WO2022227619A1 - 干扰消除方法、介质及设备 - Google Patents

干扰消除方法、介质及设备 Download PDF

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WO2022227619A1
WO2022227619A1 PCT/CN2021/138950 CN2021138950W WO2022227619A1 WO 2022227619 A1 WO2022227619 A1 WO 2022227619A1 CN 2021138950 W CN2021138950 W CN 2021138950W WO 2022227619 A1 WO2022227619 A1 WO 2022227619A1
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signal
matrix
magnetic resonance
resonance imaging
interference
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PCT/CN2021/138950
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English (en)
French (fr)
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刘懿龙
朱瑞星
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杭州微影医疗科技有限公司
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    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/05—Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fields; Measuring using microwaves or radio waves 
    • A61B5/055—Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fields; Measuring using microwaves or radio waves  involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7203—Signal processing specially adapted for physiological signals or for diagnostic purposes for noise prevention, reduction or removal
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7203—Signal processing specially adapted for physiological signals or for diagnostic purposes for noise prevention, reduction or removal
    • A61B5/7217—Signal processing specially adapted for physiological signals or for diagnostic purposes for noise prevention, reduction or removal of noise originating from a therapeutic or surgical apparatus, e.g. from a pacemaker

Definitions

  • the present application relates to the technical field of signal processing, and in particular, to an interference cancellation method, medium and device.
  • the collected magnetic resonance imaging signals are usually affected by interference signals such as electromagnetic interference signals (Electromagnetic Interference, EMI) in the environment, which makes magnetic resonance imaging exist.
  • interference signals such as electromagnetic interference signals (Electromagnetic Interference, EMI)
  • EMI Electromagnetic Interference
  • Artifacts or reduced signal-to-noise ratio of magnetic resonance imaging reducing the accuracy of magnetic resonance imaging.
  • the embodiments of the present application provide an interference cancellation method, medium and device, which can eliminate interference signals from measurement signals received based on multiple channels to obtain valid signals, so as to avoid the influence of interference signals on valid signals.
  • an embodiment of the present application provides an interference cancellation method, which is applied to an electronic device including multiple channels with a signal receiving function.
  • the method includes: acquiring measurement signals from the multiple channels, and mixing effective signals in the measurement signals. Signal and interference signal; use sliding time window to construct the data in the measurement signal into the first block Hankel matrix, and decompose the first block Hankel matrix into multiple components according to singular value decomposition; The component corresponding to the interference signal is used to obtain the target effective signal in the measurement signal; wherein, the data in the same column in the first block Hankel matrix are the data sampled from multiple channels in the same sliding time window, and the data in different columns are different sliding
  • one sliding time window includes at least two sampling time points, and two adjacent sliding time windows are separated by one sampling time point.
  • the coupling relationship between the multiple channels of the interference signal has a frequency domain correlation, and the coupling relationship is continuous and smooth in the frequency domain.
  • the above method can be applied to scenarios such as magnetic resonance imaging, synchronous EEG-functional magnetic resonance imaging, and speech signal processing, but is not limited thereto. It can be understood that since the above coupling relationship is continuous and smooth in the frequency domain, the coupling relationship in the time domain is reflected as, for a signal in a certain channel, the sampling data of the adjacent time points of the channel can be used, and The current and adjacent time points of other channels are used for linear representation, and the linear coefficients of these linear relationships are time-invariant.
  • the sliding time window can be used to construct the data in the measurement signal into the first block Hankel matrix according to the above method, so that the singular value decomposition of the first block Hankel matrix can be obtained.
  • the components corresponding to the interference signals such as electromagnetic interference signals can be extracted, and then these components can be removed and only the components corresponding to the effective signals can be retained.
  • an effective signal with a high signal-to-noise ratio in the measurement signal can be obtained.
  • the above-mentioned measurement signals include mixed magnetic resonance imaging signals and electromagnetic interference signals. Magnetic resonance imaging signals. Furthermore, the quality of magnetic resonance imaging can be greatly improved, and the low-field magnetic resonance imaging equipment can be normally operated in an unshielded or partially shielded environment.
  • j (t-a+1) ⁇ p
  • t is the sampling times of acquiring measurement signals based on multiple channels
  • p is the number of phase encoding lines during data acquisition (or the number of repeated data acquisitions).
  • m is the number of phase encoding lines during data acquisition (or the number of repeated data acquisitions).
  • the above-mentioned identifying and removing the component corresponding to the interference signal from the multiple components to obtain the target effective signal in the measurement signal includes: obtaining the target effective signal from the first block Hankel matrix Identify and remove the component corresponding to the interference signal source from the multiple components to obtain the second block Hankel matrix; convert the second block Hankel matrix to signals of multiple channels to obtain the target effective signal.
  • the components of the first sub-block Hankel matrix may be removed from the first sub-block Hankel matrix by zeroing out all data in the components corresponding to the interfering signal.
  • the above-mentioned second block Hankel matrix only includes components of valid signals, but does not include components corresponding to electromagnetic interference signal sources and components corresponding to noise signal sources. That is, the data in the second block Hankel matrix can represent the effective signal in the measurement signal.
  • the above-mentioned method further includes: determining a component type of each of the multiple components, where the component type at least includes a valid signal and an interference signal.
  • the components corresponding to different signal sources can be identified by using an independent component analysis (Independent Component Analysis, ICA) method or other blind source separation methods.
  • ICA Independent Component Analysis
  • the above-mentioned determining the component type of each of the plurality of components includes: in the case where the electronic device is a magnetic resonance imaging device, for each of the plurality of components , determine the ratio between the average signal intensity of the central part of the frequency domain space corresponding to a component and the average signal intensity of the edge part to determine the component type of the corresponding component; wherein, the effective signal is a magnetic resonance imaging signal, and the interference signal includes electromagnetic interference At least one of signal and thermal noise. Specifically, if the above ratio is higher than a set threshold (eg, 5), the component is considered to be the component corresponding to the magnetic resonance signal. On the contrary, if the ratio is lower than the set threshold, the component is considered to be the component corresponding to the interference signal such as the electromagnetic interference signal.
  • a set threshold eg, 5
  • each channel in the above-mentioned multiple channels is a first-type channel, or, the multiple channels include at least one first-type channel and at least one second-type channel;
  • the first type of channel is used for receiving valid signals and receiving or inducing interference signals
  • the second type of channel is only used for receiving or inducing interference signals.
  • the first type of channel is the receiving coil channel hereinafter
  • the second type of channel is the induction coil channel hereinafter.
  • the electronic device is a magnetic resonance imaging device
  • the effective signal is a magnetic resonance imaging signal
  • the interference signal includes at least one of an electromagnetic interference signal and thermal noise
  • the first type of channel That is, the receiving coil channel in the following
  • the second type of channel (the receiving coil channel in the following) is realized by one or more phased array coils or stickers. It is implemented by one or more electrodes on the surface of the detection object (such as human skin).
  • the electronic device is a synchronous EEG-functional magnetic resonance imaging device
  • the effective signal is an EEG signal
  • the interference signal includes a radio frequency signal initiated by the synchronous EEG-functional magnetic resonance imaging device and at least one of the interference caused by the gradient signal
  • the first type of channel is realized by one or more electrodes attached to the surface of the scalp (ie the detection object)
  • the second type of channel is realized by attaching to the human skin (ie the detection object) ) on the surface of one or more electrodes, or one or more phased array coils.
  • the measurement signal is one-dimensional or multi-dimensional data
  • the first block Hankel matrix is constructed using a one-dimensional or multi-dimensional (eg, two-dimensional) sliding time window. It can be understood that the dimension of the measurement signal is consistent with the dimension of the sliding time window of the constructed first block Hankel matrix.
  • an embodiment of the present application provides an interference cancellation device, which is applied to an electronic device including multiple channels with a signal receiving function, including: an acquisition module for acquiring measurement signals from multiple channels, and mixing the measurement signals with The effective signal and the interference signal are obtained, the coupling relationship of the interference signal between the multiple channels has frequency domain correlation, and the coupling relationship is continuous and smooth in the frequency domain; the building block is used to obtain a sliding time window.
  • the data in the measurement signal acquired by the module is constructed as the first block Hankel matrix, wherein the data in the same column of the first block Hankel matrix is the data sampled from multiple channels in the same sliding time window, and the data in different columns is different.
  • one sliding time window includes at least two sampling time points, and there is a sampling time point between two adjacent sliding time windows;
  • the singular value decomposition decomposes the first block Hankel matrix constructed by the building module into multiple components; the separation module is used to identify and remove the component corresponding to the interference signal from the multiple components obtained by the decomposition module, so as to obtain the component in the measurement signal.
  • Target valid signal For example, the above-mentioned acquisition module, building module, decomposition module and separation module can be implemented by a processor having the functions of these modules or units in the electronic device.
  • V is a matrix of order j ⁇ n
  • each column of V corresponds to a component of a signal source
  • multiple components are the components corresponding to all columns in the matrix V
  • n is the total number of multiple components
  • k m ⁇ a
  • m is the number of multiple channels
  • a is the number of sampled data in one channel in a sliding time window
  • j is the total number of sliding time windows.
  • j (t-a+1) ⁇ p
  • t is the sampling times of acquiring measurement signals based on multiple channels
  • p is the number of phase encoding lines during data acquisition (or the number of repeated data acquisitions).
  • the above separation module is specifically configured to identify and remove components corresponding to the interference signal from multiple components in the first sub-block Hankel matrix to obtain a second sub-block Hankel matrix ; Convert the second block Hankel matrix to the signal of multiple channels to obtain the target effective signal.
  • the above-mentioned apparatus further includes: a determination module configured to determine a component type of each of the multiple components, where the component type at least includes a valid signal and an interference signal.
  • a determination module configured to determine a component type of each of the multiple components, where the component type at least includes a valid signal and an interference signal.
  • the above determination module may be implemented by a processor having the function of the block or unit in the electronic device.
  • the above determining module is specifically configured to determine, for each of the multiple components, a frequency domain space corresponding to one component when the electronic device is a magnetic resonance imaging device The ratio between the average signal intensity of the central part and the average signal intensity of the edge part to determine the component type of the corresponding component; wherein the effective signal is a magnetic resonance imaging signal, and the interference signal includes at least one of an electromagnetic interference signal and thermal noise .
  • each of the above-mentioned multiple channels is a first-type channel, or, the multiple channels include at least one first-type channel and at least one second-type channel; Among them, the first type of channel is used for receiving valid signals and receiving or inducing interference signals, and the second type of channel is only used for receiving or inducing interference signals.
  • the electronic device is a magnetic resonance imaging device
  • the effective signal is a magnetic resonance imaging signal
  • the interference signal includes at least one of an electromagnetic interference signal and thermal noise
  • the first type of channel is composed of One or more phased array coils are implemented
  • the second type of channel is implemented by one or more phased array coils, or one or more electrodes attached to the surface of the detection object.
  • the electronic device is a synchronous EEG-functional magnetic resonance imaging device
  • the effective signal is an EEG signal
  • the interference signal includes a radio frequency signal initiated by the synchronous EEG-functional magnetic resonance imaging device and at least one of gradient signals
  • the first type of channel is realized by one or more electrodes attached to the surface of the detection object
  • the second type of channel is realized by one or more electrodes attached to the surface of the detection object, or one or more A phased array coil is implemented.
  • the measurement signal is one-dimensional or multi-dimensional data
  • the first block Hankel matrix is constructed using a one-dimensional or multi-dimensional sliding time window.
  • an embodiment of the present application provides a computer-readable storage medium, where instructions are stored on the storage medium, and when executed on a computer, the instructions cause the computer to execute the interference cancellation method in the first aspect.
  • embodiments of the present application provide an electronic device, including: one or more processors; one or more memories; the one or more memories store one or more programs, when the one or more memories When executed by the one or more processors, the program causes the electronic device to execute the interference cancellation method in the first aspect.
  • FIG. 1 shows a schematic structural diagram of a magnetic resonance imaging apparatus according to some embodiments of the present application
  • FIG. 2 shows a schematic structural diagram of a magnetic resonance imaging apparatus according to some embodiments of the present application
  • FIG. 3 shows a schematic flowchart of an interference cancellation method according to some embodiments of the present application.
  • FIG. 4 shows a schematic diagram of constructing a block Hankel matrix according to some embodiments of the present application
  • FIG. 5 shows a schematic diagram of a distribution in k-space according to some embodiments of the present application.
  • Fig. 6 shows a schematic diagram of a reconstructed image, k-space and each signal component in a magnetic resonance imaging process according to some embodiments of the present application
  • Figure 7 shows a block diagram of a computer of a magnetic resonance imaging apparatus according to some embodiments of the present application.
  • FIG. 8 shows a block diagram of a mobile phone according to some embodiments of the present application.
  • Illustrative embodiments of the present application include, but are not limited to, interference cancellation methods, apparatus, media, and devices.
  • the interference elimination method provided by the embodiments of the present application can be applied to scenarios such as magnetic resonance imaging (Magnetic Resonance Imaging, MRI), synchronous EEG-functional magnetic resonance imaging, and speech signal processing, but is not limited thereto.
  • the electronic device may include multiple channels with a signal receiving function, so as to eliminate interference signals from the measurement signals of the multiple channels, so as to obtain effective signals that are not affected by the interference signals, such as the magnetic resonance imaging signals in the aforementioned applications, EEG signals, voice signals, etc.
  • the effective signal may be a magnetic resonance imaging signal
  • the interference signal may be thermal noise or an electromagnetic interference signal (Electromagnetic Interference, EMI) in the environment, or the like.
  • the electronic device may be a device having a magnetic resonance imaging function, which is referred to as a magnetic resonance imaging device herein.
  • the effective signal may be an EEG signal
  • the interference signal may include magnetic resonance imaging radio frequency signals and gradient signals generated during the operation of the electronic device.
  • the above-mentioned electronic device may be a device with synchronized EEG-functional magnetic resonance imaging, which may be referred to as an EEG imaging device herein.
  • the effective signal may be the speech signal to be processed, and the interference signal may be ambient noise or the like.
  • the above-mentioned electronic device may be an electronic device having a voice processing function, such as an electronic device installed with voice assistant software.
  • electronic devices in this scenario may include, but are not limited to: mobile phones, smart speakers, tablet computers, laptop computers, desktop computers, ultra-mobile personal computers (UMPCs), netbooks, and cellular phones , personal digital assistant (personal digital assistant, PDA), augmented reality (augmented reality, AR), virtual reality (virtual reality, VR) equipment and so on.
  • the interference cancellation method provided by the embodiments of the present application is mainly described by taking the interference cancellation method performed by the magnetic resonance imaging device in the magnetic resonance imaging scene as an example. Similarly, the implementation details of the interference cancellation method performed by the electronic device in other application scenarios will not be repeated here. For some descriptions, reference may be made to the relevant description of the interference cancellation method performed by the magnetic resonance imaging device.
  • Magnetic resonance imaging technology can generate medical images in medical or clinical application scenarios for disease diagnosis. Specifically, magnetic resonance imaging technology can use the signals generated by the resonance of atomic nuclei in a strong magnetic field to perform image reconstruction, and to make cross-sectional, sagittal, coronal and various oblique tomographic images of objects such as the human body.
  • the magnetic resonance imaging device may be a low-field or ultra-low-field magnetic resonance imaging device, or a mid-field or high-field magnetic resonance imaging device.
  • magnetic resonance imaging systems in clinical applications can generally be divided into high-field (above 1T), mid-field (0.3-1T), low-field (0.1-0.3T), ultra-low-field (0.1 below T).
  • magnetic resonance imaging equipment usually needs to be deployed in specific rooms or areas of hospitals or research institutions to achieve strict electromagnetic shielding. Cannot be used as a general-purpose imaging device.
  • the deployment site is not limited, for example, it is not limited to use in hospitals or research institutions, and a small portable magnetic resonance imaging device with low cost will greatly expand the application scenarios of magnetic resonance imaging.
  • the embodiments of the present application are mainly applied to low-field or ultra-low-field magnetic resonance imaging equipment, to eliminate interference signals such as environmental electromagnetic interference signals in the magnetic resonance imaging process, thereby eliminating artifacts existing in magnetic resonance imaging and improving magnetic resonance imaging.
  • the quality of resonance imaging enabling low-field MRI equipment to function properly in an unshielded or partially shielded environment.
  • the magnetic resonance imaging equipment does not require strict electromagnetic shielding, that is, the magnetic resonance imaging equipment does not need to be placed in the shielding room, there is no need to build a special shielding room, the installation is simple, and the cost can be greatly reduced.
  • the application scenarios of magnetic resonance imaging can be greatly expanded, for example, it can be applied to bedside magnetic resonance imaging (Point-Of-Care MRI, POC MRI), emergency room (ICU), or medical vehicles and ambulances.
  • one or more multi-channel coils eg, phased array coils
  • one or more electrodes that can be attached to the human skin surface can be used to receive signals.
  • the above-mentioned coils or electrodes can be divided into two categories.
  • a type of coil called a receiving coil, is used to receive magnetic resonance signals (specifically, magnetic resonance imaging signals), and should avoid receiving interference signals such as electromagnetic interference signals or thermal noise in the environment.
  • the receiving coil will inevitably be affected by electromagnetic interference, that is, the receiving coil will also receive some electromagnetic interference signals.
  • the other coil called the sensing coil, is used to sense environmental electromagnetic interference signals, and this function can also be achieved with electrodes.
  • the magnetic resonance imaging apparatus 100 may include: a computer 101, a spectrometer 102, a gradient amplifier 103, a gradient coil 104, a transmitting radio frequency amplifier 105, a transmitting radio frequency coil (also referred to as a transmitting coil) 106, a receiving radio frequency coil 107, a receiving radio frequency amplifier ( Also called receive coil) 108 and magnet 109.
  • the computer 101 is configured to issue an instruction to the spectrometer 102 under the control of the operator, so as to trigger the spectrometer 102 to generate the waveform of the gradient signal and the waveform of the radio frequency signal according to the instruction.
  • the gradient signal generated by the spectrometer 102 is amplified by the gradient amplifier 103, the gradient of the magnetic field is formed by the gradient coil 104, thereby realizing the spatial gradient encoding of the magnetic resonance signal (specifically, the magnetic resonance imaging signal).
  • the spatial gradient coding is used to spatially localize the magnetic resonance signals, ie to distinguish the location of the source of the magnetic resonance signals.
  • the radio frequency signal generated by the spectrometer 102 is amplified by the transmitting radio frequency amplifier 105 and emitted by the transmitting radio frequency coil 106 to excite the protons (hydrogen nuclei) in the imaging area.
  • the excited protons can send out radio frequency signals, which can be received by the receiving coil 108, amplified by the receiving radio frequency amplifier 107, and then converted into digital signals by the spectrometer 102, and then sent to the computer 101 for processing to obtain images and display.
  • magnet 109 may be any suitable type of magnet capable of generating a main magnetic field.
  • FIG. 2 shows a schematic diagram of another possible magnetic resonance imaging apparatus 100 . Comparing FIG. 2 with FIG. 1 , the difference is that an induction coil 111 and a corresponding receiving RF amplifier 110 are newly added to the magnetic resonance imaging apparatus 100 shown in FIG. 2 , and other components are the same as those shown in FIG. 1 .
  • the induction coil 111 is used for sensing the electromagnetic interference signal in the environment, and after being amplified by the receiving RF amplifier 110 , it is converted into a digital signal by the spectrometer 102 and sent to the computer 101 for processing.
  • both the receiver coil and the induction coil need to be designed to maximize the signal-to-noise ratio that the coil can provide. That is, the receiving coil should be able to receive magnetic resonance signals (specifically, magnetic resonance imaging signals) as sensitively as possible, and be less affected by electromagnetic interference and thermal noise as much as possible. For the induction coil, it should be able to sense ambient electromagnetic interference as sensitively as possible, receive magnetic resonance signals as little as possible, and be affected by thermal noise as little as possible.
  • the above two types of coils need to reduce the influence of thermal noise as much as possible.
  • some cooling devices can use cooling to minimize coil resistance, thereby reducing thermal effect of noise. It can be understood that, the embodiment of the present application does not specifically describe the cooling device, and reference may be made to any achievable manner in the related art.
  • the EEG imaging device in this embodiment of the present application may also include the transmitting coil 106 and the receiving coil 108 shown in FIG. 1 , which are used to generate magnetic resonance imaging radio frequency signals based on the same process; to generate gradient signals.
  • the above-mentioned receiving coils and induction coils may be implemented using single or multiple phased array coils that are widely used in modern medical magnetic resonance imaging.
  • the above-mentioned induction coil can also be replaced with an electrode attached to the surface of the human skin. Signal.
  • the multiple channels with the signal receiving function involved in the magnetic resonance imaging apparatus 100 may include multiple channels of a single phased array coil, or may include multiple channels of multiple coils.
  • the design and layout (deployment position, deployment direction, etc.) of the receiving coil and the induction coil in the magnetic resonance imaging device 100 are not specifically limited, and can be any achievable solution.
  • the channel in the receiving coil may be referred to as a receiving coil channel.
  • the receiving coils of multiple channels may also be used to enhance the ability to identify and eliminate electromagnetic interference signals.
  • the channels in the induction coil may be referred to as induction coil channels. Among them, the more channels of the induction coil, the more accurately the characteristics of the electromagnetic interference signal can be depicted, so that the electromagnetic interference signal received by the receiving coil can be accurately estimated through the electromagnetic interference signal received by the induction coil.
  • the magnetic resonance imaging apparatus 100 shown in FIG. 1 may provide one receiving coil and the receiving coil has multiple channels, or provide multiple receiving coils and each receiving coil channel has one or more channels, but not limited thereto .
  • the multiple channels provided by the magnetic resonance imaging apparatus 100 are all receiving coil channels.
  • the magnetic resonance imaging apparatus 100 shown in FIG. 2 may provide one receiving coil and one induction coil, and the receiving coil has one channel and the induction coil has two channels, but is not limited thereto.
  • the plurality of channels provided by the magnetic resonance imaging apparatus 100 include a receiving coil channel and an induction coil channel.
  • the multiple channels with signal receiving function provided by the EEG device can be realized by electrodes attached to the scalp.
  • the multiple channels provided by the electronic device may be multiple analog signal channels provided by multiple microphones.
  • the electromagnetic interference signal has a coupling relationship between multiple channels of the magnetic resonance imaging apparatus 100 , and the coupling relationship is specifically the frequency domain correlation of the electromagnetic interference signal between the multiple channels, and the coupling relationship is in the frequency domain. continuous and smooth. It can be understood that the frequency domain correlation of the electromagnetic interference signal among the multiple channels may be the linear relationship of the electromagnetic interference signal received by each channel at different frequency points.
  • the coupling relationship in the time domain is reflected as: the signal for a certain channel can be sampled by the adjacent time points of the channel; and other The sampling of the current and adjacent time points of the channel is used for linear representation, and the linear coefficients of these linear relationships are time-invariant.
  • the execution body of the electromagnetic interference cancellation method of the present application may be the magnetic resonance imaging apparatus 100 , and specifically the computer 101 in the magnetic resonance imaging apparatus 100 .
  • a schematic flowchart of a method for eliminating electromagnetic interference provided by the present application may include the following steps 301 to 306:
  • Step 301 The magnetic resonance imaging apparatus 100 receives measurement signals from a plurality of channels, where the measurement signals include mixed magnetic resonance imaging signals and electromagnetic interference signals.
  • the above-mentioned multiple channels are all receiving coil channels.
  • the above-mentioned multiple channels include a receiving coil channel and an induction coil channel.
  • the above-mentioned measurement signals are obtained based on multiple acquisitions of multiple channels. It can be understood that, in the high-field magnetic resonance imaging apparatus 100 (for example, the magnetic field strength is greater than 1 T), only one acquisition is often required; in a low-field or ultra-low-field system, the SNR of the signal acquired by a single acquisition is low. , so it is necessary to average the data acquired for multiple times to improve the SNR of the final magnetic resonance imaging signal.
  • Step 302 The magnetic resonance imaging apparatus 100 uses a sliding time window to construct the data in the measurement signal into a first block Hankel matrix.
  • the data in the same column is data sampled from multiple channels in the same time window
  • the data in different columns is data sampled from multiple channels in different time windows.
  • the magnetic resonance imaging apparatus 100 may use a sliding time window to construct the data in the measurement signal into a first block Hankel matrix, wherein a vector of data sampled from multiple channels in a sliding time window is used as the first block Hankel matrix.
  • a sliding time window includes at least two sampling time points, and two adjacent sampling time points The sliding time windows are separated by a sampling time point.
  • matrix H is the first block Hankel matrix and is a matrix of order k ⁇ j
  • matrix U is of order k ⁇ n
  • matrix S is a diagonal matrix of order n ⁇ n
  • matrix V * is the conjugate transpose of matrix V matrix and matrix V is a matrix of order j ⁇ n
  • n is the number of multiple components
  • each column of V corresponds to a component of a signal source
  • multiple components are the components corresponding to all columns in matrix V
  • k m ⁇ a
  • m is the number m of multiple channels
  • a is the number of sampled data in one channel in a sliding time window
  • j is the total number of sliding time windows
  • j (t-a+1) ⁇ p
  • t is based on multiple Channel obtains the sampling times of the measurement signal
  • p is the number of phase encoding lines during data acquisition (or the number of repeated data acquisitions).
  • the above-mentioned plurality of channels include one receiving coil channel and two induction coil channels
  • m 3.
  • Figure 4 shows an example graph for building a block Hankel matrix.
  • 4 shows the data acquired by the magnetic resonance imaging apparatus 100 based on multiple channels.
  • the block Hankel matrix is the above-mentioned first block Hankel matrix H.
  • a dotted box shown in FIG. 4 is a sliding time window, each sliding time window includes 3 sampling time points, and a circle in the sliding time window represents a piece of data sampled from a channel.
  • the N channels are the multiple channels in the magnetic resonance imaging apparatus 100, and the data sampled in each channel are sorted in the order of sampling time.
  • channel 1 to channel N-1 of the N channels are all induction coil channels, and channel N is a receiving coil channel, and N may be 3.
  • Step 304 The magnetic resonance imaging apparatus 100 determines a component type of each of the plurality of components, where the component type at least includes the magnetic resonance imaging signal and the electromagnetic interference signal.
  • the aforementioned component types may also include noise, such as thermal noise.
  • noise such as thermal noise.
  • a component of a component type corresponds to a signal source, for example, a component whose component type is a magnetic resonance imaging signal corresponds to a magnetic resonance imaging signal source, and a component whose component type is an electromagnetic interference signal corresponds to a magnetic interference signal source. .
  • Step 305 The magnetic resonance imaging apparatus 100 identifies and removes the components corresponding to the electromagnetic interference signal source and the components corresponding to the noise signal source from the plurality of components in the first segmented Hankel matrix to obtain a second segmented Hankel matrix.
  • all data in the components of the first sub-block Hankel matrix corresponding to interference signals such as electromagnetic interference signals may be set to zero to remove these components from the first sub-block Hankel matrix.
  • all data (or components) corresponding to the electromagnetic interference signal in the second block Hankel matrix are removed, eg, all are set to zero.
  • the above-mentioned second block Hankel matrix only includes components (ie, data) of magnetic resonance imaging signals, but does not include components corresponding to electromagnetic interference signal sources and components corresponding to noise signal sources. That is, the data in the second block Hankel matrix can represent the effective signal in the measurement signal.
  • the data in the measurement signal can be constructed by using a sliding time window in the above-mentioned manner.
  • the manner in which the magnetic resonance imaging apparatus 100 identifies each component may be as follows: for each component, the magnetic resonance imaging apparatus 100 determines the average signal intensity of the central part of the frequency domain space and the average signal intensity of the edge part of the frequency domain space corresponding to one component The ratio between to determine the component type of the corresponding component.
  • the frequency domain space is called k-space, where the center of the k-space is the low-frequency part, and the edge is called the high-frequency part.
  • FIG. 5 which is a schematic diagram of the distribution of k-space, the range marked by the dotted box is the low frequency part, and the range marked by the solid line box is the high frequency part.
  • the average signal intensity of the component in the low-frequency part and the high-frequency part of the k-space can be calculated separately. If the average signal intensity of the low-frequency part is significantly higher than the average signal intensity of the high-frequency part.
  • the signal strength can be considered as the component corresponding to the magnetic resonance imaging signal; otherwise, the component can be considered as the component corresponding to the electromagnetic interference signal or the noise.
  • FIG. 6 it is a schematic diagram of the reconstructed image, k-space and each component in the magnetic resonance imaging process.
  • the left column shown in (A) of FIG. 6 shows a schematic diagram of the electromagnetic interference signal component and the magnetic resonance signal (ie, the magnetic resonance imaging signal) component in the reconstructed image
  • the right column shows the reconstructed image Schematic diagram of the EMI signal components and the magnetic resonance signal components in k-space.
  • the electromagnetic interference signal component is in the edge part of k-space, while the magnetic resonance signal component is in the center part of k-space.
  • the magnetic resonance imaging apparatus 100 may calculate the ratio of the average signal intensity of the low-frequency part to the high-frequency part in each component, and set an appropriate threshold (for example, 5, the threshold needs to be based on the inclusion of factors such as noise level can be adjusted according to the actual situation). If the ratio is higher than the set threshold, the component is considered to be the component corresponding to the magnetic resonance signal. Conversely, if the ratio is lower than the set threshold, the component is considered to be a component corresponding to interference signals such as electromagnetic interference signals.
  • an appropriate threshold for example, 5
  • embodiments of the present application are not limited to the methods for identifying components exemplified above, and may also be other methods.
  • methods such as Independent Component Analysis (ICA) or other blind source separation methods may also be used to identify Components corresponding to different signal sources are not described in detail in this embodiment of the present application.
  • ICA Independent Component Analysis
  • the above-mentioned second block Hankel matrix includes components (ie, data) of magnetic resonance imaging signals, but does not include components corresponding to electromagnetic interference signal sources and components corresponding to noise signal sources.
  • Step 306 The magnetic resonance imaging apparatus 100 converts the second block Hankel matrix to the above-mentioned multiple channels, and obtains the target magnetic resonance imaging signal.
  • the magnetic resonance imaging apparatus 100 converts the second sub-block Hankel matrix to the above-mentioned multiple channels, the magnetic resonance imaging signal with high signal-to-noise ratio in the receiving coil channel among the multiple channels can be obtained, which is the above-mentioned target Magnetic resonance signals.
  • the upper row of (B) in FIG. 6 shows the reconstructed image and the corresponding k-space diagram before the electromagnetic interference is eliminated according to the above method
  • the lower row shows the reconstructed image and the corresponding k-space after the electromagnetic interference is eliminated according to the above method.
  • Schematic diagram of k-space Obviously, the reconstructed image obtained according to the electromagnetic interference elimination method provided by the present application has fewer artifacts and higher quality.
  • the electromagnetic interference elimination method provided by the present application can eliminate electromagnetic interference signals from signals collected by multiple channels of the magnetic resonance imaging apparatus 100 based on singular value decomposition, without knowing whether the electromagnetic interference signals are among the multiple channels.
  • the coupling relationship between them is conducive to simplifying the process of eliminating electromagnetic interference signals and improving the stability of electromagnetic interference elimination.
  • the electronic device may also implement the interference cancellation method according to steps similar to the above steps 301-306, the difference being that the execution subjects are different, and the types of valid signals and interference signals are different.
  • components corresponding to different signal sources may be identified based on an independent component analysis method or a blind source separation method, which is not repeated in this embodiment of the present application.
  • the independent component analysis method can be used to obtain the source signal from the signals received by multiple channels, and determine the properties of the source signal (such as effective signal or interference signal) ), keep only the source signal corresponding to the valid signal, and resynthesize the signal of the first type of channel (that is, the channel used to receive the valid signal).
  • the component identification method applicable to the present application includes but is not limited to the above examples, and may also be any other achievable manner.
  • the effective signal and the interference signal in the measurement signal may be one-dimensional or multi-dimensional (eg, two-dimensional) data.
  • the one-dimensional or multi-dimensional sliding time window is used in the interference elimination method to construct the block Hankel matrix, and the dimension of the measurement signal is consistent with the dimension of the sliding time window. Similar, and will not be repeated here.
  • FIG. 7 schematically illustrates an example computer 1400 in accordance with various embodiments.
  • the system 1400 may include one or more processors 1404 , system control logic 1408 coupled to at least one of the processors 1404 , system memory 1412 coupled to the system control logic 1408 , coupled to the system control logic 1408 non-volatile memory (NVM) 1416 , and a network interface 1420 to the system control logic 1408 .
  • processors 1404 the system control logic 1408 coupled to at least one of the processors 1404
  • system memory 1412 coupled to the system control logic 1408
  • NVM non-volatile memory
  • processor 1404 may include one or more single-core or multi-core processors. In some embodiments, processor 1404 may comprise any combination of general purpose processors and special purpose processors (e.g., graphics processors, application processors, baseband processors, etc.). In an embodiment in which the system 1400 adopts an eNB (Evolved Node B, enhanced base station) 101 or a RAN (Radio Access Network, radio access network) controller 102, the processor 1404 may be configured to perform various conforming embodiments, For example, the embodiment shown in FIG. 3 . For example, the processor 1404 can construct a matrix for the actual measurement signals from multiple channels, perform singular value decomposition on the matrix to obtain multiple components, and then remove the components corresponding to the interference signal (source) in the measurement signal to obtain the final valid signal.
  • eNB evolved Node B, enhanced base station
  • RAN Radio Access Network, radio access network
  • system control logic 1408 may include any suitable interface controller to provide any suitable interface to at least one of processors 1404 and/or any suitable device or component in communication with system control logic 1408 .
  • system control logic 1408 may include one or more memory controllers to provide an interface to system memory 1412 .
  • System memory 1412 may be used to load as well as store data and/or instructions.
  • the memory 1412 of the system 1400 in some embodiments may include any suitable volatile memory, such as suitable dynamic random access memory (DRAM).
  • DRAM dynamic random access memory
  • NVM/memory 1416 may include one or more tangible, non-transitory computer-readable media for storing data and/or instructions.
  • the NVM/memory 1416 may include any suitable non-volatile memory such as flash memory and/or any suitable non-volatile storage device, such as HDD (Hard Disk Drive, hard disk drive), CD (Compact Disc) , CD-ROM) drive, at least one of DVD (Digital Versatile Disc, Digital Versatile Disc) drive.
  • NVM/storage 1416 may include a portion of storage resources on the device where system 1400 is installed, or it may be accessed by, but not necessarily be part of, a device. For example, NVM/storage 1416 can be accessed over the network via network interface 1420 .
  • system memory 1412 and NVM/memory 1416 may include a temporary copy and a permanent copy of instructions 1424, respectively.
  • the instructions 1424 may include instructions that, when executed by at least one of the processors 1404, cause the computer 1400 to implement the method shown in FIG.
  • instructions 1424 , hardware, firmware, and/or software components thereof may additionally/alternatively reside in system control logic 1408 , network interface 1420 , and/or processor 1404 .
  • Network interface 1420 may include a transceiver for providing a radio interface for system 1400 to communicate with any other suitable devices (eg, front-end modules, antennas, etc.) over one or more networks.
  • network interface 1420 may be integrated with other components of system 1400 .
  • network interface 1420 may be integrated with at least one of processor 1404, system memory 1412, NVM/memory 1416, and a firmware device (not shown) having instructions when at least one of processors 1404 executes the When instructed, the computer 1400 implements the method shown in FIG. 3 .
  • Network interface 1420 may further include any suitable hardware and/or firmware to provide a multiple-input multiple-output radio interface.
  • network interface 1420 may be a network adapter, wireless network adapter, telephone modem, and/or wireless modem.
  • At least one of the processors 1404 may be packaged with logic for one or more controllers of the system control logic 1408 to form a system-in-package (SiP). In one embodiment, at least one of the processors 1404 may be integrated on the same die with logic for one or more controllers of the system control logic 1408 to form a system on a chip (SoC).
  • SiP system-in-package
  • SoC system on a chip
  • Computer 1400 may further include an input/output (I/O) device 1432 .
  • I/O device 1432 may include a user interface that enables a user to interact with computer 1400 ; the peripheral component interface is designed to enable peripheral components to interact with computer 1400 as well.
  • computer 1400 also includes sensors for determining at least one of environmental conditions and location information associated with computer 1400 .
  • the user interface may include, but is not limited to, a display (eg, a liquid crystal display, a touch screen display, etc.), a speaker, a microphone, one or more cameras (eg, a still image camera and/or video camera), a flashlight (eg, a LED flash) and keyboard.
  • a display eg, a liquid crystal display, a touch screen display, etc.
  • a speaker e.g., a speaker
  • a microphone e.g, a still image camera and/or video camera
  • a flashlight eg, a LED flash
  • keyboard e.g, a keyboard
  • the above-mentioned interface for use can be used to display an imaging image of a magnetic resonance imaging process (eg, a reconstructed image in FIG. 6 ), an image in k-space, and the like.
  • peripheral component interfaces may include, but are not limited to, non-volatile memory ports, audio jacks, and power connectors.
  • sensors may include, but are not limited to, gyroscope sensors, accelerometers, proximity sensors, ambient light sensors, and positioning units.
  • the positioning unit may also be part of or interact with the network interface 1420 to communicate with components of the positioning network (eg, global positioning system (GPS) satellites).
  • GPS global positioning system
  • the electronic device for performing interference cancellation in the present application is a mobile phone as an example for illustration, and the structure of the electronic device is described.
  • the mobile phone 10 may include a processor 110 , a power supply module 140 , a memory 180 , a mobile communication module 130 , a wireless communication module 120 , a sensor module 190 , an audio module 150 , a camera 170 , an interface module 160 , buttons 101 and a display screen 102, etc.
  • the structures illustrated in the embodiments of the present invention do not constitute a specific limitation on the mobile phone 10 .
  • the mobile phone 10 may include more or less components than shown, or combine some components, or separate some components, or arrange different components.
  • the illustrated components may be implemented in hardware, software, or a combination of software and hardware.
  • Processor 110 may include one or more processing units.
  • a storage unit may be provided in the processor 110 for storing instructions and data.
  • the storage unit in processor 110 is cache memory 180 .
  • the processor 110 may construct a matrix for the actual measurement signals from multiple channels, perform singular value decomposition on the matrix to obtain multiple components, and then remove the components corresponding to the interference signal (source) in the measurement signal to obtain the final valid signal.
  • the power module 140 may include power supplies, power management components, and the like.
  • the power source can be a battery.
  • the power management part is used to manage the charging of the power supply and the power supply of the power supply to other modules.
  • the mobile communication module 130 may include, but is not limited to, an antenna, a power amplifier, a filter, an LNA (Low noise amplify, low noise amplifier), and the like.
  • the wireless communication module 120 may include an antenna, and transmit and receive electromagnetic waves via the antenna.
  • the cell phone 10 can communicate with the network and other devices through wireless communication technology.
  • the mobile communication module 130 and the wireless communication module 120 of the handset 10 may also be located in the same module.
  • the display screen 102 is used for displaying human-computer interaction interfaces, images, videos, etc., for example, for displaying semantic information of speech corresponding to the valid signals processed by the processor 110 .
  • Display screen 102 includes a display panel.
  • the sensor module 190 may include a proximity light sensor, a pressure sensor, a gyro sensor, an air pressure sensor, a magnetic sensor, an acceleration sensor, a distance sensor, a fingerprint sensor, a temperature sensor, a touch sensor, an ambient light sensor, a bone conduction sensor, and the like.
  • the audio module 150 is used for converting digital audio information into analog audio signal output, or converting analog audio input into digital audio signal. Audio module 150 may also be used to encode and decode audio signals. In some embodiments, the audio module 150 may be provided in the processor 110 , or some functional modules of the audio module 150 may be provided in the processor 110 . In some embodiments, the audio module 150 may include a speaker, earpiece, microphone, and headphone jack. For example, microphones can be used to provide multiple channels for acquiring calibration data or acquiring measurement signals.
  • the cell phone 10 further includes a button 101, a motor, an indicator, and the like.
  • the key 101 may include a volume key, an on/off key, and the like.
  • Embodiments of the mechanisms disclosed herein may be implemented in hardware, software, firmware, or a combination of these implementation methods.
  • Embodiments of the present application may be implemented as a computer program or program code executing on a programmable system including at least one processor, a storage system (including volatile and nonvolatile memory and/or storage elements) , at least one input device, and at least one output device.
  • Program code may be applied to input instructions to perform the functions described herein and to generate output information.
  • the output information can be applied to one or more output devices in a known manner.
  • a processing system includes any system having a processor such as, for example, a digital signal processor (DSP), microcontroller, application specific integrated circuit (ASIC), or microprocessor.
  • DSP digital signal processor
  • ASIC application specific integrated circuit
  • the program code may be implemented in a high-level procedural language or an object-oriented programming language to communicate with the processing system.
  • the program code may also be implemented in assembly or machine language, if desired.
  • the mechanisms described in this application are not limited in scope to any particular programming language. In either case, the language may be a compiled language or an interpreted language.
  • the disclosed embodiments may be implemented in hardware, firmware, software, or any combination thereof.
  • the disclosed embodiments can also be implemented as instructions carried by or stored on one or more transitory or non-transitory machine-readable (eg, computer-readable) storage media, which can be executed by one or more processors read and execute.
  • the instructions may be distributed over a network or over other computer-readable media.
  • a machine-readable medium can include any mechanism for storing or transmitting information in a form readable by a machine (eg, a computer), including, but not limited to, floppy disks, optical disks, optical disks, read only memories (CD-ROMs), magnetic Optical Disc, Read Only Memory (ROM), Random Access Memory (RAM), Erasable Programmable Read Only Memory (EPROM), Electrically Erasable Programmable Read Only Memory (EEPROM), Magnetic or Optical Cards, Flash Memory, or Tangible machine-readable storage for transmitting information (eg, carrier waves, infrared signal digital signals, etc.) using the Internet in electrical, optical, acoustic, or other forms of propagating signals.
  • machine-readable media includes any type of machine-readable media suitable for storing or transmitting electronic instructions or information in a form readable by a machine (eg, a computer).
  • each unit/module mentioned in each device embodiment of this application is a logical unit/module.
  • a logical unit/module may be a physical unit/module or a physical unit/module.
  • a part of a module can also be implemented by a combination of multiple physical units/modules.
  • the physical implementation of these logical units/modules is not the most important, and the combination of functions implemented by these logical units/modules is the solution to the problem of this application. The crux of the technical question raised.
  • the above-mentioned device embodiments of the present application do not introduce units/modules that are not closely related to solving the technical problems raised in the present application, which does not mean that the above-mentioned device embodiments do not exist. other units/modules.

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Abstract

一种干扰消除方法、介质及设备，可以从基于多个通道接收的测量信号中消除干扰信号得到有效信号，以避免干扰信号对有效信号的影响。方法包括：从多个通道获取测量信号，测量信号中混合了有效信号和干扰信号；采用滑动时间窗将测量信号中的数据构建为第一分块Hankel矩阵，按照奇异值分解将第一分块Hankel矩阵分解为多个分量；从多个分量中识别并去除与干扰信号源对应的分量，以得到测量信号中的目标有效信号；同一列数据为同一滑动时间窗内从多个通道采样得到的数据，不同列数据为不同滑动时间窗内从多个通道采样得到的数据。可以用于消除电磁干扰信号对磁共振成像信号的影响。

Description

干扰消除方法、介质及设备 技术领域
本申请涉及信号处理技术领域，特别涉及一种干扰消除方法、介质及设备。
背景技术
随着电气、电子设备的大量应用，人们对于电子设备接收到的信号的质量的要求越来越高。通常电子设备所处的环境存在干扰(Interference)，并且电子设备的运行过程以及馈线系统也会产生干扰，这使得电子设备接收到的有效信号会受到其他干扰信号的影响。也就是说，干扰信号会对有效信号的接收造成损害，从而导致电子设备获取的有效信号失真或者信噪比(signal-to-noise ratio，SNR)降低。
例如，对于磁共振成像(Magnetic Resonance Imaging，MRI)设备而言，采集的磁共振成像信号通常会受到环境中的电磁干扰信号(ElectromagneticInterference，EMI)等干扰信号的影响，进而使得磁共振成像中存在伪影或者降低磁共振成像的信噪比，降低了磁共振成像的准确性。为了避免电磁干扰信号对磁共振成像质量的影响，通常需要对磁共振成像设备进行严格的电磁屏蔽，如将磁共振成像设备放置于特定的房间内，而电磁屏蔽将会极大地限制磁共振成像的应用场景。
发明内容
本申请实施例提供了一种干扰消除方法、介质及设备，可以从基于多个通道接收的测量信号中消除干扰信号得到有效信号，以避免干扰信号对有效信号的影响。
第一方面，本申请实施例提供了一种干扰消除方法，应用于包括具有信号接收功能的多个通道的电子设备，该方法包括：从该多个通道获取测量信号，测量信号中混合了有效信号和干扰信号；采用滑动时间窗将测量信号中的数据构建为第一分块Hankel矩阵，按照奇异值分解将第一分块Hankel矩阵分解为多个分量；从多个分量中识别并去除与干扰信号对应的分量，以得到测量信号中的目标有效信号；其中，第一分块Hankel矩阵中同一列数据均为同一滑动时间窗内从多个通道采样得到的数据，不同列数据为不同滑动时间窗内从上述多个通道采样得到的数据，一个滑动时间窗中包括至少两个采样时间点，并且相邻的两个滑动时间窗之间间隔了一个采样时间点。干扰信号在多个通道之间的耦合关系具有频域相关性，且该耦合关系在频域上连续且平滑。
具体地，上述方法可以应用于磁共振成像、同步脑电-功能磁共振成像以及 语音信号处理等场景中，但不限于此。可以理解的是，由于上述耦合关系在频域上连续且平滑，因此使得在时域上该耦合关系反映为，针对某个通道中的信号可以用该通道的相邻时间点的采样数据，以及其他通道的当前及相邻时间点的采样数据来进行线性表示，而且这些线性关系的线性系数是时不变的。如此，基于这些线性系数时不变的特性，可以实现按照上述方式采用滑动时间窗将测量信号中的数据构建为第一分块Hankel矩阵，以使得对第一分块Hankel矩阵的奇异值分解得出与电磁干扰信号等干扰信号对应的分量，进而可以去除这些分量仅保留与有效信号对应的分量。如此，便可以得到测量信号中信噪比较高的有效信号。更具体地，在磁共振成像场景中，上述测量信号包括混合的磁共振成像信号和电磁干扰信号等，按照上述干扰消除方法可以消除磁共振成像中存在的伪影、得到信噪比较高的磁共振成像信号。进而，可以极大地提高磁共振成像的质量，实现在未屏蔽或部分屏蔽的环境中正常运行低场磁共振成像设备。
在上述第一方面的一种可能的实现中，上述按照奇异值分解将第一分块Hankel矩阵分解为多个分量，可以包括：使用公式H＝U×S×V *，实现按照奇异值分解将第一分块Hankel矩阵分解为多个分量；其中，矩阵H为第一分块Hankel矩阵且为k×j阶的矩阵，矩阵U为k×n阶的矩阵，矩阵S为n×n阶对角矩阵，矩阵V *为矩阵V的共轭转置矩阵且矩阵V为j×n阶的矩阵，V的每一列对应一个信号源的分量，多个分量为矩阵V中所有列对应的分量，n为多个分量的总数，k＝m×a，m为多个通道的数量，a为一个滑动时间窗内在一个通道中采样数据的个数，j为滑动时间窗的总数。此外，j＝(t-a+1)×p，t为基于多个通道获取测量信号的采样次数,p为数据采集时相位编码线的条数(或者重复数据采集的次数)。例如，在上述多个通道包括一个接收线圈通道和两个感应线圈通道的情况下，m＝3。此时，作为一种示例，若a＝3，t＝100，p＝100,则k＝9，j＝9800。并且，假设磁共振成像设备100的信号源包括一个磁共振信号源，一个电磁干扰信号源和一个热噪声信号源，则n＝3。
在上述第一方面的一种可能的实现中，上述从多个分量中识别并去除与干扰信号对应的分量，以得到测量信号中的目标有效信号，包括：从第一分块Hankel矩阵中的多个分量中识别并去除与干扰信号源对应的分量，得到第二分块Hankel矩阵；将第二分块Hankel矩阵转换到多个通道的信号，以得到目标有效信号。作为一种示例，可以通过将第一分块Hankel矩阵中与干扰信号对应的分量中的所有数据均置零，以从第一分块Hankel矩阵中去除这些分量。此外，理想情况下第二分块Hankel矩阵中与干扰信号对应的所有数据(或分量)均被去除，如均被置零。进而，可以理解的是，上述第二分块Hankel矩阵中仅包括有效信号的分量，而不包括与电磁干扰信号源对应的分量和噪声信号源对应的分量。即第二分块Hankel矩阵中的数据可以表示测量信号中的有效信号。
在上述第一方面的一种可能的实现中，上述方法还包括：确定多个分量中的每个分量的分量类型，分量类型至少包括有效信号和干扰信号。例如，可以采用独立成分分析(Independent Component Analysis，ICA)方法或者其他盲源分 离方法等方法识别出与不同信号源对应的分量。
在上述第一方面的一种可能的实现中，上述确定多个分量中的每个分量的分量类型，包括：在电子设备为磁共振成像设备的情况下，针对多个分量中的每个分量，确定一个分量对应的频域空间中心部分的平均信号强度和边缘部分的平均信号强度之间的比值，以确定对应分量的分量类型；其中，有效信号为磁共振成像信号，干扰信号包括电磁干扰信号和热噪声中的至少一项。具体地，如果上述比值高于设定的阈值(如5)，则认为分量为磁共振信号对应的分量。反之，如果比值低于设定的阈值，则认为分量为电磁干扰信号等干扰信号对应的分量。
在上述第一方面的一种可能的实现中，上述多个通道中的每个通道均为第一类通道，或者，多个通道中包括至少一个第一类通道和至少一个第二类通道；其中，第一类通道用于接收有效信号并接收或感应干扰信号，第二类通道仅用于接收或感应干扰信号。例如，第一类通道为下文中的接收线圈通道，第二类通道为下文中的感应线圈通道。
在上述第一方面的一种可能的实现中，上述电子设备为磁共振成像设备，有效信号为磁共振成像信号，干扰信号包括电磁干扰信号和热噪声中的至少一项；第一类通道(即下文中的接收线圈通道)由一个或多个相控阵线圈(如下文中的接收线圈)实现，第二类通道(即下文中的接收线圈通道)由一个或多个相控阵线圈或贴于检测对象表面(如人体皮肤)的一个或多个电极实现。
在上述第一方面的一种可能的实现中，上述电子设备为同步脑电-功能磁共振成像设备，有效信号为脑电信号，干扰信号包括同步脑电-功能磁共振成像设备发起的射频信号和梯度信号所引起的干扰中的至少一项；第一类通道由贴附在头皮(即检测对象)表面的一个或多个电极实现；第二类通道由贴附在人体皮肤(即检测对象)表面的一个或多个电极，或者一个或多个相控阵线圈实现。
在上述第一方面的一种可能的实现中，上述测量信号为一维或者多维数据，上述第一分块Hankel矩阵是使用一维或者多维(如二维)的滑动时间窗构建的。可以理解的，测量信号的维度与构建的第一分块Hankel矩阵的滑动时间窗的维度一致。
第二方面，本申请实施例提供了一种干扰消除装置，应用于包括具有信号接收功能的多个通道的电子设备，包括：获取模块，用于从多个通道获取测量信号，测量信号中混合了有效信号和干扰信号，干扰信号在所述多个通道之间的耦合关系具有频域相关性，且所述耦合关系在频域上连续且平滑；构建模块，用于采用滑动时间窗将获取模块获取的测量信号中的数据构建为第一分块Hankel矩阵，其中，第一分块Hankel矩阵中同一列数据均为同一滑动时间窗内从多个通道采样得到的数据，不同列数据为不同滑动时间窗内从多个通道采样得到的数据，一个滑动时间窗中包括至少两个采样时间点，并且相邻的两个滑动时间窗之间间隔了一个采样时间点；分解模块，用于按照奇异值分解将构建模块构建的第一分块Hankel矩阵分解为多个分量；分离模块，用于从分解模块得到的多个分量中识别并去除与干扰信号对应的分量，以得到测量信号中的目标有效信号。例如，上 述获取模块、构建模块、分解模块和分离模块可以通过电子设备中具有这些模块或单元功能的处理器实现。
在上述第二方面的一种可能的实现中，上述分解模块，具体用于使用公式H＝U×S×V *，实现按照奇异值分解将第一分块Hankel矩阵分解为多个分量；其中，矩阵H为第一分块Hankel矩阵且为k×j阶的矩阵，矩阵U为k×n阶的矩阵，矩阵S为n×n阶对角矩阵，矩阵V *为矩阵V的共轭转置矩阵且矩阵V为j×n阶的矩阵，V的每一列对应一个信号源的分量，多个分量为矩阵V中所有列对应的分量，n为多个分量的总数，k＝m×a，m为多个通道的数量，a为一个滑动时间窗内在一个通道中采样数据的个数，j为滑动时间窗的总数。此外，j＝(t-a+1)×p，t为基于多个通道获取测量信号的采样次数,p为数据采集时相位编码线的条数(或者重复数据采集的次数)。
在上述第二方面的一种可能的实现中，上述分离模块，具体用于从第一分块Hankel矩阵中的多个分量中识别并去除与干扰信号对应的分量，得到第二分块Hankel矩阵；将第二分块Hankel矩阵转换到多个通道的信号，以得到目标有效信号。
在上述第二方面的一种可能的实现中，上述装置还包括：确定模块，用于确定多个分量中的每个分量的分量类型，分量类型至少包括有效信号和干扰信号。例如，上述确定模块可以通过电子设备中具有该块或单元功能的处理器实现。
在上述第二方面的一种可能的实现中，上述确定模块，具体用于在电子设备为磁共振成像设备的情况下，针对多个分量中的每个分量，确定一个分量对应的频域空间中心部分的平均信号强度和边缘部分的平均信号强度之间的比值，以确定对应分量的分量类型；其中，有效信号为磁共振成像信号，干扰信号包括电磁干扰信号和热噪声中的至少一项。
在上述第二方面的一种可能的实现中，上述多个通道中的每个通道均为第一类通道，或者，多个通道中包括至少一个第一类通道和至少一个第二类通道；其中，第一类通道用于接收有效信号并接收或感应干扰信号，第二类通道仅用于接收或感应干扰信号。
在上述第二方面的一种可能的实现中，上述电子设备为磁共振成像设备，有效信号为磁共振成像信号，干扰信号包括电磁干扰信号和热噪声中的至少一项；第一类通道由一个或多个相控阵线圈实现，第二类通道由一个或多个相控阵线圈、或贴附于检测对象表面的一个或多个电极实现。
在上述第二方面的一种可能的实现中，上述电子设备为同步脑电-功能磁共振成像设备，有效信号为脑电信号，干扰信号包括同步脑电-功能磁共振成像设备发起的射频信号和梯度信号中的至少一项；第一类通道由贴附在检测对象表面的一个或多个电极实现；第二类通道由贴附在检测对象表面的一个或多个电极，或者一个或多个相控阵线圈实现。
在上述第二方面的一种可能的实现中，测量信号为一维或者多维数据，上述第一分块Hankel矩阵是使用一维或者多维的滑动时间窗构建的。
第三方面，本申请实施例提供了一种计算机可读存储介质，该存储介质上存储有指令，该指令在计算机上执行时使该计算机执行上述第一方面中的干扰消除方法。
第四方面，本申请实施例提供了一种电子设备，包括：一个或多个处理器；一个或多个存储器；该一个或多个存储器存储有一个或多个程序，当该一个或者多个程序被该一个或多个处理器执行时，使得该电子设备执行上述第一方面中的干扰消除方法。
附图说明
图1根据本申请的一些实施例，示出了一种磁共振成像设备的结构示意图；
图2根据本申请的一些实施例，示出了一种磁共振成像设备的结构示意图；
图3根据本申请的一些实施例，示出了一种干扰消除方法的流程示意图；
图4根据本申请的一些实施例，示出了一种构建分块Hankel矩阵的示意图；
图5根据本申请的一些实施例，示出了一种为k空间的分布示意图；
图6根据本申请的一些实施例，示出了一种磁共振成像过程中的重建图像、k空间以及各信号分量的示意图；
图7根据本申请的一些实施例，示出了一种磁共振成像设备的计算机的框图；
图8根据本申请的一些实施例，示出了一种手机的框图。
具体实施方式
本申请的说明性实施例包括但不限于干扰消除方法、装置、介质及设备。
本申请实施例提供的干扰消除方法，可以应用于磁共振成像(Magnetic Resonance Imaging，MRI)、同步脑电-功能磁共振成像以及语音信号处理等场景中，但不限于此。具体地，电子设备可以包括具有信号接收功能的多个通道，以从多个通道的测量信号中消除干扰信号，从而得到不受干扰信号影响的有效信号，如前述应用中的磁共振成像信号、脑电信号、语音信号等。
作为一种示例，在磁共振成像场景中，有效信号可以为磁共振成像信号，而干扰信号可以为热噪声或者环境中的电磁干扰信号(ElectromagneticInterference，EMI)等。此时，电子设备可以为具有磁共振成像功能的设备，本文中将其称为磁共振成像设备。
作为另一种示例，在同步脑电-功能磁共振成像场景中，有效信号可以为脑电信号，而干扰信号可以包括电子设备运行过程产生的磁共振成像射频信号和梯度信号等。此时，上述电子设备可以为具有同步脑电-功能磁共振成像的设备，本文中可以将其称为脑电成像设备。
作为又一种示例，在语音信号处理场景中，有效信号可以为待处理语音信号，而干扰信号可以为环境噪音等。此时，上述电子设备可以为具有语音处理功能，如安装有语音助手软件的电子设备。作为一种示例，该场景下的电子设备可以包括但不限于：手机、智能音箱、平板电脑、笔记本电脑、台式电脑、超级移动个 人计算机(ultra-mobile personal computer，UMPC)、上网本，以及蜂窝电话、个人数字助理(personal digital assistant，PDA)、增强现实(augmentedreality，AR)、虚拟现实(virtual reality，VR)设备等。
以下实施例中主要以磁共振成像场景中磁共振成像设备执行干扰消除方法为例，对本申请实施例提供的干扰消除方法进行说明。类似的，本文中对于其他应用场景中电子设备执行干扰消除方法的实施细节将不做一一赘述，一些描述可以参照对磁共振成像设备执行消干扰方法的相关描述。
磁共振成像技术可以在医疗或临床应用场景中生成医学影像，以进行疾病诊断。具体地，磁共振成像技术可以利用原子核在强磁场内发生共振产生的信号进行图像重建，对人体等对象作出横断面、矢状面、冠状面和各种斜面的体层图像。
本申请实施中，磁共振成像设备可以为低场、超低场磁共振成像设备，也可以为中场、高场磁共振成像设备。作为一种示例，通常可以按磁场强度将临床应用中的磁共振成像系统划分为高场(1T以上)、中场(0.3-1T)、低场(0.1-0.3T)、超低场(0.1T以下)。
可以理解的是，通常磁共振成像设备需要部署在医院或者研究机构的特定的房间或区域内，以实现严格的电磁屏蔽，为成本较高且结构较为复杂的大型设备，受限于使用场地而无法作为通用成像设备。而不限定部署的场地，例如不限于在医院或者研究机构中使用，为可移动且成本较低的小型磁共振成像设备将极大地扩展磁共振成像的应用场景。
更具体地，本申请实施例主要应用于低场或超低场磁共振成像设备，在磁共振成像过程中消除环境电磁干扰信号等干扰信号，进而消除磁共振成像中存在的伪影，提高磁共振成像的质量，实现在未屏蔽或部分屏蔽的环境中正常运行低场磁共振成像设备。这样一来，由于磁共振成像设备不需要严格的电磁屏蔽，即不需要将磁共振成像设备放置于屏蔽间内，从而无需专门搭建屏蔽间，安装简便，可以极大地降低成本。并且，可以极大地扩展磁共振成像的应用场景，例如可以应用于床旁磁共振成像(Point-Of-Care MRI，POC MRI)，急诊室(ICU)或者医疗车和救护车等场景。
根据本申请的一些实施例，可以使用一个或者多个磁共振并行成像中常用的多通道线圈(如相控阵线圈)，或者一个或者多个可以贴于人体皮肤表面的电极来接收信号。从功能上，可以将上述线圈或者电极划分为两类。一类线圈，称为接收线圈(receiving coil)，用于接收磁共振信号(具体为磁共振成像信号)，而应避免接收到环境中的电磁干扰信号或者热噪声等干扰信号。具体地，在实际应用过程中，由于低场磁共振成像设备缺少电磁屏蔽，因此接收线圈不可避免地会受到电磁干扰的影响，即接收线圈也会接收到一些电磁干扰信号等。而另一线圈，称为感应线圈(sensing coil)，用于感应环境电磁干扰信号，这一功能也可以用电极来实现。
下面将结合附图对本申请的实施例作进一步地详细描述。
如图1所示，为本申请实施例提供的一种磁共振成像设备可能的结构示意图。 该磁共振成像设备100可以包括：计算机101、谱仪102、梯度放大器103、梯度线圈104、发射射频放大器105、发射射频线圈(也称为发射线圈)106、接收射频线圈107、接收射频放大器(也称为接收线圈)108和磁体109。
具体地，计算机101用于在操作人员的控制下向谱仪102发出指令，以触发谱仪102根据该指令生成梯度信号的波形和射频信号的波形。谱仪102生成的梯度信号经过梯度放大器103进行放大以后，由梯度线圈104形成磁场的梯度，从而实现针对磁共振信号(具体为磁共振成像信号)的空间梯度编码。具体地，空间梯度编码用于对磁共振信号进行空间定位，即区分磁共振信号的来源的位置。而谱仪102生成的射频信号经发射射频放大器105进行放大，由发射射频线圈106发射，从而激发成像区域内的质子(氢原子核)。其中，被激发的质子可以发出射频信号，该射频信号可以被接收线圈108接收到，并经过接收射频放大器107放大以后，再由谱仪102转化为数字信号，进而传送到计算机101进行处理获得图像并显示。此外，磁体109可以是能够生成主磁场的任何合适类型的磁体。
作为另一种示例，图2示出了另一种可能的磁共振成像设备100的示意图。将图2与图1相比，区别在于，图2示出的磁共振成像设备100中新增了感应线圈111和对应的接收射频放大器110，而其他部件均与图1所示的部件相同。
而感应线圈111用于感应环境中的电磁干扰信号，并经过接收射频放大器110放大后，再由谱仪102转化为数字信号并传送到计算机101进行处理。
在一些实施例中，在设计接收线圈和感应线圈时，都需要尽可能提高线圈所能提供的信噪比。即，对于接收线圈而言，应能够尽量灵敏地接收磁共振信号(具体为磁共振成像信号)，而尽可能少地受电磁干扰及热噪声的影响。对于感应线圈而言，应能够尽量灵敏地感知环境电磁干扰，而尽可能少地接收到磁共振信号，以及也尽可能少地受热噪声的影响。
此外，在一些实施例中，上述两类线圈都需要尽可能地减少热噪声的影响，例如，在实际应用中，可以通过一些冷却装置使用冷却的方式最大程度地减小线圈电阻，从而减少热噪声的影响。可以理解的是，本申请实施例对冷却装置不进行具体描述，可以参照相关技术中任意可实现的方式。
类似的，本申请实施例中的脑电成像设备也可以包括图1示出的发射线圈106和接收线圈108，用于基于相同的流程产生磁共振成像射频信号；还可以包括梯度线圈104，用于产生梯度信号。
在一些实施例中，上述接收线圈和感应线圈可以使用单个或多个广泛应用于现代医学磁共振成像中的相控阵线圈来实现。此外，扫描对象为人体，上述感应线圈还可以替换为贴于人体皮肤表面的电极，该电极可以用于感应人体所接收到的电磁干扰信号，从而用于消除接收线圈的测量信号中的电磁干扰信号。
可以理解的是，本申请实施例中，磁共振成像设备100涉及的具有信号接收功能的多个通道可以包括单个相控阵线圈的多个通道，也可以包括多个线圈的多个通道，本申请对此不作具体限定。此外，本申请实施例中，对磁共振成像设备100中的接收线圈和感应线圈的设计、布局(部署位置、部署方向等)不做具体 限定，可以为任意可实现的方案。
更具体地，本申请的一些实施例中，针对磁共振设备100，接收线圈中的通道可以称为接收线圈通道。其中，接收线圈的通道的数量越多，将有利于提高接收线圈接收得到磁共振信号的信噪比(signal-to-noiseratio，SNR)，或者使得接收线圈可以提供并行成像的能力。在本申请实施例中，多个通道的接收线圈还可以用于增强其对电磁干扰信号的识别与消除能力。感应线圈中的通道可以称为感应线圈通道。其中，感应线圈的通道的数目越多，越能够准确刻画出电磁干扰信号的特征，从而准确通过感应线圈接收的到电磁干扰信号估计出接收线圈所接收到的电磁干扰信号。
例如，图1示出的磁共振成像设备100可以提供一个接收线圈且该接收线圈具有多个通道，或者，提供多个接收线圈且每个接收线圈通道具有一个或多个通道，但不限于此。此时，磁共振成像设备100提供的多个通道均为接收线圈通道。
例如，图2示出的磁共振成像设备100可以提供一个接收线圈和一个感应线圈，且接收线圈具有一个通道，而感应线圈具有两个通道，但不限于此。此时，磁共振成像设备100提供的多个通道包括接收线圈通道和感应线圈通道。
类似的，在同步脑电-功能磁共振成像场景中，脑电成像设备提供的具有信号接收功能的多个通道可以由贴附于头皮的电极实现。以及，在语音信号处理场景中，电子设备提供的多个通道可以为多个麦克风提供的多个模拟信号通道。
需要说明的是，电磁干扰信号在磁共振成像设备100的多个通道之间具有耦合关系，该耦合关系具体为电磁干扰信号在多个通道之间的频域相关性，该耦合关系在频域上连续且平滑。可以理解的是，电磁干扰信号在多个通道之间的频域相关性，可以为各个通道接收的电磁干扰信号在不同频点上的线性关系。
在一些实施例中，由于上述耦合关系在频域上连续且平滑，因此使得在时域上该耦合关系反映为，针对某个通道的信号可以用该通道的相邻时间点的采样；以及其他通道的当前及相邻时间点的采样，来进行线性表示，而且这些线性关系的线性系数是时不变的。
基于上面的描述，下面具体介绍核磁共振成像设备100执行电磁干扰消除方法的主要工作流程。具体地，上述对图2示出的磁共振成像设备100中描述的技术细节在下述方法流程中依然适用，为了避免重复，有些将不再赘述。在一些实施例中，本申请的电磁干扰消除方法的执行主体可以为磁共振成像设备100，具体为该磁共振成像设备100中的计算机101。如图3所示，为本申请的提供的一种电磁干扰消除方法的流程示意图，可以包括下述步骤301-步骤306：
步骤301：磁共振成像设备100从多个通道接收测量信号，该测量信号中包括混合的磁共振成像信号和电磁干扰信号。
例如，对于图1示出的磁共振成像设备100，上述多个通道均为接收线圈通道。对于图2示出的磁共振成像设备100，上述多个通道包括接收线圈通道和感应线圈通道。
在一些实施例中，对于低场磁共振成像设备100，上述测量信号为基于多个 通道多次采集得到的。可以理解的是，在高场磁共振成像设备100(例如，磁场强度大于1T)中，往往只需要采集一次就行；在低场或者超低场系统中，由于单次采集的信号的SNR较低，所以需要将多次采集的数据取平均值以提高最终的磁共振成像信号的SNR。
步骤302：磁共振成像设备100采用滑动时间窗将测量信号中的数据构建为第一分块Hankel矩阵。
其中，在第一分块Hankel矩阵中同一列数据均为同一时间窗内从多个通道采样得到的数据，不同列数据为不同时间窗内从多个通道采样得到的数据。
在一些实施例中，磁共振成像设备100可以采用滑动时间窗将测量信号中的数据构建为第一分块Hankel矩阵，其中，一个滑动时间窗内从多个通道采样得到的数据的向量作为第一分块Hankel矩阵的一列数据，不同滑动时间窗采样得到的向量对应第一分块Hankel矩阵中的不同列的数据，一个滑动时间窗中包括至少两个采样时间点，并且相邻的两个滑动时间窗之间间隔了一个采样时间点。
步骤303：磁共振成像设备100使用公式H＝U×S×V *，按照奇异值分解将第一分块Hankel矩阵分解为多个分量，矩阵H为第一分块Hankel矩阵。
其中，矩阵H为第一分块Hankel矩阵且为k×j阶的矩阵，矩阵U为k×n阶，矩阵S为n×n阶对角矩阵，矩阵V *为矩阵V的共轭转置矩阵且矩阵V为j×n阶的矩阵，n为多个分量的数量，V的每一列对应一个信号源的分量，多个分量为矩阵V中所有列对应的分量，k＝m×a，m为多个通道的数量m，a为一个滑动时间窗内在一个通道中采样数据的个数，j为滑动时间窗的总数，j＝(t-a+1)×p，t为基于多个通道获取测量信号的采样次数,p为数据采集时相位编码线的条数(或者重复数据采集的次数)。例如，在上述多个通道包括一个接收线圈通道和两个感应线圈通道的情况下，m＝3。此时，作为一种示例，若a＝3，t＝100，p＝100，则k＝9，j＝9800。并且，假设磁共振成像设备100的信号源包括一个磁共振信号源，一个电磁干扰信号源和一个热噪声信号源，则n＝3。
作为一种示例，图4示出了构建分块Hankel矩阵的示例图。其中，图4示出了磁共振成像设备100基于多个通道采集得到的数据。例如，在这些数据为上述多个通道采集得到的测量信号时该分块Hankel矩阵为上述第一分块Hankel矩阵H。其中，图4示出的一个虚线方框为一个滑动时间窗，每个滑动时间窗中包括3个采样时间点，滑动时间窗中的一个圆圈表示从一个通道采样得到的一个数据。其中，N个通道即为上述磁共振成像设备100中的多个通道，每个通道中采样得到的数据按照采样时间的先后顺序排序。例如，N个通道中的通道1至通道N-1均为感应线圈通道，而通道N为接收线圈通道，N可以为3。
步骤304：磁共振成像设备100确定多个分量中的每个分量的分量类型，分量类型至少包括磁共振成像信号和电磁干扰信号。
在一些其他实施例中，上述分量类型还可以包括噪声，如热噪声。可以理解的是，一种分量类型的分量对应于一种信号源，例如分量类型为磁共振成像信号的分量对应于磁共振成像信号源，分量类型为电磁干扰信号的分量对应于磁干扰 信号源。
步骤305：磁共振成像设备100从第一分块Hankel矩阵中的多个分量中识别并去除与电磁干扰信号源对应的分量和噪声信号源对应的分量，得到第二分块Hankel矩阵。
作为一种示例，可以通过将第一分块Hankel矩阵中与电磁干扰信号等干扰信号对应的分量中的所有数据均置零，以从第一分块Hankel矩阵中去除这些分量。此外，理想情况下第二分块Hankel矩阵中与电磁干扰信号对应的所有数据(或分量)均被去除，如均被置零。
进而，可以理解的是，上述第二分块Hankel矩阵中仅包括磁共振成像信号的分量(即数据)，而不包括与电磁干扰信号源对应的分量和噪声信号源对应的分量。即第二分块Hankel矩阵中的数据可以表示测量信号中的有效信号。
可以理解的是，本申请中，基于干扰信号在多个通道之间的耦合关系在时域上具有时不变的线性系数的特性，可以按照上述方式采用滑动时间窗将测量信号中的数据构建为第一分块Hankel矩阵，以对第一分块Hankel矩阵的奇异值分解得出与电磁干扰信号等干扰信号对应的分量，进而去除这些分量。
在一些实施例中，磁共振成像设备100识别各个分量的方式可以为：磁共振成像设备100针对每个分量，确定一个分量对应的频域空间中心部分的平均信号强度和边缘部分的平均信号强度之间的比值，以确定对应分量的分量类型。
频域空间即为k空间，其中k空间的中心为低频部分，而边缘被称为高频部分。如图5所示，为k空间的分布示意图，虚线框标示的范围为低频部分，而实线框标示的范围为高频部分。
可以理解的是，为了判断某分量是否为磁共振成像信号，可以分别计算该分量在k空间低频部分和高频部分的平均信号强度，如果低频部分的平均信号强度显著高于高频部分的平均信号强度，就可以认为该分量为磁共振成像信号对应的分量；反之，则认为该分量为电磁干扰信号或者噪声对应的分量。
例如，如图6所示，为磁共振成像过程中的重建图像、k空间以及各个分量的示意图。其中，图6中的(A)示出的左侧一列示出了重建图像中的电磁干扰信号分量和磁共振信号(即磁共振成像信号)分量的示意图，右侧一列示出了该重建图像的k空间的电磁干扰信号分量和磁共振信号分量的示意图。显然，电磁干扰信号分量处于k空间的边缘部分，而磁共振信号分量处于k空间的中心部分。
作为一种示例，在实际的实施中，磁共振成像设备100可以计算每个分量中低频部分与高频部分的平均信号强度的比值，并设定合适的阈值(比如5，该阈值需要根据包括噪声水平等因素在内实际情况来调整)。如果该比值高于设定的阈值，则认为该分量为磁共振信号对应的分量。反之，如果比值低于设定的阈值，则认为该分量为电磁干扰信号等干扰信号对应的分量。
此外，本申请实施例不限于上述示例出的识别分量的方法，还可以是其他方法，例如还可以采用独立成分分析(Independent Component Analysis，ICA)的方法或者其他盲源分离方法等方法识别出与不同信号源对应的分量，本申请实 施例对此不做赘述。
可以理解的是，上述第二分块Hankel矩阵中即包括磁共振成像信号的分量(即数据)，而不包括与电磁干扰信号源对应的分量和噪声信号源对应的分量。
步骤306：磁共振成像设备100将第二分块Hankel矩阵转换到上述多个通道，并得到目标磁共振成像信号。
具体地，磁共振成像设备100将第二分块Hankel矩阵转换到上述多个通道之后，可以得到该多个通道中接收线圈通道中的信噪比较高的磁共振成像信号，即为上述目标磁共振信号。
例如，如图6中的(B)的上边一行示出了按照上述方法消除电磁干扰前的重建图像和对应的k空间示意图，下边一行示出了按照上述方法消除电磁干扰后的重建图像和对应的k空间示意图。显然，按照本申请提供的电磁干扰消除方法得到的重建图像的伪影更少质量更高。
可以理解的是，本申请提供的电磁干扰消除方法，基于奇异值分解可以从磁共振成像设备100的多个通道采集的信号中消除电磁干扰信号，而无需获知电磁干扰信号在该多个通道之间的耦合关系，有利于简化消除电磁干扰信号的过程，并提升电磁干扰消除的稳定性。
类似的，对于本申请实施例应用的其他场景，电子设备也可以按照与上述步骤301-306相似的步骤实施干扰消除方法，区别在于，执行主体不同，以及有效信号和干扰信号的类型不同。
更具体的，针对本申请实施例应用的其他场景，可以基于独立成分分析的方法或者盲源分离方法等识别出与不同信号源对应的分量，本申请实施例对此不做赘述。例如，假设不同信号源的有效信号和干扰信号是相互独立的，可以采用独立成分分析的方法，从多个通道接收得到的信号中获得源信号，判断源信号的属性(如有效信号或者干扰信号)，只保留有效信号对应的源信号，并重新合成第一类通道(即用于接收有效信号的通道)的信号。当然，本申请可应用的分量识别方法包括但不限于上述示例，还可以为其他任意可实现的方式。
此外，在其他一些实施例中，测量信号中的有效信号和干扰信号可以为一维或多维(如二维)数据。此时，干扰消除方法中采用一维或多维滑动时间窗构建分块Hankel矩阵，而测量信号的维数与滑动时间窗的维数一致，其他过程与上述步骤301-步骤306中的相关描述类似，不再赘述。
现在参考图7，所示为根据本申请的一个实施例的磁共振成像设备100中的计算机的框图。图7示意性地示出了根据多个实施例的示例计算机1400。在一个实施例中，系统1400可以包括一个或多个处理器1404，与处理器1404中的至少一个连接的系统控制逻辑1408，与系统控制逻辑1408连接的系统内存1412，与系统控制逻辑1408连接的非易失性存储器(NVM)1416，以及与系统控制逻辑1408连接的网络接口1420。
在一些实施例中，处理器1404可以包括一个或多个单核或多核处理器。在一些实施例中，处理器1404可以包括通用处理器和专用处理器(例如，图形处 理器，应用处理器，基带处理器等)的任意组合。在系统1400采用eNB(Evolved Node B，增强型基站)101或RAN(Radio Access Network，无线接入网)控制器102的实施例中，处理器1404可以被配置为执行各种符合的实施例，例如，如图3所示的实施例。例如，处理器1404可以对来自多个通道的实际测量信号构建矩阵，并对矩阵进行奇异值分解得到多个分量，进而去除测量信号中的与干扰信号(源)对应的分量，以得到最终的有效信号。
在一些实施例中，系统控制逻辑1408可以包括任意合适的接口控制器，以向处理器1404中的至少一个和/或与系统控制逻辑1408通信的任意合适的设备或组件提供任意合适的接口。
在一些实施例中，系统控制逻辑1408可以包括一个或多个存储器控制器，以提供连接到系统内存1412的接口。系统内存1412可以用于加载以及存储数据和/或指令。在一些实施例中系统1400的内存1412可以包括任意合适的易失性存储器，例如合适的动态随机存取存储器(DRAM)。
NVM/存储器1416可以包括用于存储数据和/或指令的一个或多个有形的、非暂时性的计算机可读介质。在一些实施例中，NVM/存储器1416可以包括闪存等任意合适的非易失性存储器和/或任意合适的非易失性存储设备，例如HDD(Hard Disk Drive，硬盘驱动器)，CD(Compact Disc，光盘)驱动器，DVD(Digital Versatile Disc，数字通用光盘)驱动器中的至少一个。
NVM/存储器1416可以包括安装系统1400的装置上的一部分存储资源，或者它可以由设备访问，但不一定是设备的一部分。例如，可以经由网络接口1420通过网络访问NVM/存储1416。
特别地，系统内存1412和NVM/存储器1416可以分别包括：指令1424的暂时副本和永久副本。指令1424可以包括：由处理器1404中的至少一个执行时导致计算机1400实施如图3所示的方法的指令。在一些实施例中，指令1424、硬件、固件和/或其软件组件可另外地/替代地置于系统控制逻辑1408，网络接口1420和/或处理器1404中。
网络接口1420可以包括收发器，用于为系统1400提供无线电接口，进而通过一个或多个网络与任意其他合适的设备(如前端模块，天线等)进行通信。在一些实施例中，网络接口1420可以集成于系统1400的其他组件。例如，网络接口1420可以集成于处理器1404的，系统内存1412，NVM/存储器1416，和具有指令的固件设备(未示出)中的至少一种，当处理器1404中的至少一个执行所述指令时，计算机1400实现如图3所示的方法。
网络接口1420可以进一步包括任意合适的硬件和/或固件，以提供多输入多输出无线电接口。例如，网络接口1420可以是网络适配器，无线网络适配器，电话调制解调器和/或无线调制解调器。
在一个实施例中，处理器1404中的至少一个可以与用于系统控制逻辑1408的一个或多个控制器的逻辑封装在一起，以形成系统封装(SiP)。在一个实施例中，处理器1404中的至少一个可以与用于系统控制逻辑1408的一个或多个控制 器的逻辑集成在同一管芯上，以形成片上系统(SoC)。
计算机1400可以进一步包括：输入/输出(I/O)设备1432。I/O设备1432可以包括用户界面，使得用户能够与计算机1400进行交互；外围组件接口的设计使得外围组件也能够与计算机1400交互。在一些实施例中，计算机1400还包括传感器，用于确定与计算机1400相关的环境条件和位置信息的至少一种。
在一些实施例中，用户界面可包括但不限于显示器(例如，液晶显示器，触摸屏显示器等)，扬声器，麦克风，一个或多个相机(例如，静止图像照相机和/或摄像机)，手电筒(例如，发光二极管闪光灯)和键盘。例如，上述用于界面可以用于显示磁共振成像过程的成像图像(如图6中的重建图像)以及k空间的图像等。
在一些实施例中，外围组件接口可以包括但不限于非易失性存储器端口、音频插孔和电源接口。
在一些实施例中，传感器可包括但不限于陀螺仪传感器，加速度计，近程传感器，环境光线传感器和定位单元。定位单元还可以是网络接口1420的一部分或与网络接口1420交互，以与定位网络的组件(例如，全球定位系统(GPS)卫星)进行通信。
类似的，对于本申请实施例应用的语音处理场景，在一些实施例中，以本申请执行干扰消除的电子设备为手机为例进行说明，描述电子设备的结构。
如图8所示，手机10可以包括处理器110、电源模块140、存储器180，移动通信模块130、无线通信模块120、传感器模块190、音频模块150、摄像头170、接口模块160、按键101以及显示屏102等。
可以理解的是，本发明实施例示意的结构并不构成对手机10的具体限定。在本申请另一些实施例中，手机10可以包括比图示更多或更少的部件，或者组合某些部件，或者拆分某些部件，或者不同的部件布置。图示的部件可以以硬件，软件或软件和硬件的组合实现。
处理器110可以包括一个或多个处理单元。处理器110中可以设置存储单元，用于存储指令和数据。在一些实施例中，处理器110中的存储单元为高速缓冲存储器180。例如，处理器110可以对来自多个通道的实际测量信号构建矩阵，并对矩阵进行奇异值分解得到多个分量，进而去除测量信号中的与干扰信号(源)对应的分量，以得到最终的有效信号。
电源模块140可以包括电源、电源管理部件等。电源可以为电池。电源管理部件用于管理电源的充电和电源向其他模块的供电。
移动通信模块130可以包括但不限于天线、功率放大器、滤波器、LNA(Low noise amplify，低噪声放大器)等。
无线通信模块120可以包括天线，并经由天线实现对电磁波的收发。手机10可以通过无线通信技术与网络以及其他设备进行通信。
在一些实施例中，手机10的移动通信模块130和无线通信模块120也可以位于同一模块中。
显示屏102用于显示人机交互界面、图像、视频等，例如，用于显示处理器110处理得到的有效信号对应的语音表示语义信息。显示屏102包括显示面板。
传感器模块190可以包括接近光传感器、压力传感器，陀螺仪传感器，气压传感器，磁传感器，加速度传感器，距离传感器，指纹传感器，温度传感器，触摸传感器，环境光传感器，骨传导传感器等。
音频模块150用于将数字音频信息转换成模拟音频信号输出，或者将模拟音频输入转换为数字音频信号。音频模块150还可以用于对音频信号编码和解码。在一些实施例中，音频模块150可以设置于处理器110中，或将音频模块150的部分功能模块设置于处理器110中。在一些实施例中，音频模块150可以包括扬声器、听筒、麦克风以及耳机接口。例如，麦克风可以用于提供多个通道，用于获取校准数据或者采集测量信号。
在一些实施例中，手机10还包括按键101、马达以及指示器等。其中，按键101可以包括音量键、开/关机键等。
本申请公开的机制的各实施例可以被实现在硬件、软件、固件或这些实现方法的组合中。本申请的实施例可实现为在可编程系统上执行的计算机程序或程序代码，该可编程系统包括至少一个处理器、存储系统(包括易失性和非易失性存储器和/或存储元件)、至少一个输入设备以及至少一个输出设备。
可将程序代码应用于输入指令，以执行本申请描述的各功能并生成输出信息。可以按已知方式将输出信息应用于一个或多个输出设备。为了本申请的目的，处理系统包括具有诸如例如数字信号处理器(DSP)、微控制器、专用集成电路(ASIC)或微处理器之类的处理器的任何系统。
程序代码可以用高级程序化语言或面向对象的编程语言来实现，以便与处理系统通信。在需要时，也可用汇编语言或机器语言来实现程序代码。事实上，本申请中描述的机制不限于任何特定编程语言的范围。在任一情形下，该语言可以是编译语言或解释语言。
在一些情况下，所公开的实施例可以以硬件、固件、软件或其任何组合来实现。所公开的实施例还可以被实现为由一个或多个暂时或非暂时性机器可读(例如，计算机可读)存储介质承载或存储在其上的指令，其可以由一个或多个处理器读取和执行。例如，指令可以通过网络或通过其他计算机可读介质分发。因此，机器可读介质可以包括用于以机器(例如，计算机)可读的形式存储或传输信息的任何机制，包括但不限于，软盘、光盘、光碟、只读存储器(CD-ROMs)、磁光盘、只读存储器(ROM)、随机存取存储器(RAM)、可擦除可编程只读存储器(EPROM)、电可擦除可编程只读存储器(EEPROM)、磁卡或光卡、闪存、或用于利用因特网以电、光、声或其他形式的传播信号来传输信息(例如，载波、红外信号数字信号等)的有形的机器可读存储器。因此，机器可读介质包括适合于以机器(例如，计算机)可读的形式存储或传输电子指令或信息的任何类型的机器可读介质。
在附图中，可以以特定布置和/或顺序示出一些结构或方法特征。然而，应该理解，可能不需要这样的特定布置和/或排序。而是，在一些实施例中，这些 特征可以以不同于说明性附图中所示的方式和/或顺序来布置。另外，在特定图中包括结构或方法特征并不意味着暗示在所有实施例中都需要这样的特征，并且在一些实施例中，可以不包括这些特征或者可以与其他特征组合。
需要说明的是，本申请各设备实施例中提到的各单元/模块都是逻辑单元/模块，在物理上，一个逻辑单元/模块可以是一个物理单元/模块，也可以是一个物理单元/模块的一部分，还可以以多个物理单元/模块的组合实现，这些逻辑单元/模块本身的物理实现方式并不是最重要的，这些逻辑单元/模块所实现的功能的组合才是解决本申请所提出的技术问题的关键。此外，为了突出本申请的创新部分，本申请上述各设备实施例并没有将与解决本申请所提出的技术问题关系不太密切的单元/模块引入，这并不表明上述设备实施例并不存在其它的单元/模块。
需要说明的是，在本专利的示例和说明书中，诸如第一和第二等之类的关系术语仅仅用来将一个实体或者操作与另一个实体或操作区分开来，而不一定要求或者暗示这些实体或操作之间存在任何这种实际的关系或者顺序。而且，术语“包括”、“包含”或者其任何其他变体意在涵盖非排他性的包含，从而使得包括一系列要素的过程、方法、物品或者设备不仅包括那些要素，而且还包括没有明确列出的其他要素，或者是还包括为这种过程、方法、物品或者设备所固有的要素。在没有更多限制的情况下，由语句“包括一个”限定的要素，并不排除在包括所述要素的过程、方法、物品或者设备中还存在另外的相同要素。
虽然通过参照本申请的某些优选实施例，已经对本申请进行了图示和描述，但本领域的普通技术人员应该明白，可以在形式上和细节上对其作各种改变，而不偏离本申请的精神和范围。

Claims (11)

  1. 一种干扰消除方法，应用于包括具有信号接收功能的多个通道的电子设备，其特征在于，包括：
    从所述多个通道获取测量信号，所述测量信号中混合了有效信号和干扰信号，所述干扰信号在所述多个通道之间的耦合关系具有频域相关性，且所述耦合关系在频域上连续且平滑；
    采用滑动时间窗将所述测量信号中的数据构建为第一分块Hankel矩阵，其中，所述第一分块Hankel矩阵中同一列数据均为同一滑动时间窗内从所述多个通道采样得到的数据，不同列数据为不同滑动时间窗内从所述多个通道采样得到的数据，一个所述滑动时间窗中包括至少两个采样时间点，并且相邻的两个所述滑动时间窗之间间隔了一个采样时间点；
    按照奇异值分解将所述第一分块Hankel矩阵分解为多个分量；
    从所述多个分量中识别并去除与干扰信号源对应的分量，以得到所述测量信号中的目标有效信号。
  2. 根据权利要求1所述的方法，其特征在于，所述按照奇异值分解将所述第一分块Hankel矩阵分解为多个分量，包括：
    使用公式H＝U×S×V *，实现按照奇异值分解将所述第一分块Hankel矩阵分解为多个分量；
    其中，矩阵H为所述第一分块Hankel矩阵且为k×j阶的矩阵，矩阵U为k×n阶的矩阵，矩阵S为n×n阶对角矩阵，矩阵V *为矩阵V的共轭转置矩阵且矩阵V为j×n阶的矩阵，V的每一列对应一个信号源的分量，所述多个分量为矩阵V中所有列对应的分量，n为所述多个分量的总数，k＝m×a，m为所述多个通道的数量，a为一个所述滑动时间窗内在一个通道中采样数据的个数，j为所述滑动时间窗的总数。
  3. 根据权利要求1或2所述的方法，其特征在于，所述从所述多个分量中识别并去除与干扰信号源对应的分量，以得到所述测量信号中的目标有效信号，包括：
    从所述第一分块Hankel矩阵中的所述多个分量中识别并去除与干扰信号对应的分量，得到第二分块Hankel矩阵；
    将所述第二分块Hankel矩阵转换到所述多个通道的信号，以得到所述目标有效信号。
  4. 根据权利要求1至3中任一项所述的方法，其特征在于，所述方法还包括：
    确定所述多个分量中的每个分量的分量类型，所述分量类型至少包括有效信号和干扰信号。
  5. 根据权利要求4所述的方法，其特征在于，所述确定多个分量中的每个分量的分量类型，包括：
    在所述电子设备为磁共振成像设备的情况下，针对所述多个分量中的每个分 量，确定一个分量对应的频域空间中心部分的平均信号强度和边缘部分的平均信号强度之间的比值，以确定对应分量的分量类型；
    其中，所述有效信号为磁共振成像信号，所述干扰信号包括电磁干扰信号和热噪声中的至少一项。
  6. 根据权利要求1至5中任一项所述的方法，其特征在于，所述多个通道中的每个通道均为第一类通道，或者，所述多个通道中包括至少一个所述第一类通道和至少一个第二类通道；
    其中，所述第一类通道用于接收有效信号并接收或感应干扰信号，所述第二类通道仅用于接收或感应干扰信号。
  7. 根据权利要求6所述的方法，其特征在于，所述电子设备为磁共振成像设备，所述有效信号为磁共振成像信号，所述干扰信号包括电磁干扰信号和热噪声中的至少一项；
    所述第一类通道由一个或多个相控阵线圈实现；所述第二类通道由一个或多个相控阵线圈，或者贴于检测对象表面的一个或多个电极实现。
  8. 根据权利要求6所述的方法，其特征在于，所述电子设备为同步脑电-功能磁共振成像设备，所述有效信号为脑电信号，所述干扰信号包括所述同步脑电-功能磁共振成像设备的射频信号和梯度信号所引起的干扰中的至少一项；
    所述第一类通道由贴附在检测对象表面的一个或多个电极实现；所述第二类通道由贴附在检测对象表面的一个或多个电极，或者一个或多个相控阵线圈实现。
  9. 根据权利要求1所述的方法，其特征在于，所述测量信号为一维或者多维数据，所述第一分块Hankel矩阵是使用一维或者多维的滑动时间窗构建的。
  10. 一种计算机可读存储介质，其特征在于，所述存储介质上存储有指令，所述指令在计算机上执行时使所述计算机执行权利要求1至9中任一项所述的干扰消除方法。
  11. 一种电子设备，其特征在于，包括：一个或多个处理器；一个或多个存储器；所述一个或多个存储器存储有一个或多个程序，当所述一个或者多个程序被所述一个或多个处理器执行时，使得所述电子设备执行权利要求1至9中任一项所述的干扰消除方法。
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