of the present invention, data received by a plurality of channels within a set time period when a sequence pulse is not operated are collected in advance to form a reference matrix, a frequency correlation matrix is generated according to the frequency characteristics of each interference signal, an interference coefficient matrix corresponding to the interference signal is generated by using the frequency correlation matrix and the reference matrix, and an interference matrix is generated after a feature vector with the largest energy is removed by performing eigenvalue and eigenvector decomposition on the interference coefficient matrix; when a plurality of interference signals exist, the previous reference matrix can be multiplied by the obtained interference rejection matrix (that is, the interference signals of which the interference rejection matrix is calculated are eliminated from the reference matrix) to be used as a reference matrix of a new interference signal, then the interference rejection matrix corresponding to the new interference signal is calculated by adopting the same method, and then the interference can be eliminated by utilizing the interference rejection matrix for each target motion signal received by multiple channels, so that the interference can be eliminated.

In addition, the frequency correlation matrix is constructed by utilizing the harmonic frequency range of the interference signal with fixed frequency, and the frequency correlation matrix is constructed by utilizing the frequency change range of the interference signal with changed frequency, so that the frequency correlation matrix related to the characteristics of the interference signal can be obtained to the maximum extent, and the accuracy of calculating the anti-interference matrix is further improved.

Furthermore, a frequency correlation matrix of the target motion signal is constructed according to the frequency variation range of the target motion signal, a corresponding target coefficient matrix is obtained, after eigenvalue and eigenvector decomposition is carried out on the target coefficient matrix, the direction of the eigenvector where the target motion signal is located, i.e. the direction of the eigenvector with the largest energy can be obtained according to the energy of each eigenvector, and then corresponding comparison is carried out on the eigenvalue or eigenvector corresponding to the target motion signal and the interference signal respectively, so that interference with small influence can be ignored, and the processing complexity is reduced; and when it is determined that the elimination of an interference signal affects the target motion signal, the interference signal is not eliminated, so as to ensure the reception of the target motion signal as much as possible.

The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.