Electromagnetic interference suppression techniques for magnetic resonance imaging

Abstract

Systems and methods for suppressing electromagnetic interference (EMI) in magnetic resonance (MR) data are provided. These systems and methods include identifying a first subset of MR data that is affected by EMI and suppressing EMI in the first subset to obtain a second subset of MR data. Suppression of EMI in the first subset is performed by applying filtering to the first subset of MR data to suppress contributions of MR spin echo signals in the first subset of MR data, thereby obtaining signal suppressed MR data; suppressing EMI in the signal suppressed MR data to obtain EMI suppressed MR data; and applying the filtered inverse to the EMI suppressed MR data to obtain a second subset of MR data. These systems and methods include generating MR images using the second subset of MR data and outputting the generated MR images.

Description

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0002] This application claims the benefit of and priority to U.S. Provisional Patent Application No. 63 / 351,710, filed on June 13, 2022, the entire contents of which are incorporated herein by reference. Background Art

[0003] Magnetic resonance imaging (MRI) provides an important imaging modality for many applications and is widely used in clinical and research settings to produce images of the interior of the human body. In general, MRI is based on detecting magnetic resonance (MR) signals, which are electromagnetic waves emitted by atoms in response to changes in state caused by an applied electromagnetic field. For example, nuclear magnetic resonance (NMR) technology involves detecting MR signals emitted from the nuclei of excited atoms upon realignment or relaxation of the nuclear spins of atoms in the object being imaged (e.g., atoms in human tissue). The detected MR signals can be processed to produce images that enable investigation of internal structures and / or biological processes in the body for diagnostic, therapeutic and / or research purposes in the context of medical applications. Summary of the invention

[0004] Some embodiments provide a method for suppressing electromagnetic interference (EMI) in magnetic resonance data (MR data) obtained by a magnetic resonance imaging system (MRI system). The method includes: using at least one computer hardware processor to: identify a first subset of the MR data that is affected by EMI; suppress EMI in the first subset of the MR data to obtain a second subset of the MR data by: applying a filter to the first subset of the MR data to suppress the contribution of MR spin echo signals in the first subset of the MR data, thereby obtaining signal-suppressed MR data; suppressing EMI in the signal-suppressed MR data to obtain EMI-suppressed MR data; and applying the inverse of the filter to the EMI-suppressed MR data to obtain the second subset of the MR data; generating an MR image using the second subset of the MR data; and outputting the generated MR image.

[0005] In some embodiments, suppressing EMI in the signal-suppressed MR data includes using component decomposition to obtain the EMI-suppressed MR data.

[0006] In some embodiments, the first subset of the MR data includes multiple data portions for corresponding multiple frequency or time intervals, and wherein, suppressing EMI in the first subset of the MR data includes: for each specific data portion among the multiple data portions, applying the filtering to the specific data portion to obtain a corresponding signal-suppressed MR data portion; suppressing EMI in the corresponding signal-suppressed MR data portion to obtain a corresponding EMI-suppressed MR data portion; and applying the inverse of the filtering to the EMI-suppressed MR data portion.

[0007] In some embodiments, suppressing EMI in the corresponding signal-suppressed MR data portion includes: determining a component decomposition of the corresponding signal-suppressed MR data portion; modifying the component decomposition by setting at least one component value of the component decomposition to a predetermined value or by multiplying at least one component value of the component decomposition by a predetermined weight; and obtaining the corresponding EMI-suppressed MR data portion using the modified component decomposition.

[0008] In some embodiments, the MRI system includes multiple radio frequency coils, i.e., multiple RF coils, and each of the multiple data portions includes measurements made by each of the multiple RF coils for corresponding frequencies or time intervals in the multiple frequency or time intervals.

[0009] In some embodiments, the data in the corresponding signal suppressed MR data portion is organized as N c ×M matrix, where N c is an integer representing the number of RF coils and M is one or more further dimensions representing the number of measurements performed by each of the RF coils, and determining the component decomposition of the corresponding signal suppressed MR data portion comprises: determining the N c Singular value decomposition of the .×M matrix.

[0010] In some embodiments, the data in the corresponding signal suppressed MR data portion is organized as N c ×M matrix, where N c is an integer representing the number of RF coils and M represents a set of multiple dimensions of the number of measurements performed by each of the RF coils, and determining the component decomposition of the corresponding signal suppressed MR data portion comprises: determining the N c High-order singular value decomposition of a ×M matrix.

[0011] In some embodiments, the decomposition is performed using one of a plurality of component decomposition methods including, but not limited to, principal component analysis (PCA), independent component analysis (ICA), or sparse principal component analysis (SPCA).

[0012] In some embodiments, the method further comprises, prior to identifying the first subset of the MR data, generating the MR data by operating the MRI system according to a spin echo or gradient echo pulse sequence.

[0013] In some embodiments, the spin echo pulse sequence is selected from the group consisting of a T1 pulse sequence, a T2 pulse sequence, a fluid attenuated inversion recovery (FLAIR) pulse sequence, and a diffusion weighted imaging (DWI) pulse sequence.

[0014] In some embodiments, the method further comprises, after generating the MR data and before identifying the first subset, suppressing EMI in the MR data detected by an auxiliary coil of the MRI system.

[0015] In some embodiments, the EMI is narrowband EMI, and wherein the MR data includes sensor domain data in a plurality of frequency intervals, and the EMI is present in a frequency or time interval of the plurality of frequency or time intervals.

[0016] In some embodiments, the EMI exists in no more than a threshold number of adjacent frequency or time intervals among the plurality of frequency or time intervals.

[0017] In some embodiments, the EMI is present in an nth frequency or time interval among the multiple frequency or time intervals, and applying the filtering to the first subset of MR data includes: calculating a weighted linear combination of data in multiple frequency or time intervals including the nth frequency or time interval using weights determined by coefficients of the filtering.

[0018] In some embodiments, the MR data includes data in multiple frequency or time intervals, the EMI exists in multiple adjacent frequency or time intervals, and applying the filter to the first subset of the MR data includes: applying a convolution filter, the convolution filter having a length at least equal to the number of adjacent frequency or time intervals in the multiple adjacent frequency or time intervals.

[0019] In some embodiments, identifying the first subset of the MR data includes identifying data in a single frequency or time interval or a set of adjacent frequency or time intervals of the MR data that are affected by EMI.

[0020] In some embodiments, identifying the first subset of the MR data is performed by analyzing a portion of the MR data acquired during at least one predetermined echo signal of a pulse sequence used to acquire the MR data.

[0021] In some embodiments, identifying the first subset of the MR data comprises determining whether data in the single frequency or time interval or in the set of adjacent frequency or time intervals has a magnitude greater than a threshold.

[0022] In some embodiments, generating the MR image includes: modifying the MR data by replacing the first subset of the MR data with the second subset of the MR data to obtain modified MR data; and generating the MR image using the modified MR data.

[0023] In some embodiments, the MRI system includes an RF coil configured to transmit radio frequency pulses (RF pulses), and determining the first subset of the MR data includes transforming the MR data into a reference frame of the transmitted RF pulses.

[0024] Some embodiments provide a magnetic resonance imaging system, or MRI system, comprising: a magnetic system having a plurality of magnetic components for generating a magnetic field for performing MRI by acquiring MR data; and at least one processor configured to: identify a first subset of the MR data that is affected by electromagnetic interference, or EMI; suppress EMI in the first subset of the MR data to obtain a second subset of the MR data by: applying a filter to the first subset of the MR data to suppress a contribution of MR spin echo signals in the first subset of the MR data, thereby obtaining signal-suppressed MR data; suppress EMI in the signal-suppressed MR data to obtain EMI-suppressed MR data; and apply an inverse of the filter to the EMI-suppressed MR data to obtain the second subset of the MR data; generate an MR image using the second subset of the MR data; and output the generated MR image.

[0025] Some embodiments provide at least one tangible computer-readable storage medium storing processor-executable instructions which, when executed by at least one processor, cause the at least one processor to perform a method for suppressing electromagnetic interference (EMI) in magnetic resonance data (MR data) obtained by a magnetic resonance imaging system (MRI system), the method comprising: identifying a first subset of the MR data that is affected by EMI; suppressing EMI in the first subset of the MR data to obtain a second subset of the MR data by: applying a filter to the first subset of the MR data to suppress a contribution of MR spin echo signals in the first subset of the MR data, thereby obtaining signal-suppressed MR data; suppressing EMI in the signal-suppressed MR data to obtain EMI-suppressed MR data; and applying the inverse of the filter to the EMI-suppressed MR data to obtain the second subset of the MR data; generating an MR image using the second subset of the MR data; and outputting the generated MR image. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Various aspects and embodiments will be described with reference to the following figures. It should be understood that these figures are not drawn to scale. In the accompanying drawings, each identical or nearly identical component illustrated in each figure is represented by a similar number. For clarity, not every component may be labeled in each figure.

[0027] Figure 1 A magnetic resonance (MR) image of a patient's brain including narrowband electromagnetic interference (EMI) is shown in accordance with some embodiments.

[0028] Figure 2 A processing pipeline for generating MR images according to some embodiments is illustrated.

[0029] Figure 3 A processing pipeline for performing EMI suppression is illustrated in accordance with some embodiments.

[0030] Figure 4 Pseudo code for performing EMI suppression according to some embodiments is illustrated.

[0031] Figure 5 MR data acquired using multiple radio frequency (RF) coils and including narrowband EMI is illustrated in accordance with some embodiments.

[0032] Figure 6 Schematic diagram illustrating a pulse sequence including a portion for acquiring noise during a pulse repetition period according to some embodiments.

[0033] Figure 7A schematic diagram illustrating a noise acquisition block configured to capture EMI caused by internal EMI sources and external EMI sources in accordance with some embodiments.

[0034] Figure 8 An alternative schematic diagram illustrating a noise acquisition block for capturing EMI caused by internal and external EMI sources, including EMI caused by operating gradient coils and RF coils, in accordance with some embodiments.

[0035] Fig.9A and Fig. 9B Plots of MR echo signals in the time and frequency domains are illustrated according to some embodiments.

[0036] Fig. 10A and Fig. 10B Plots illustrating narrowband EMI signals in the time and frequency domains according to some embodiments.

[0037] Fig.11A MR images of a subject's brain are shown (these MR images include narrow-band EMI) according to some embodiments.

[0038] Fig. 11B shows the suppression of narrowband EMI according to some embodiments Fig.11A MR images.

[0039] Fig. 12A MR images of a phantom are shown (these MR images include narrow-band EMI) in accordance with some embodiments.

[0040] Fig. 12B shows the suppression of narrowband EMI according to some embodiments Fig. 12A MR images.

[0041] Fig.13A MR images of a phantom according to some embodiments are shown (these MR images include narrowband EMI affecting a set of adjacent intervals in the MR data).

[0042] Fig. 13B shows the suppression of narrowband EMI according to some embodiments Fig.13A MR images.

[0043] Fig.14A MR images of a subject's brain are shown (these MR images include narrow-band EMI caused by the magnetostrictive effect) according to some embodiments.

[0044] Fig. 14B FIG. 4 shows a schematic diagram of a circuit ... Fig.14A MR images.

[0045] Fig.15 A flow chart illustrating a process for suppressing EMI in MR images according to some embodiments.

[0046] Fig.16 Components of an MRI system according to some embodiments are illustrated.

[0047] Fig.17 Components of an MRI system for performing noise suppression are illustrated in accordance with some embodiments.

[0048] Fig.18 An MRI system according to some embodiments is illustrated.

[0049] Fig.19 A portable MRI system according to some embodiments is illustrated.

[0050] Fig. 20 An alternative MRI system according to some embodiments is illustrated.

[0051] Fig.21 is a diagram of an illustrative computer system in accordance with some embodiments. DETAILED DESCRIPTION

[0052] Conventional clinical magnetic resonance imaging (MRI) systems may typically be located in a room that is specially shielded to prevent electromagnetic interference (EMI) from interfering with its proper operation. In addition to protecting personnel and equipment from the magnetic field generated by the MRI system, the shielded room may also prevent artifacts such as RF interference generated by various external electronic devices (e.g., other medical devices) from affecting the operation of the MRI system and the quality of the resulting images. In order to operate outside of a specially shielded room, and more particularly to allow for generally portable MRI, the MRI system is capable of operating in a relatively uncontrolled electromagnetic environment (e.g., in an unshielded or partially shielded room), and is generally capable of taking into account and / or compensating for the presence of interference sources and / or noise that may be present in such an environment and that may introduce artifacts into the acquired MR images.

[0053] MRI systems may be affected by various interference sources when they are not shielded from EMI, and each of these interference sources may require different mitigation strategies. Some interference sources may be outside the MRI system. These sources include patient monitoring equipment (e.g., electrocardiogram (ECG) equipment), patient medical devices (e.g., intracranial electroencephalogram (EEG) devices), and other active electronic devices placed near the MRI system (e.g., computers, tablet computers, phones, mobile and / or smart phones, wearable electronic devices, etc.). These external interference sources may generate incoherent noise that may not be synchronized with the radio frequency (RF) transmission of the MRI system.

[0054] Some interference sources may be internal to the MRI system and may generate coherent noise that may be synchronized with the RF transmission of the MRI system. As a first example, where the MRI system includes a permanent magnet (e.g., as a primary B0 field magnet, as a shim magnet, etc.), the permanent magnet may be affected by the magnetostrictive effect during operation of the MRI system. Magnetostriction is the change in shape of a magnetic material during the magnetization process, and an applied magnetic field (e.g., a gradient magnetic field, an emitted RF signal) may cause the permanent magnet of the MRI system to change shape or size, thereby affecting the amplitude and / or uniformity of the B0 magnetic field, which may be detected as an artifact in the acquired MR image. Magnetostrictive noise may create low amplitude noise lines and may appear as a "zipper" line noise artifact perpendicular to the imaging readout direction. As another example of an internal source of EMI, the RF transmission electronics of the MRI system may also generate coherent line noise that is synchronized with the RF transmission of the MRI system.

[0055] In addition to being affected by EMI generated by various interference sources, MRI systems, when unshielded, may also be affected by different types of EMI, including broadband EMI and narrowband EMI. Broadband (sometimes referred to as "wideband") EMI can exist over a wide range (e.g., all or substantially all) of frequencies and can span the entire bandwidth (e.g., 64 kHz) of the acquired signal. The acquired MR data may include multiple spatial frequencies organized in multiple frequency intervals, and broadband EMI can exist in all or substantially all of the frequency intervals in the multiple frequency intervals. Thus, because broadband EMI affects most or all frequencies detected during MR imaging, MR images affected by broadband EMI generally include artifacts that affect the MR image as a whole.

[0056] In contrast, narrowband EMI can exist in a single frequency interval or within a threshold number of adjacent frequency intervals such that the spectral content of the EMI can exist in a narrow frequency range. For example, narrowband EMI can exist in a single frequency interval, within two adjacent frequency intervals, within five adjacent frequency intervals, within ten adjacent frequency intervals, or within 25 adjacent frequency intervals. As an example, if each frequency interval corresponds to a bandwidth of approximately 670 Hz, then narrowband EMI with a bandwidth of 1 kHz can exist within two adjacent frequency intervals. As described herein, narrowband EMI typically appears as "zipper" line noise artifacts perpendicular to the imaging readout direction. These zipper line noise artifacts can affect a single line or several adjacent lines of an MR image. It can be present in Figure 1 An example of narrowband EMI artifacts is seen in an MR image of a subject's brain, which includes an MR image of the subject's brain. The arrows point to horizontal bands of zipper line noise that can be caused by narrowband EMI.

[0057] In a non-limiting example, EMI can be characterized as narrowband in a domain other than spectral frequency. For example, if the signal suppressed data portion is organized as N c ×N t ×M matrix (where: N c is an integer representing the number of RF coils, N t is an integer representing the number of time points used for each data acquisition, and M represents a set of one or more dimensions of the number of measurements performed by each RF coil, then it is possible to t Fourier or other wavelet transforms are applied in M ​​dimensions or both. In the transformed basis, the noise source can also be narrowband. A non-limiting example of a narrowband noise source in the transform domain would be a noise source that is broadband in the spectral frequency domain but constant in time across acquisition times. Such a noise source would be narrowband in the occurrence frequency domain in M ​​measurements.

[0058] In some embodiments, the domain transform may be applied along the acquisition time domain dimension, and / or along the dimension including the number of acquisitions. The domain transform may be a Fourier transform or a wavelet transform. Thus, if a noise source occupies a narrow range of frequency spectrum, the noise source may be classified as narrowband. Alternatively, a noise source may occupy a broadband frequency spectrum, but may be classified as narrowband based on the frequency of occurrence. Alternatively, a noise source may be narrow in both the occurrence band and the spectral band.

[0059] In some MRI systems, conventional noise suppression techniques may be applied to the data set as a whole and may not adequately suppress narrowband EMI artifacts, which makes narrowband EMI artifacts potentially interfere with the clinical utility of MR images. New techniques are described herein that can reduce the effects of narrowband EMI artifacts on MR images. These techniques can allow an MRI system to operate in the presence of one or more sources of narrowband EMI. In addition, although the techniques described herein can allow an MRI system to operate in the presence of narrowband EMI, these techniques can also be used to mitigate the effects of narrowband interference on the operation of an MRI system in a shielded or semi-shielded environment, as aspects of the techniques described herein are not limited in this regard.

[0060] The techniques described herein can make it possible to suppress EMI in MR images by targeting the portions of MR data that are affected by EMI. These techniques may include first identifying which portions of MR data (e.g., "lines" or "frequency intervals") may be affected by EMI, and then suppressing EMI in these identified portions. In the identified portions, EMI can be suppressed by first applying filtering to the MR data. The filtering can be designed to suppress the contribution of MR spin echo signals to the MR data, so that EMI is the main contributing factor to the filtered data (i.e., the data generated as a result of applying filtering to the MR data). Then, EMI can be suppressed in the filtered data (e.g., by calculating the singular value decomposition of the filtered data and setting at least one singular value (e.g., the first singular value) to zero) to obtain EMI-suppressed data, and the inverse of the filtering can be applied to obtain a version of the EMI contribution of the identified portion of the MR data that is suppressed. The process can be repeated until no further MR data portions (e.g., no additional lines) can be identified as having EMI. Afterwards, these EMI-suppressed portions of the MR data can be used to generate and output MR images. In a non-limiting example, the filtering can be or can include convolution filtering. In other non-limiting example implementations, filtering may be or may include apodization filtering. In still other non-limiting examples, filtering may involve applying singular value decomposition (SVD) or high-order singular value decomposition (HOSVD). In still other non-limiting examples, filtering may be or may include component decomposition such as independent component analysis (ICA) or principal component analysis (PCA). In still other non-limiting examples, filtering may be or may include a combination of two or more filtering or other operations.

[0061] In some embodiments, the MR data may include multiple frequency intervals, each frequency interval including a portion of the MR data (e.g., a portion of the MR data acquired at a specific frequency). In some embodiments, identifying the portion of the MR data affected by EMI may include identifying the MR data in a single frequency interval or multiple frequency intervals. The multiple frequency intervals may include a set of adjacent frequency intervals or multiple sets of adjacent frequency intervals, wherein the sets are not adjacent to each other. Adjacent frequency intervals may be frequency intervals where the corresponding frequency ranges are no more than a threshold Hz apart (e.g., 0 Hz apart). The set of adjacent frequency intervals may include no more than a threshold number of adjacent frequency intervals (e.g., 2, 5, 10, 25, 50, etc.). In some embodiments, the threshold number of frequency intervals may depend on the sampling frequency of the MRI device (e.g., when there may be a larger sampling frequency, the threshold number may be set higher). In some embodiments, the length of the filter applied to the MR data may be set as a function of the number of adjacent frequency intervals where EMI can be suppressed.

[0062] In some embodiments, suppressing EMI in identified portions of MR data that may be affected by EMI may include, for each identified portion of the MR data: applying filtering to a particular data portion to obtain a corresponding signal-suppressed MR data portion; suppressing EMI in the corresponding signal-suppressed MR data portion to obtain a corresponding EMI-suppressed MR data portion; and applying the inverse of the filtering to the EMI-suppressed MR data portion.

[0063] In some embodiments, suppressing EMI in the signal suppressed MR data can be achieved using a component decomposition process, which can include singular value decomposition (SVD), independent component analysis (ICA) or principal component analysis (PCA). In one or more non-limiting example implementations, the SVD of the filtered data can be determined, and the SVD can be modified to suppress the contribution of EMI. In some embodiments, the SVD can be modified by setting at least one singular value of the SVD to zero (e.g., by setting the first singular value of the SVD to zero, by setting the first two, first three or threshold number of singular values ​​of the SVD to zero). In other embodiments, the SVD can be modified by multiplying one or more singular values ​​of the SVD by a number between 0 and 1 (e.g., by multiplying the first singular value of the SVD by a number between 0 and 1, by multiplying the first two, first three or threshold number of singular values ​​of the SVD by a number between 0 and 1). Then, the modified SVD can be used to determine the EMI suppressed data. However, in other embodiments, one or more other techniques can be used instead of the SVD method to suppress noise in the filtered data. In some embodiments, principal component analysis (PCA) can be used to suppress noise in the filtered data. In some embodiments, independent component analysis (ICA) can be used to suppress noise in the filtered data.

[0064] In some embodiments, the MRI system may include multiple (e.g., 2, 4, 8, 16, 32, etc.) RF coils, and each of the multiple data portions includes measurements made by each of the multiple RF coils for a corresponding frequency interval in the multiple frequency intervals. In some embodiments, the data in the corresponding signal suppressed data portion may be organized as N c ×M matrix, where N c is an integer representing the number of RF coils and M is an integer representing the number of measurements performed by each RF coil, and wherein determining the SVD of the corresponding signal suppressed MR data portion comprises determining N c The singular value decomposition of the Λ × M matrix. The singular value decomposition may be computed in any suitable manner, including by using any suitable software library for performing numerical linear algebra algorithms.

[0065] In some embodiments, before identifying the first subset of MR data, the MR data may be generated by operating the MRI system according to a spin echo pulse sequence. The spin echo MR signal may have a characteristic linear phase that produces an echo at the center of the acquisition, and as a result, the spin echo MR signal may alternate the phase between even and odd points. In contrast, EMI noise may not always match this signal pattern throughout the duration of the entire image acquisition. For this reason, filtering may be used to suppress the contribution of the spin echo MR signal, thereby making EMI the main contributing factor to the signal from applying convolution filtering to the MR data. In a non-limiting example, the filtering may be a convolution filter.

[0066] The techniques described herein can be applied to any of a plurality of types of spin echo pulse sequences and / or gradient echo pulse sequences. For example, the techniques described herein can be applied to T1 pulse sequences, T2 pulse sequences, fluid attenuated inversion recovery (FLAIR) pulse sequences, diffusion weighted imaging (DWI) pulse sequences, and / or other spin echo pulse sequences and / or gradient echo pulse sequences currently in use or to be developed.

[0067] In some embodiments, after generating the MR data and before identifying the first subset, a portion of the EMI may be detected by an auxiliary coil of the MRI system and suppressed in the MR data.

[0068] In some embodiments, the EMI may be narrowband EMI. In some embodiments, the MR data may include sensor domain data having multiple frequency intervals, and the EMI may be present in a frequency interval in the multiple frequency intervals. Alternatively, the EMI may be present in a set of adjacent frequency intervals having a threshold number (e.g., 2, 5, 10, 25, 50, etc.) of the multiple frequency intervals. Alternatively, the EMI may be present in each set of adjacent frequency intervals in a plurality of sets of adjacent frequency intervals, wherein the sets are not adjacent to each other.

[0069] In some embodiments, EMI may be present in an nth frequency interval among a plurality of frequency intervals, and wherein applying filtering to a first subset of the MR data comprises calculating a weighted linear combination of data in a plurality of frequency intervals, including the nth frequency interval, using weights determined by coefficients of a convolution filter.

[0070] In some embodiments, the MR data may include multiple frequency intervals, EMI may be present in multiple adjacent frequency intervals, and applying the filter to the first subset of the MR data may include applying a filter having a certain length. The length of the filter may be at least equal to the number of adjacent frequency intervals in which EMI may be present. In some embodiments, if the number of frequency intervals in the band is an even number, the size of the filter may be selected to be equal to the number of frequency intervals in the band. If the number of frequency intervals in the band is an odd number, the size of the filter may be selected to be equal to a number that is one greater than the number of frequency intervals in the band.

[0071] In some embodiments, identifying the first subset of the MR data may include identifying data in a single frequency bin or a set of adjacent frequency bins of the MR data that may be affected by EMI.

[0072] In some embodiments, identifying the first subset of MR data can be performed by analyzing a portion of the MR data acquired by detecting the edge of k-space. For example, identifying the first subset of MR data can be performed by analyzing one or more echo signals acquired from the edge of k-space. In some embodiments, identifying the first subset of MR data can be performed by analyzing a portion of the MR data acquired during two echo signals at the end of a repetition period of a pulse sequence used to acquire MR data. In some embodiments, identifying the first subset of MR data includes identifying any frequency period in which a portion of the data being analyzed has an amplitude greater than a threshold.

[0073] In some embodiments, generating the MR image may include: modifying the MR data by replacing the first subset of the MR data with the second subset of the MR data to obtain modified MR data; and generating the MR image using the modified MR data.

[0074] The techniques described herein can be used to suppress (e.g., reduce and / or eliminate) artifacts from MR data obtained by any suitable type of MRI system. In some embodiments, low-field MRI systems may be more susceptible to EMI. In some systems, EMI may exist regardless of the field strength of the MRI system. The techniques described herein can be used to reduce and / or eliminate artifacts from MR data obtained by any suitable type of MRI system. The techniques described herein may not be limited to use with low-field MRI systems or any particular type of MRI system, and may be used with high-field and / or any other suitable type of MRI system.

[0075] "High field" generally refers to MRI systems currently used in clinical settings, and more particularly refers to MRI systems that operate with a main magnetic field (i.e., B0 field) at or above 1.5 T, although clinical systems that operate between 0.5 T and 1.5 T are also often characterized as "high field". Field strengths between 0.2 T and 0.5 T have been characterized as "mid-field", and as field strengths in the high-field state have continued to increase, field strengths in the range between 0.5 T and 1 T have also been characterized as mid-field. In contrast, "low field" generally refers to MRI systems that operate with B0 field strengths between 0.02 T and 0.2 T, although systems with B0 fields between 0.2 T and 0.3 T are sometimes also characterized as low field due to the increased field strength at the high end of the high-field state.

[0076] Techniques for processing medical data to generate MR images of a subject conventionally involve applying different computational tools to perform different tasks that may be part of a data processing pipeline. Figure 2 As shown, the MRI system 202 can be used to acquire MR data by imaging a subject (eg, a human patient, an animal patient, an inanimate object, etc.). Figure 2 As shown, the MRI system 202 can be a portable or non-portable MRI system. The MRI system 202 can be any type of MRI system, as aspects of the technology described herein are generally not limited to the physical size or portability of an MRI system.

[0077] In some embodiments, the MR data 204 may be acquired in multiple instances. Figure 2 As shown, multiple acquisitions of data may be performed to enable averaging of the MR data 204 (e.g., to improve the signal-to-noise ratio and / or improve the quality of the resulting MR image). Additionally, in some embodiments, the MRI system 202 may include multiple sensors that may be configured to acquire portions of the medical data. The MRI system 202 may include multiple RF coils located at different positions relative to the subject, and the multiple RF coils may be used to acquire different portions (“data channels”) of the MR data. In some embodiments, the multiple RF coils may include 2 or 4 or 6 or 16 or 32 or more or any other suitable number of RF coils.

[0078] exist Figure 5 An example of MR data acquired by an MRI system having multiple RF coils and subjected to narrowband EMI is shown in FIG. Figure 5The MR data shown includes data obtained from 8 RF coils and is shown in the "sensor domain", where the real components of the acquired complex data are shown in the top row and the imaginary components of the acquired complex data are shown in the bottom row. The data in the sensor domain may include raw sensor measurements obtained by the MRI system. The sensor domain data may include measurements acquired line by line for a set of coordinates specified by a sampling mode. The measurement lines may be referred to as "readout" lines. Each measurement may be a spatial frequency. Thus, the sensor domain data may include multiple readout lines. For example, if n readout lines are measured and each readout line includes M samples, the sensor domain data may be organized into an M×n matrix. Knowing the k-space coordinates associated with each of the M×n samples, the sensor domain data may be reorganized into corresponding k-space data, which may then be considered as spatial frequency domain data. Image domain data may be obtained by reconstructing the spatial frequency domain data.

[0079] After acquiring the MR data 204, various computational tools may be applied to the MR data 204 as part of a processing pipeline. Figure 2 As shown, the processing pipeline may involve performing various pre-processing tasks 206, which may include basebanding 206a, filtering 206b, and / or broadband noise suppression 206c. It should be understood that the pre-processing tasks 206 may include performing various pre-processing tasks 206a, filtering 206b, and / or broadband noise suppression 206c. Figure 2 Other processing processes are not shown in the examples, as aspects of the technology described herein are not limited in this respect.

[0080] In some embodiments, basebanding 206a may include transforming the raw voltage signal from (one or more than one) RF coil into one or more baseband signals. The baseband signal may be a complex signal that may describe the complex envelope of the received voltage signal and may represent the integral of the MR spin echo signal received from the imaged object. Basebanding 206a may be performed, for example, by multiplying the input data received from an analog-to-digital converter (ADC) of the MRI system with a baseband frequency. In some embodiments, basebanding 206a may also include interval elimination, thereby reducing the sampling of the signal received from the ADC. As a non-limiting example, in an embodiment, the reduction in sampling may reduce the sampling from 50 MHz sampling of a 2.7 MHz signal to 200 kHz sampling of a signal centered at 0 Hz.

[0081] In some embodiments, filtering 206b may include one or more filtering steps to remove or suppress spurious signals that fall outside the baseband signal. In some embodiments, filtering 206b may include one or more low-pass filtering steps to remove or suppress signals that fall outside the baseband signal. Filtering 206b may also include "trimming" the baseband signal to a desired acquisition bandwidth (e.g., to 64kHz).

[0082] In some embodiments, broadband EMI suppression 206c may include any suitable noise suppression technique applied to the entirety of the MR data and arranged to suppress noise affecting the entire MR data. In some embodiments, broadband EMI suppression 206c may be based on noise measurements obtained from the environment of the MRI system. Noise measurements may be made by one or more auxiliary sensors as described herein and may be used to suppress noise present in MR signals detected by the MRI system during operation.

[0083] In some embodiments, differences between (one or more) auxiliary sensors and the RF coil configured to receive MR signals from the subject (e.g., different physical characteristics, different positions relative to the field of view, etc.) can result in differences in characteristics of noise signals received by the (one or more) auxiliary sensors and the RF coil. As a result, subtracting the noise signal measured by the (one or more) auxiliary sensors may not adequately suppress the noise detected by the RF coil. Therefore, in some embodiments, a transfer function can be estimated and the transfer function can be used to transform the noise signal received via the one or more auxiliary sensors into an estimate of the noise received by the one or more RF coils. In some embodiments, broadband EMI suppression can include: obtaining samples of noise using one or more auxiliary sensors; obtaining samples of MR data using the primary RF coil; obtaining a transfer function; transforming the noise samples using the transfer function; and subtracting the transformed noise samples from the obtained MR data to suppress and / or eliminate the noise.

[0084] After preprocessing 206, EMI artifacts may still be present in the MR data. More specifically, narrowband EMI artifacts may still be present in the MR data. Thus, after preprocessing 206 the MR data, the processing pipeline may include narrowband EMI suppression 208. The process of performing narrowband EMI suppression 208 is further described herein. According to some embodiments, Figure 3 An embodiment of a processing pipeline for performing narrowband EMI suppression is illustrated, and Figure 4 An embodiment of a pseudo code for performing EMI suppression is illustrated.

[0085] In some embodiments, the processing pipeline 300 may begin with a first act 302 of identifying a portion of the MR data that includes EMI (represented by the EMI_index line 402 of the pseudo-code 400). As indicated in line 404 of the pseudo-code 400, the processing pipeline 300 may be iteratively implemented until no remaining EMI is identified in the MR data.

[0086] In some embodiments, the portion of the MR data affected by EMI can be identified based on which frequency intervals of the MR data are likely to be affected by EMI. Let y be the complete set of MR data and n be the readout index. The MR data at index n is y n =s n +EMI n , where y n is the two-dimensional signal cross-section across the nth readout index or frequency bin, s n is the expected MR data, and EMI n is EMI interference. e The MR data collected at the end of the spin echo train can be used to identify the frequency interval including the MR data affected by EMI. In some embodiments, a portion of the MR data acquired by a subset of the echoes of the spin echo train can be used to identify which parts of the MR data may be affected by EMI. The echo subset used to identify which parts of the MR data may be affected by EMI can be an echo that detects the edge of the k-space. Compared with the contribution to the MR data from (one or more than one) sources of EMI, the MR data acquired from the outer edge of the k-space may include a small or disappearing contribution to the MR data from the spin echo signal. In some pulse sequences, the echoes at the end of the spin echo train (e.g., the last echo, the last two echoes, some of the last echoes) can be used to identify which parts of the MR data are affected by EMI. Together, the last echoes from all repetition cycles of the pulse sequence used to acquire MR data can form a k-space edge data set for detecting frequency intervals affected by EMI.

[0087] In some embodiments, the data set y e The absolute value of can be used to detect the frequency range affected by EMI. If the amplitude of is greater than the threshold, the nth frequency interval can be identified as being affected by EMI, where can be MR data collected from the end of the spin echo train in the nth frequency interval. In some embodiments, if the data The nth frequency interval can be marked as affected by EMI if the amplitude of satisfies the following:

[0088]

[0089] in, is the dataset y e The signal at the nth frequency, and They are y e is the mean and standard deviation of , and θ is a predefined threshold.

[0090] In some embodiments, one or more methods for measuring external and / or internal EMI can be used to identify portions of the MR data that are affected by EMI. In some embodiments, noise acquisition can be performed in one or more pulse repetition cycles of a plurality of pulse repetition cycles where little or no MR signals are expected to be detected. In some embodiments, EMI can be acquired before and / or after an MR acquisition block in at least some (e.g., at least one, at least half, all) of the pulse repetition cycles of a spin echo pulse sequence. Figure 6 In the embodiment, EMI may be acquired during a noise acquisition block 602 a before the MR signal acquisition block 604 and during a noise acquisition block 602 b after the MR signal acquisition block 604 .

[0091] To this end, during the noise acquisition blocks 602a and 602b, in the absence of any encoding gradients (which may be achieved by turning off the gradient coils) or RF excitation pulses, the RF receiver of the MRI system may be turned on so that the primary RF coil and / or (one or more) auxiliary RF sensors may acquire noise data that includes EMI (to any extent present) but may not include any spin echo MR signals from the subject. In turn, the collected data may be used to determine the frequencies at which EMI may affect the MR data collected during block 604. In this way, the collected data may be used to identify portions (e.g., frequency bins) of the MR data where the amplitude and / or power of EMI exceeds a threshold. In some embodiments, identifying portions of the MR data affected by EMI may be performed for each repetition period of the pulse sequence (e.g., using the noise acquisition blocks 602a, 602b within each respective repetition period) to account for variations in EMI over the acquisition period (e.g., due to drift of the center frequency of the MRI system, due to physical movement of the device emitting EMI relative to the MRI system). In some embodiments, identifying the EMI affected portion of the MR data may be performed for the first and last repetition periods of the pulse sequence, for a subset of the repetition periods of the pulse sequence, and / or for at least half of the repetition periods of the pulse sequence.

[0092] As described herein, the noise acquisition blocks 602a and 602b can be configured to detect noise generated by external sources of EMI. However, in some embodiments, it may be desirable to also detect EMI generated by sources of EMI internal to the MRI system. In some embodiments, electronic components of the MRI system (e.g., gradient and / or RF coils and / or electronics) may generate or otherwise induce EMI during operation of the MRI system. The noise acquisition block can be configured such that the gradient coils and / or RF transmit coils operate during the noise acquisition block to detect EMI generated by internal sources. Figure 7 and Figure 8 An example of a noise acquisition block for detecting EMI generated by both internal and external sources of EMI is shown in FIG.

[0093] In some embodiments, the noise acquisition block may include an alternating series of RF pulses 702, 802 and gradient pulses 704, 804, wherein acquisition 706, 806 is performed while the MRI system is generating the gradient pulses 704, 804. Acquisition 706, 806 may be performed by turning on the RF receiver of the MRI system and turning off the RF transmitter. The RF pulses 702, 802 may be refocusing pulses configured to flip the direction of the magnetization vector of the spins in the field of view (e.g., flip 180°). The RF pulses 702, 802 may preferably not be 90° pulses, which may tilt the net magnetization of the spins in the field of view into the transverse plane and emit spin echo MR signals as the spins relax back to the longitudinal plane.

[0094] In some embodiments, the gradient pulses may be configured to suppress MR spin echo signals from the subject and may not include phase encoding gradient pulses. In some embodiments, correction gradients ("broken" gradients) may be included in the noise acquisition block to dephase and / or otherwise suppress MR spin echo signals generated by spins within the field of view of the MRI system. In this way, the RF receiver of the MRI system can acquire noise data including EMI caused by external EMI sources and internal EMI sources.

[0095] In some embodiments, the noise acquisition block can be configured based on the type and / or parameters of the pulse sequence used to acquire the MR signal. The noise acquisition block can be configured to simulate the parameters of the pulse sequence used to acquire the MR signal so that the acquired EMI caused by the internal EMI source can be similar to the internal EMI generated during the pulse sequence used to acquire the MR signal. In some embodiments, the noise acquisition block can include an RF excitation pulse 808. When the pulse sequence used to acquire the MR signal is a fast spin echo (FSE) pulse sequence, the RF excitation pulse 808 can be included.

[0096] In some embodiments, one or more advanced peak extraction algorithms may be used to identify portions of the MR data affected by EMI. In some embodiments, Bayesian peak extraction, non-negative matrix factorization, and / or non-decimated discrete wavelet transform (UDWT) techniques may be used to identify portions of the MR data affected by EMI.

[0097] In some embodiments, a portion of the MR data acquisition (e.g., MR data acquired in a subset (one or more) of a repeating cycle) may be used to identify portions of the MR data that are affected by EMI. In some embodiments, it may be desirable to identify temporal variations in the effects of EMI on the MR data, and then apply the EMI suppression techniques described herein to a subset of the MR data based on the EMI identified in the subset (one or more) of the MR data acquisition. In some embodiments, an external device that emits EMI may have been present in the vicinity of the MRI system during the first half of the MR data acquisition cycle, and may have been relocated thereafter. It may be desirable to identify a subset that includes the first half of the MR data acquisition (which may have been affected by EMI caused by the external device), and which frequency intervals (one or more) within the first half of the MR data may include EMI signals. It may also be desirable to apply EMI suppression techniques to the first half of the MR data acquisition. In some embodiments, the subset (one or more) of MR data may not only be the first half of the MR data acquisition cycle, but may be a smaller or larger subset (one or more), more than one, and / or a subset (one or more) that is not located at the beginning or end of the MR data acquisition cycle.

[0098] In some embodiments, a sliding window may be used to identify portions of the MR data that are affected by EMI. In some embodiments, a first subset of the MR data acquisition may be identified as being affected by EMI, and noise suppression may be applied to the first subset of the MR data as described herein. Thereafter, a second subset of the MR data (e.g., an adjacent subset, a partially overlapping subset) may be identified as being affected by EMI, and noise suppression may be applied to the second subset of the MR data. Identification and noise suppression may be performed iteratively by continuing to "slide" the window across the MR data.

[0099] In some embodiments, after identifying frequency bins containing MR data affected by EMI, for each identified frequency bin as indicated by for loop line 406 of pseudo code 400, a Figure 3 As illustrated in the second action 304 of the pseudo code 400 and the fifth line 406a of the pseudo code 400, filtering may be applied to the MR data. In this non-limiting example, the convolution filtering may be arranged to suppress the MR signal contribution s n , and can be designed based on the characteristics of the spin echo MR signal.

[0100] Spin echo MR signal s n may have a characteristic linear phase that produces an echo at the center of the acquisition. The MR signal can accordingly be described by the Fourier-time shift relationship:

[0101]

[0102] The Fourier transform can be obtained by multiplying the frequency X(ω) by the linear phase For time With a spin echo MR signal centered at the middle of the acquisition at (where N may be the total number of sampling points within the readout and δt may be the duration between sampling points), the phase of the spin echo MR signal alternates between even and odd points:

[0103]

[0104] Fig.9A and Fig. 9B Non-limiting examples of MR echo signals plotted in the time domain and the frequency domain are illustrated respectively. Fig.9A In , the real part 902 of an exemplary spin echo MR signal and the imaginary part 904 of the same exemplary spin echo MR signal are superimposed in the time domain. Fig. 9B , the real part 906, the imaginary part 908, and the amplitude 910 of the spin echo MR signal are superimposed in the frequency domain. As described herein, the real part 906 and the imaginary part 908 of the spin echo MR signal exhibit alternating phases.

[0105] In some embodiments, the signal contribution due to EMI is unlikely to match the alternating phase signal pattern exhibited by the spin echo MR signal. Fig. 10A and Fig. 10B An example of a curve diagram of Fig. 10A and Fig. 10B EMI signals plotted in the time domain and the frequency domain according to some embodiments are respectively illustrated. Fig. 10A In FIG. 1 , the real part 1002 and the imaginary part 1004 of the exemplary EMI signal are superimposed in the time domain. Fig. 10B , the real part 1006, the imaginary part 1008, and the amplitude 1010 of the EMI signal are superimposed in the frequency domain. The real part 1006 and the imaginary part 1008 do not exhibit alternating phases as would be expected from a spin echo MR signal.

[0106] In some embodiments, a convolution filter may be designed based on the difference in phase behavior between the spin echo MR signal and the EMI signal. In some embodiments, if EMI can be identified in a single frequency bin n, the following convolution filter may be applied:

[0107] [-1,1,4,1,-1].

[0108] The convolution filter may apply a wide apodization window that suppresses any signal roughly centered in the acquisition window. This will suppress most of the spin echo MR signal, and EMI noise may enhance the signal. n The enhanced signal a n can be rewritten as the following expression:

[0109]

[0110] In some embodiments, since the position of the spin echo MR signal (e.g., due to eddy currents and / or stray magnetic fields) may drift during MR data acquisition, the assumption that the spin echo MR signal is centered in the middle of the acquisition window may not be accurate. In some embodiments, the convolution filter may be adapted to compensate for spin echo MR signals that may not be centered in the middle of the acquisition window. For a spin echo MR signal that has drifted by Δt, its Fourier transform may obtain a linear phase across the frequency interval given by:

[0111]

[0112] Where TE is the echo duration. The linear phase can be compensated by phase modulating the frequency spectrum for all n pairs:

[0113]

[0114] Then, convolution filtering can be applied to the phase compensated signal z n In some embodiments, the enhanced signal a n Then it can be written as:

[0115]

[0116] In some embodiments, EMI may be present in consecutive adjacent frequency intervals in the MR data. In such embodiments, the width of the convolution filter may be adapted based on the width of the noise band. The width of the noise band may be the number of consecutive frequency intervals with MR data affected by EMI. In some embodiments, if interference is detected at indices [1, 2, 3, 16, 17, 48, 61, 62, 63, 64], these indices may be grouped into four bands as follows:

[0117] [[1,2,3],[16,17],

[48] ,[61,62,63,64]].

[0118] For each grouped band having indices of MR data affected by EMI, the size k of the convolution filter may be selected to be at least equal to the number of indices in the band. If the number of indices in the band is an even number, the size k of the convolution filter may be selected to be equal to the number of indices in the band. If the number of indices in the band is an odd number, the size k of the convolution filter may be selected to be equal to a number that is one greater than the number of indices in the band. For example, for the first band [1,2,3], the size of the convolution filter would be selected to be k=4, and for the second band [16,17], the size of the convolution filter would be selected to be k=2. The filtered signal a is then n can be expressed as:

[0119]

[0120] In some embodiments, after applying convolution filtering to suppress the spin echo MR signal, as determined by Figure 3 As illustrated in the third action 306 of the pseudocode 400 and line 406b of the pseudocode 400, it is possible to determine a n Singular value decomposition (SVD) of the filtered signal a n can be written as:

[0121] a n =USV T

[0122] in: and

[0123] In some embodiments, the convolution filtering has suppressed a n The EMI signal can be left to dominate the spin echo MR signal in a n At least the first singular value of the SVD of . Then the EMI signal can be suppressed, and the modified SVD (USV T )'. Figure 3 As illustrated by the fourth action 308 of the pseudocode 400 and the line 406c of the pseudocode 400, the modified SVD can be obtained by setting at least the first singular value of the SVD equal to zero. In some embodiments, the first singular value of the SVD can be set equal to zero to suppress the EMI signal. In other embodiments, the first two, first several, or some singular values ​​of the SVD can be set equal to zero to suppress the EMI signal.

[0124] Alternatively, the modified SVD may be obtained by multiplying ("scaling down") at least the first singular value of the SVD by a number between 0 and 1. In some embodiments, the first singular value may be multiplied by a number between 0 and 1 to reduce the contribution of EMI to the MR data. In other embodiments, the first two, first several, or some singular values ​​of the SVD may be multiplied by numbers between 0 and 1 to modify the SVD. Modifying the SVD by multiplying at least the first singular value of the SVD by a number between 0 and 1 may suppress a portion of the EMI in the MR data such that a certain small portion of the EMI remains in the MR data. Iteratively performing the actions of identifying portions of the MR data affected by the remaining EMI and suppressing the EMI may sufficiently suppress the EMI such that the EMI approaches a negligible contribution to the MR data.

[0125] In some embodiments, after obtaining the modified SVD by suppressing the EMI signal, as determined by Figure 3 As illustrated in the fifth action 310 of the pseudocode 400 and line 406d of the pseudocode 400, the modified SVD may be used to obtain the modified signal a n ' (where the contribution of EMI is suppressed). For example, a can be obtained according to the following n ':

[0126] a ′ n =(USV T ) ′ .

[0127] In some embodiments, the modified signal a can then be used n 'To obtain MR data with suppressed EMI contribution. Figure 3 As illustrated by the sixth action 312 of the pseudocode 400 and line 406e of the pseudocode 400, the inverse of the convolution filter may be applied to the modified signal a n ' to produce the desired EMI-suppressed MR data:

[0128]

[0129] return Figure 2 In some embodiments, after narrowband EMI suppression 208, image reconstruction 210 may be used to generate an MR image. In some embodiments, the EMI suppressed MR data may then be used to generate an MR image. In some embodiments, the original MR data affected by EMI may be n MR data can be suppressed by EMI n 'replacement. Then the EMI suppressed MR data can be used n 'The modified MR data is used to generate an MR image.

[0130] In some embodiments, an MR image may be generated using an image reconstruction technique to reconstruct the image from the spatial frequency domain to the image domain. Image reconstruction 210 may be performed using any suitable image reconstruction technique, including but not limited to linear reconstruction techniques and nonlinear reconstruction techniques. Non-limiting examples of linear reconstruction techniques include gridding, principal component analysis (PCA), generalized autocalibrated partially parallel acquisition (GRAPPA), sensitivity encoding (SENSE), and conjugate gradient sensitivity encoding (CG-SENSE). Various aspects related to PCA, GRAPPA, SENSE, and CG-SENSE are described in the literature.

[0131] In some embodiments, after the MR image is generated using image reconstruction 210, additional post-processing 212 may be performed to further refine the MR image. In some embodiments, post-processing 212 may further include denoising 212a, image registration 212b, distortion correction 212c, and / or coil strength correction 212d.

[0132] In some embodiments, post-processing 212 may further include denoising 212a. De-noising 212a may be arranged to suppress residual EMI artifacts in the MR image that are not adequately suppressed by broadband noise suppression 206c or narrowband EMI suppression 208. In some embodiments, denoising 212a may include suppressing residual noise in the generated MR image using any suitable noise suppression technique, including deep learning techniques.

[0133] In some embodiments, post-processing 212 may include image registration 212b. Image registration 212b may include techniques for aligning multiple MR images acquired during operation of the MRI system. Accurately aligning multiple MR images before combining the MR images may improve MR image contrast and quality. In some embodiments, image registration 212b may include using any suitable image registration technique (including deep learning techniques) to align the MR images acquired by the MRI system.

[0134] In some embodiments, post-processing 212 may include distortion correction 212c. Distortion correction 212c may correct distortion between multiple MR images acquired during operation of the MRI system. Correcting distortion may improve MR image contrast and quality and provide clinically more accurate MR images. In some embodiments, distortion correction 212c may include any suitable distortion correction technique (including deep learning techniques).

[0135] In some embodiments, post-processing 212 may include coil strength correction 212d. Coil strength correction 212d may account for differences in contrast caused by different RF coils outputting different signal strengths due to different physical properties (e.g., being located at different positions relative to the field of view of the MRI system). In some embodiments, coil strength correction 212d may include any suitable coil strength correction technique (including deep learning techniques).

[0136] In some embodiments, post-processing 212 may include Figure 2 Other processing processes not shown in the figure are not included, because research on the present disclosure may reveal a wide range of similar, equivalent or alternative methods covered by the spirit of the present disclosure.

[0137] exist FIG. 11A to FIG. 14B Additional embodiments of narrowband EMI suppression are shown in . Fig.11A MR images of a subject's brain are shown, the MR images including narrow-band EMI present in horizontal bands extending across the images. Fig. 11B Figure 2 shows the suppression of narrowband EMI according to some embodiments described herein. Fig.11A MR images.

[0138] Fig. 12A and Fig.13A MR images of an MR phantom are shown that include narrow-band EMI present in vertical bands extending across the image. Fig. 12B and Fig. 13B Figures 1 and 2 respectively show the suppression of narrowband EMI according to some embodiments of the technology described herein. Fig. 12A and Fig.13A MR images.

[0139] Fig.14A MR images of a subject's brain are shown, which include narrowband EMI caused by the magnetostrictive effect. As described herein, magnetostriction can cause coherent line noise that can be synchronized with the timing and phase of the RF pulses transmitted by the MRI system. Since this noise is coherent with the RF pulse transmission and is not as combined with the Figures 2 to 4 The spin echo MR signal described above can therefore be transformed to amplify the EMI signal and suppress the spin echo MR signal. The transformation can transform the data into a frame of the RF transmit phase. In some embodiments, for a multi-spin echo sequence, the frame of the RF transmit phase can be different from the frame of the RF receive phase. The transformation can be described by:

[0140]

[0141] Where tx and adc are the phase of the transmitted RF pulse and the phase of the RF receiver, respectively, and S aq and Stx are the observed data and the transformed data respectively.

[0142] Due to the magnetostrictive noise, the echo train across the repetition period is in S tx In the domain, magnetostrictive EMI signals may be coherent and accumulate at zero frequency bins along the repetition period FFT. The selection criteria for this EMI can be set much higher than the selection criteria for incoherent EMI because coherent EMI can be consistent throughout the acquisition. Thus, coherent EMI can be identified based on the following thresholds:

[0143]

[0144] in, is the index n tx S tx data, and and are the corresponding mean and standard deviation, respectively, and θ2 is a predefined threshold. Once the frequency bins including MR data affected by coherent EMI are identified, the coherent EMI can be suppressed as described herein. Fig. 14B FIG. 4 shows the effect of suppressing narrowband EMI due to magnetostrictive effect according to some embodiments. Fig.14A MR images.

[0145] Fig.15 A flowchart illustrating a process 1500 for suppressing EMI in MR images according to some embodiments of the techniques described herein. The process 1500 can be performed using any suitable computing device. For example, in some embodiments, the process 1500 can be performed by a computing device co-located with an MRI system that acquired MR data by imaging a subject (e.g., in the same room). As another example, in some embodiments, the process 1500 can be performed by one or more processors located on the MRI system that acquired the MR data. Alternatively, in some embodiments, the process 1500 can be performed by one or more processors located remotely from the MRI system that acquired the MR data (e.g., as part of a cloud computing environment).

[0146] In some embodiments, the process 1500 may optionally include: generating MR data before identifying the first subset of the MR data affected by EMI. Generating the MR data may include: operating the MRI system according to a spin echo pulse sequence. For example, the MRI system may operate according to a spin echo pulse sequence selected from the group consisting of a T1 pulse sequence, a T2 pulse sequence, a fluid attenuated inversion recovery (FLAIR) pulse sequence, and a diffusion weighted imaging (DWI) pulse sequence.

[0147] In some embodiments, the process 1500 may optionally include, after generating the MR data and before identifying the first subset of the MR data, suppressing EMI in the MR data detected by auxiliary sensors and / or coils of the MRI system. As described herein, the auxiliary sensor(s) may be any suitable auxiliary sensor(s). The auxiliary sensor(s) may be arranged to detect EMI generated by an EMI source located near or within the field of view of the MRI system.

[0148] In some embodiments, suppressing EMI in the MR data may include estimating a transfer function of (one or more) auxiliary sensors to more accurately estimate the noise detected by the RF coil. As a result, subtracting the noise signal measured by the (one or more) auxiliary sensors may not adequately suppress the noise detected by the RF coil. In some embodiments, the transfer function of (one or more) auxiliary sensors may be estimated, and the transfer function may be used to transform the noise signal received via the (one or more) auxiliary sensors into an estimate of the noise received by the RF coil. In some embodiments, broadband EMI suppression may include: obtaining samples of noise by using one or more auxiliary sensors; obtaining samples of MR data using the primary RF coil; obtaining a transfer function; transforming the noise samples using the transfer function; and subtracting the transformed noise samples from the obtained MR data to suppress and / or eliminate the noise.

[0149] In some embodiments, the process 1500 may begin with an action 1502 for identifying a first subset of MR data that may be affected by EMI. Identifying the first subset of MR data may include identifying data in a single frequency interval or a set of adjacent frequency intervals of the MR data that may be affected by EMI. In some embodiments, identifying the first subset of MR data may include determining whether the data in a frequency interval or a set of adjacent frequency intervals may have an amplitude greater than a threshold. In some embodiments, the threshold may be determined based on a mean and / or standard deviation of the amplitude of the MR data.

[0150] In some embodiments, one or more methods for measuring external EMI and / or internal EMI can be used to identify portions of the MR data affected by EMI. In some embodiments, noise data acquisition can be performed using a noise acquisition block placed before and / or after the MR signal acquisition block of the pulse sequence. The noise acquisition block can be configured to acquire noise data including EMI caused by external and / or internal sources of EMI.

[0151] In some embodiments, one or more advanced peak extraction algorithms may be used to identify portions of the MR data affected by EMI. In some embodiments, Bayesian peak extraction, non-negative matrix factorization, and / or non-decimated discrete wavelet transform (UDWT) techniques may be used to identify portions of the MR data affected by EMI.

[0152] In some embodiments, only a portion of the MR data may be used to identify the portion of the MR data affected by EMI.In some embodiments, one or more subsets of repetitive cycles of MR data acquisition may be used to identify the portion of the MR data affected by EMI.

[0153] In some embodiments, identifying the first subset of MR data can be performed by analyzing a portion of the MR data acquired during an echo signal at the end of a repetition period of a pulse sequence used to acquire the MR data. The echo at the end of the spin echo train can acquire MR data from the outer edge of k-space, where the contribution to the MR data from the spin echo signal generated by the subject may be small or disappearing. In some embodiments, identifying the first subset of MR data can be performed by analyzing the last two echo signals at the end of a repetition period of a pulse sequence used to acquire the MR data.

[0154] In some embodiments, where the EMI includes coherent EMI (e.g., due to magnetostriction, RF transmission electronics, etc.), determining the first subset of MR data may include transforming the MR data into a reference frame of transmitted pulses. Thereafter, determining the first subset of MR data may include identifying whether the MR data in a frequency bin or in a set of adjacent frequency bins may have an amplitude greater than a threshold. Additional aspects for identifying coherent EMI are described herein.

[0155] In some embodiments, after identifying the first subset of MR data, process 1500 may proceed to act 1504 for suppressing EMI in the first subset of MR data to obtain a second subset of MR data. In some embodiments, suppressing EMI in the first subset of MR data may begin with subact 1504a for applying convolution filtering to the first subset of MR data. The convolution filtering may be configured to suppress the contribution of MR spin echo signals in the first subset of MR data, and thereby obtain signal-suppressed MR data. In some embodiments, as described herein, the convolution filtering may be adapted to compensate for spin echo MR signals that are not centered in the acquisition window.

[0156] In some embodiments, EMI may be present in an nth frequency interval of a plurality of frequency intervals comprising MR data. In some embodiments, applying a convolution filter to a first subset of MR data may include calculating a weighted linear combination of data in a plurality of frequency intervals including the nth frequency interval, wherein the weights are determined by coefficients of the convolution filter. In some embodiments, calculating a weighted linear combination of data in a plurality of frequency intervals may include calculating a weighted linear combination of data in the nth frequency interval and adjacent frequency intervals (e.g., the (n±1)th interval, the (n±2)th interval, etc.).

[0157] In some embodiments, the EMI may be present in a plurality of adjacent frequency bins (e.g., the EMI may have a width greater than a single frequency bin). In some embodiments, applying a convolution filter to the first subset of the MR data may include applying a convolution filter having a length equal to the number of adjacent frequency bins in the plurality of adjacent frequency bins, if the number of adjacent frequency bins is an even number, or equal to a number greater than the number of adjacent frequency bins in the plurality of adjacent frequency bins, if the number of adjacent frequency bins is an odd number.

[0158] After applying the convolution filter to the first subset of MR data, the process 1000 may continue by suppressing EMI in the signal-suppressed MR data to obtain EMI-suppressed MR data 1504b. In some embodiments, suppressing EMI in the signal-suppressed MR data may include using an SVD to obtain the EMI-suppressed MR data. In some embodiments, suppressing EMI in the signal-suppressed MR data may include determining an SVD of the signal-suppressed MR data, modifying the SVD by setting at least one singular value of the SVD to zero, and using the modified SVD to obtain corresponding EMI-suppressed MR data. In some embodiments, modifying the SVD may include setting a first singular value of the SVD to zero, setting the first few singular values ​​of the SVD to zero, and / or setting some singular values ​​of the SVD to zero. After suppressing EMI in the signal-suppressed MR data, the process 1500 may continue by applying an inverse of the convolution filter to the EMI-suppressed MR data to obtain a second subset of MR data 1504c.

[0159] In some embodiments, the first subset of MR data may include multiple data portions for respective multiple frequency bins. In some embodiments, where the MRI system includes multiple RF coils, each data portion may include measurements made by each RF coil in each respective frequency bin. In some embodiments, the data in the respective signal suppressed data portion may be organized as N c ×M matrix, where N c may be an integer representing the number of RF coils and M may be an integer representing the number of measurements performed by each RF coil. Then, determining the SVD of the corresponding signal suppressed MR data portion may include determining N c Singular value decomposition of the .×M matrix.

[0160] In some embodiments, the first subset of MR data may include multiple data portions for corresponding multiple frequency bins, and suppressing EMI in the first subset of MR data may include performing the described actions 1504a to 1504c for each specific data portion of the multiple data portions. In some embodiments, suppressing EMI in the first subset of MR data may include applying a convolution filter to the specific data portion to obtain a corresponding signal-suppressed MR data portion, suppressing EMI in the corresponding signal-suppressed MR data portion to obtain a corresponding EMI-suppressed MR data portion, and applying an inverse of the convolution filter to the EMI-suppressed MR data portion. In some embodiments, suppressing EMI in the corresponding signal-suppressed MR data portion may include determining an SVD of the corresponding signal-suppressed MR data portion, modifying the SVD by setting at least one singular value of the SVD to zero, and using the modified SVD to obtain the corresponding EMI-suppressed MR data portion.

[0161] After obtaining the second subset of MR data, the process 1500 can proceed to determine whether EMI remains in the MR data 1005. Determining whether EMI remains in the MR data 1005 can be performed in substantially the same manner as identifying the first subset of MR data affected by EMI in the first act 1502 of the process 1500. If it is determined that EMI may still exist in the MR data, the process 1500 can return to perform additional EMI suppression. In this manner, the process 1500 can iteratively suppress EMI in the MR data until all EMI has an amplitude below a threshold. In some embodiments, as described herein, the process 1500 can iteratively suppress EMI in the MR data until all EMI has an amplitude below a threshold determined based on the standard deviation of the MR data.

[0162] In some embodiments, once the EMI is sufficiently suppressed, process 1500 may proceed to act 1506 for generating an MR image using the second subset of MR data. In some embodiments, generating an MR image using the modified MR data may include modifying the MR data by replacing the first subset of MR data with the second subset of MR data to obtain modified MR data. The modified MR data may then be used to generate an MR image.

[0163] In some embodiments, generating MR images can be achieved using any suitable image reconstruction technique arranged to reconstruct images from a spatial frequency domain to an image domain. Any suitable image reconstruction technique (including but not limited to linear and / or nonlinear reconstruction techniques) can be used for image reconstruction. In some embodiments, image reconstruction can be performed using one or more of fast Fourier transform (FFT), non-uniform Fourier transform, gridding, principal component analysis (PCA), sensitivity encoding (SENSE), conjugate gradient sensitivity encoding (CG-SENSE), generalized autocalibrated partially parallel acquisition (GRAPPA), compressed sensing (CS) and / or deep learning techniques.

[0164] In some embodiments, after generating the MR image, the process 1500 may continue to: output the generated MR image 1008. In some embodiments, outputting the generated image may include displaying the generated MR image. In some embodiments, the generated MR image may be displayed on a screen associated with a desktop or laptop computer, a television monitor, a tablet computer, a smart phone, or any other suitable electronic device. In some embodiments, outputting the generated image may include transmitting the generated MR image to another computing device. For example, the generated MR image may be transmitted through a network (e.g., a local area network (LAN) or a wide area network (WAN)) or through the Internet (e.g., in an electronic message such as an email and / or SMS, etc.). In some embodiments, outputting the generated MR message may include storing the generated MR image in a computer memory. In some embodiments, the generated MR message may be stored locally on the computer memory of the computer generating the MR image, or remotely stored on a computer memory located away from the computer generating the MR image. In some embodiments, the generated MR image may be stored on an image server (such as a DICOM server or a patient database server, etc.).

[0165] Fig.16 is a block diagram of typical components of an MRI system 1600. Fig.16 In the illustrative example of FIG. 1 , the MRI system 1600 includes a computing device 1604, a controller 1606, a pulse sequence storage unit 1608, a power management system 1610, and a magnetic assembly 1620. It should be understood that the MRI system 1600 is illustrative and that the present invention is not limited to the present invention. Fig.16 In addition to or in place of the components shown in Fig.16 1600, the MRI system may have one or more other components of any suitable type. However, the MRI system will generally include these advanced components, although the implementation of these components used by a particular MRI system may be different. It will be appreciated that the techniques described herein for suppressing EMI can be used with any suitable type of MRI system including high-field MRI systems, low-field MRI systems, and ultra-low-field MRI systems. In some implementations, a magnetic shielding coating to reduce magnetic noise can be applied to one or more parts of the MRI system 1600 to reduce magnetic noise from one or more external sources.

[0166] like Fig.16As illustrated, magnetic assembly 1620 includes B0 magnet 1622, shim magnet 1624, radio frequency (RF) transmit and receive coil 1626, and gradient coil 1628. B0 magnet 1622 can be used to generate the main magnetic field B0. B0 magnet 1622 can be a magnetic assembly of any suitable type or combination that can generate the desired main magnetic field B0. In some embodiments, B0 magnet 1622 can be a permanent magnet, an electromagnet, a superconducting magnet, or a hybrid magnet including one or more permanent magnets and one or more electromagnets and / or one or more superconducting magnets. In some embodiments, the B0 magnet 1622 can be configured to generate a B0 magnetic field having a field strength less than or equal to 0.2T and greater than or equal to 20mT, less than or equal to 0.2T and greater than or equal to 50mT, less than or equal to 0.15T and greater than or equal to 40mT, less than or equal to 0.1T and greater than or equal to 20mT, or less than or equal to 0.1T and greater than or equal to 50mT.

[0167] In some embodiments, the B0 magnet 1622 may include a first B0 magnet and a second B0 magnet, each of which includes permanent magnet blocks arranged in concentric rings around a common center. The first B0 magnet and the second B0 magnet may be arranged in a bi-planar configuration such that the imaging area is located between the first B0 magnet and the second B0 magnet. In some embodiments, the first B0 magnet and the second B0 magnet may each be coupled to and supported by a ferromagnetic yoke configured to capture and direct magnetic flux from the first B0 magnet and the second B0 magnet.

[0168] The gradient coils 1628 may be arranged to provide a gradient field, and for example may be arranged to generate gradients in three substantially orthogonal directions (X, Y, Z) in the B0 field. The gradient coils 1628 may be configured to encode the transmitted MR signals by systematically varying the B0 field (the B0 field generated by the magnet 1622 and / or the shim magnet 1624) to encode the spatial position of the received MR signals as a function of frequency or phase. In some embodiments, the gradient coils 1628 may be configured to vary the frequency or phase as a linear function of the spatial position along a particular direction, although more complex spatial encoding profiles may also be provided by using nonlinear gradient coils. In some embodiments, the gradient coils 1628 may be implemented using a laminate (e.g., a printed circuit board).

[0169] MRI is performed by exciting and detecting the transmitted MR signals using transmit and receive coils, commonly referred to as radio frequency (RF) coils, respectively. The transmit / receive coil 1626 may include a separate coil for transmitting and receiving, multiple coils for transmitting and / or receiving, or the same coil for transmitting and receiving. Thus, the transmit / receive component may include one or more coils for transmitting, one or more coils for receiving, and / or one or more coils for transmitting and receiving. The transmit / receive coil 1626 is also commonly referred to as Tx / Rx or Tx / Rx coil to generally refer to various configurations of the transmit and receive magnetic components of an MRI system. These terms are used interchangeably herein. Fig.16 , the RF transmit and receive coils 1626 include one or more transmit coils that can be used to generate RF pulses to induce an oscillating magnetic field B1. The (one or more) transmit coils can be configured to generate any suitable type of RF pulses. The transmit / receive coils 1626 can include additional electronic components of the transmit and receive chains.

[0170] The power management system 1610 may include electronics for providing operating power to one or more components of the MRI system 1600. In some embodiments, the power management system 1610 may include one or more power supplies, gradient power components, transmit coil components, and / or any other suitable power electronics required to provide suitable operating power to power on and operate the components of the MRI system 1600. The power management system 1610 may include a power supply 1612, (one or more) amplifiers 1614, transmit / receive circuitry 1616, and thermal management components 1618 (e.g., cryogenic cooling equipment for superconducting magnets, or fluid cooling equipment for electromagnets and / or circuitry). The power supply 1612 may include electronics for providing operating power to a magnetic assembly 1620 of the MRI system 1600. In some embodiments, the power supply 1612 may include electronics for providing operating power to one or more B0 coils (e.g., B0 magnet 1622) to generate a main magnetic field used by a low-field MRI system. In a non-limiting example, the power management system 1610 may receive power from a standard wall outlet to provide power to the MRI system 1600 .

[0171] The amplifier(s) 1614 may include: one or more RF receive (Rx) preamplifiers that amplify MR signals detected by one or more RF receive coils (e.g., coil 1626); one or more RF transmit (Tx) power components configured to provide power to one or more RF transmit coils (e.g., coil 1626); one or more gradient power components configured to provide power to one or more gradient coils (e.g., gradient coil 1628); and one or more shim power components configured to provide power to one or more shim coils (e.g., shim magnet 1624). The transmit / receive circuit system 1616 may be configured to select (e.g., using one or more switches) whether the RF transmit coil or the RF receive coil is being operated.

[0172] like Fig.16 As illustrated, the MRI system 1600 includes a controller 1606 (also referred to as a console) having control electronics that send instructions to the power management system 1610 and receive information from the power management system 109. The controller 1606 can be configured to implement one or more pulse sequences that are used to determine instructions sent to the power management system 1610 to operate the magnetic assembly 1620 in a desired sequence (e.g., parameters for operating the RF transmit and receive coils 1626, parameters for operating the gradient coils 1628, etc.). In some embodiments, the controller 1606 also interacts with a computing device 1604 that is programmed to process received MR data. In some embodiments, the computing device 1604 can process the received MR data using any suitable (one or more) image reconstruction process to generate one or more MR images. The controller 1606 can provide information related to the one or more pulse sequences to the computing device 1604 for processing the data by the computing device. In some embodiments, the controller 1606 may provide information related to one or more pulse sequences to the computing device 1604, and the computing device may perform an image reconstruction process based at least in part on the provided information.

[0173] Fig.17 Illustrative components of a portion of an MRI system that may be used for broadband EMI suppression according to some embodiments described herein are shown. In some embodiments, the transmit / receive system 1700 may form at least a portion of a transmit / receive device of the MRI system. As discussed herein, the transmit / receive system 1700 may be configured to detect MR signals emitted from excited atoms of a subject 1704 being imaged, and to characterize noise in the environment to suppress or remove the characterized noise from the detected MR signals.

[0174] like Fig.17 As shown, the transmit / receive system 1700 may include a primary RF receive coil 1702, which is configured to measure MR signals emitted by the subject 1704 in response to an excitation pulse sequence. The excitation pulse sequence may be generated by the primary RF receive coil 1702 and / or by one or more other transmit RF coils disposed near the subject 1704 and configured to generate a suitable MR pulse sequence when operated. The primary receive coil 1702 may be a single coil or may be a plurality of coils, wherein in the latter case, the primary receive coil 1702 may be used to perform parallel MRI. The tuning circuit system 1708 may facilitate the operation of the primary receive coil 1702, and may provide the signals detected by the (one or more) RF coils 1702 to an acquisition system 1710, which may amplify the detected signals, digitize the detected signals, and / or perform any other suitable type of processing.

[0175] The transmit / receive system 1700 may also include (one or more) auxiliary sensors 1706, which may include any number or type of (one or more) sensors configured to detect or otherwise measure noise sources in the environment and / or ambient noise generated by the MRI system itself. The noise measured by the (one or more) auxiliary sensors 1706 may be characterized and used to suppress noise in MR signals detected by the (one or more) primary RF coils 1702 using the techniques described herein. In some embodiments, after the acquisition system 1710 processes the signals detected by the (one or more) RF coils 1702 and the (one or more) auxiliary sensors 1706, the acquisition system 1710 may provide the processed signals to one or more other components of the MRI system for further processing (e.g., for use in forming one or more MR images of the subject 1704). The acquisition system 1710 may include any suitable circuitry, and may include, for example, one or more controllers and / or processors configured to control the MRI system to perform noise suppression according to embodiments described herein.

[0176] In some embodiments, the auxiliary sensor(s) 1706 may include one or more auxiliary coils configured to measure noise from one or more noise sources in the environment in which the MRI system is operating. In some embodiments, the primary RF coil(s) 1702 may include eight primary RF coils, and the auxiliary sensor(s) 1706 may include eight auxiliary coils, although it should be understood that the number of primary RF coil(s) 1702 and the number of auxiliary sensors(s) 1706 may be less than or greater than eight (e.g., 2, 4, 6, 10, 12, 14, and / or 16), and the number of primary RF coil(s) 1702 and the number of auxiliary sensors(s) 1706 need not be equal, as the technology described herein is not limited in this regard.

[0177] In some embodiments, the auxiliary RF coil(s) may be configured to be more sensitive to ambient noise than to any noise generated by the coil(s) itself. For example, the auxiliary RF coil(s) may have a sufficiently large aperture and / or number of turns such that the auxiliary coil(s) may be more sensitive to noise from the environment than to noise generated by the auxiliary coil(s) itself. In some embodiments, the auxiliary RF coil(s) may have a larger aperture and / or a greater number of turns than the primary RF coil(s) 1702. However, the auxiliary RF coil(s) may be the same as the primary RF coil(s) in this respect and / or may be different from the primary RF coil(s) 1702 in other respects.

[0178] In some embodiments, the auxiliary RF coil(s) may be located at a distance from the primary RF coil 1702. The distance may be selected such that the auxiliary coil(s) are sufficiently far from the sample 1704 to avoid sensing MR signals emitted by the sample during imaging, but are otherwise arranged as close to the primary RF coil 1702 as possible such that the auxiliary coil(s) detect noise similar to the noise detected by the primary coil(s) 1702. In this manner, noise from one or more noise sources measured by the auxiliary coil(s) 1706 and characterized using the techniques discussed herein (e.g., by using the detected noise to at least partially calculate a transfer function that can be used to suppress and / or cancel noise present on the detected MR signals) may be representative of the noise detected by the primary coil(s) 1702. In some embodiments, the auxiliary coil(s) may not be RF coils, but may be any type of sensor capable of detecting or measuring noise in the environment that may affect the performance of the MRI system.

[0179] According to some embodiments, the auxiliary sensor(s) 1706 may include the primary coil(s) themselves, where the primary RF coil(s) are labeled as both the primary receive coil(s) 1702 and the auxiliary sensor(s) 1706 used by the system, since the primary RF coil(s) may perform both roles in some cases. As discussed herein, certain pulse sequences may facilitate the use of signals acquired from the primary coil(s) to also suppress noise thereon. A pulse sequence generally refers to operating the transmit coil(s) and the gradient coil(s) in a specified sequence to induce an MR response. By repeating the same pulse sequence using the same spatial encoding, "redundant" MR signals may be obtained and used to estimate the noise present in the MR signals.

[0180] Fig.18 An MRI system 1800 is illustrated that can be used to acquire MR images of a subject in accordance with some embodiments. The MRI system 1800 may include a B0 magnet 1810 partially formed by an upper magnet 1810a and a lower magnet 1810b, the B0 magnet 1810 being coupled with a yoke 1820 to increase the flux density within the imaging region. The B0 magnet 1810 may be housed in a magnet housing 1812 together with a gradient coil 1815. In accordance with some embodiments, the B0 magnet 1810 may include an electromagnet. In accordance with some embodiments, the B0 magnet 1810 may include a permanent magnet.

[0181] The MRI system 1800 may also include a base 1850 for housing the electronics required to operate the MRI system. In some embodiments, the base 1850 may house electronics including power components configured to operate the MRI system 1800 using mains power (e.g., via connection to a standard wall outlet and / or large appliance outlet). In some embodiments, the MRI system 1800 may be brought to the patient and plugged into a nearby wall outlet.

[0182] The base 1850 may be supported by a transport mechanism 1880. Fig.18 As shown, the transport mechanism 1880 may include wheels that enable movement of the MRI system 1800. In some embodiments, the transport mechanism 1880 may include motorized wheels configured to assist a user in transporting the MRI system 1800. In this manner, the MRI system 1800 may be transported to the patient and maneuvered to the bedside for imaging. Fig.19 An MRI system 1900 is shown transported to a patient's bedside to perform a brain scan.

[0183] Fig. 20An alternative MRI system 2000 that can be used to acquire MR images of a subject according to some embodiments is illustrated. The MRI system 2000 may include a housing 2010 that may house a B0 magnet having a bore 2020. An imaging region may be located within the bore 2020. In some embodiments, the subject may be placed on a subject support 2030 and slid into the bore 2020 so as to be placed within the imaging region of the MRI system 2000. In some embodiments, the B0 magnet may include a superconducting magnet. In some embodiments, the B0 magnet may include an electromagnet. In some embodiments, the B0 magnet may generate a magnetic field having an intensity in the range of 0.2T to 0.5T, 0.5T to 1.5T, 1.5T to 3T, 2T to 4T, or greater than 4T. In some embodiments, the MRI system 2000 may be a high field system.

[0184] Fig.21 is a diagram of an exemplary computer system on which the embodiments described herein may be implemented. Fig.21 An exemplary implementation of a computer system 2100 that can be used in conjunction with any embodiment of the disclosure provided herein is shown. In some embodiments, any of the processes described herein can be implemented on and / or using a computer system 2100. The computer system 2100 may include one or more processors 2110 and one or more articles of manufacture, the one or more articles of manufacture including tangible (e.g., non-transitory) computer-readable storage media (e.g., memory 2120 and one or more non-volatile storage media 2130). The processor 2110 can control writing data to the memory 2120 and the non-volatile storage device 2130 and reading data from the memory 2120 and the non-volatile storage device 2130 in any suitable manner. In order to perform any functionality described herein, processor 2110 may execute one or more processor-executable instructions stored in one or more non-transitory computer-readable storage media (e.g., memory 2120), which may be used as non-transitory computer-readable storage media for storing processor-executable instructions for execution by processor 2110.

[0185] Example 1

[0186] In an exemplary embodiment, EMI suppression can be achieved in conjunction with a low-field MRI system. The low-field MRI system may include a B0 magnet configured to generate a B0 magnetic field having a magnetic field strength in the range of from 0.05T to 0.2T. The B0 magnet may include a permanent magnet arranged in one or more concentric rings. The low-field MRI system may have an open configuration, wherein the permanent magnet may be arranged in a dual-plane configuration so that the imaging area is configured therebetween. The low-field MRI system may also include one or more gradient coils. The low-field MRI system may also include one or more RF coils. In addition to one or more RF coils, the low-field MRI system may include one or more auxiliary sensors configured to detect EMI. The auxiliary sensors may be positioned outside the field of view of the low-field MRI system so that they mainly detect noise outside the low-field MRI system, rather than MR signals generated during imaging using the low-field MRI system. The low-field MRI system may be located outside a shielded room, inside a partially shielded room, or inside a fully shielded room. The low-field MRI system may be portable and may be transported to different locations where it may be used.

[0187] EMI suppression can be performed by acquiring MR data using a low-field MRI system. A first subset of MR data in one or more frequency intervals of the MR data can be identified as including EMI based on a portion of the data acquired near or at an edge of the k-space. A convolution filter can be applied to the first subset of the MR data to suppress the spin echo MR signals in the first subset of the MR data and obtain signal-suppressed MR data. The SVD of the signal-suppressed MR data can be determined, and the first singular value of the SVD can be set to zero to obtain a modified SVD. The modified SVD can be used to obtain EMI-suppressed MR data, and the inverse of the convolution filter can be applied to the EMI-suppressed MR data to obtain a second subset of MR data. The first subset of MR data can be replaced by the second subset of MR data, and the modified MR data can be used to generate an MR image. The MR image can be output (e.g., displayed, transmitted, and / or stored in a computer memory) after being generated.

[0188] Example 2

[0189] In another exemplary embodiment, EMI suppression can be achieved in conjunction with a high field MRI system. The high field MRI system can include a B0 magnet configured to generate a B0 magnetic field having a magnetic field strength in the range of from 1.0T to 13.0T. The B0 magnet can include a magnet arranged to form a hole so that the imaging area is configured in the hole. The magnet can be an electromagnet, a superconducting magnet, or a combination of an electromagnet and a superconducting magnet. The high field MRI system can be located in a shielded room or a partially shielded room.

[0190] EMI suppression can be performed by acquiring MR data using a high-field MRI system. A first subset of MR data in one or more frequency intervals of the MR data can be identified as including EMI based on a portion of the data acquired near or at an edge of the k-space. A convolution filter can be applied to the first subset of the MR data to suppress the spin echo MR signals in the first subset of the MR data and obtain signal-suppressed MR data. The SVD of the signal-suppressed MR data can be determined, and the first singular value of the SVD can be set to zero to obtain a modified SVD. The modified SVD can be used to obtain EMI-suppressed MR data, and the inverse of the convolution filter can be applied to the EMI-suppressed MR data to obtain a second subset of MR data. The first subset of MR data can be replaced by the second subset of MR data, and the modified MR data can be used to generate an MR image. The MR image can be output (e.g., displayed, transmitted, and / or stored in a computer memory) after being generated.

[0191] Example 3

[0192] In another exemplary embodiment, EMI suppression can be achieved in conjunction with a low-field, medium-field, or high-field MRI system. The MRI system can include a B0 magnet configured to generate a B0 magnetic field having a magnetic field strength in a range from 0.02T to 13T. The B0 magnet can include a permanent magnet, an electromagnet, and / or a superconducting magnet arranged to form an imaging region. The MRI system can be located outside a shielded room, inside a partially shielded room, or inside a fully shielded room.

[0193] EMI suppression can be performed by acquiring MR data using an MRI system. A first subset of MR data in one or more frequency intervals of the MR data can be identified as including EMI based on a portion of the data acquired near or at an edge of the k-space. A convolution filter can be applied to the first subset of the MR data to suppress the spin echo MR signals in the first subset of the MR data and obtain signal-suppressed MR data. The SVD of the signal-suppressed MR data can be determined, and the first singular value of the SVD can be multiplied by a number between 0 and 1 to obtain a modified SVD. The modified SVD can be used to obtain EMI-suppressed MR data, and the inverse of the convolution filter can be applied to the EMI-suppressed MR data to obtain a second subset of MR data. The first subset of MR data can be replaced by the second subset of MR data, and the modified MR data can be used to generate an MR image. The MR image can be output (e.g., displayed, transmitted, and / or stored in a computer memory) after being generated.

[0194] Furthermore, the present technology may be embodied in any of the following structures:

[0195] (1) A method for suppressing electromagnetic interference (EMI) in magnetic resonance data (MR data) obtained by a magnetic resonance imaging system (MRI system), the method comprising: using at least one computer hardware processor to: identify a first subset of the MR data that is affected by EMI; suppress EMI in the first subset of the MR data to obtain a second subset of the MR data by: applying a filter to the first subset of the MR data to suppress the contribution of MR spin echo signals in the first subset of the MR data, thereby obtaining signal-suppressed MR data; suppressing EMI in the signal-suppressed MR data to obtain EMI-suppressed MR data; and applying the inverse of the filter to the EMI-suppressed MR data to obtain the second subset of the MR data; generating an MR image using the second subset of the MR data; and outputting the generated MR image.

[0196] (2a) The method of (1), wherein suppressing EMI in the signal-suppressed MR data comprises using component decomposition to obtain the EMI-suppressed MR data.

[0197] (2b) A method according to (1), wherein suppressing EMI in the signal-suppressed MR data includes: applying a domain transform to the signal-suppressed MR data, using component decomposition to obtain the EMI-suppressed MR data, and applying an inverse of the domain transform, wherein the domain transform and the EMI signal suppression can be applied iteratively.

[0198] (3) A method according to (1) or (2a) or (2b), wherein the first subset of the MR data includes multiple data parts for corresponding multiple frequency or time intervals, and wherein suppressing EMI in the first subset of the MR data includes: for each specific data part among the multiple data parts, applying the filtering to the specific data part to obtain a corresponding signal-suppressed MR data part; suppressing EMI in the corresponding signal-suppressed MR data part to obtain a corresponding EMI-suppressed MR data part; and applying the inverse of the filtering to the EMI-suppressed MR data part.

[0199] (4) A method according to any one of (1) to (3), wherein suppressing EMI in the corresponding signal-suppressed MR data portion includes: determining a component decomposition of the corresponding signal-suppressed MR data portion; modifying the SVD by setting at least one singular value of the component decomposition to a predetermined value or by multiplying at least one singular value of the component decomposition by a predetermined weight; and obtaining the corresponding EMI-suppressed MR data portion using the modified component decomposition.

[0200] (5) A method according to any one of (1) to (4), wherein the MRI system includes multiple radio frequency coils, i.e., multiple RF coils, and wherein each of the multiple data portions includes measurements performed by each of the multiple RF coils for a corresponding frequency or time interval in the multiple frequency or time intervals.

[0201] (6) The method according to any one of (1) to (5), wherein the data in the corresponding signal suppressed data portion is organized into N c ×M matrix, where N c is an integer representing the number of RF coils and M is an integer representing the number of measurements performed by each of the RF coils, and wherein determining the component decomposition of the corresponding signal suppressed MR data portion comprises: determining the N c Singular value decomposition of the .×.M matrix.

[0202] (7) The method according to any one of (1) to (6) further includes: before identifying the first subset of the MR data, generating the MR data by operating the MRI system according to a spin echo pulse sequence or a gradient echo pulse sequence.

[0203] (8) A method according to any one of (1) to (7), wherein the spin echo pulse sequence is selected from the following group, which consists of a T1 pulse sequence, a T2 pulse sequence, a fluid attenuated inversion recovery (FLAIR) pulse sequence and a diffusion weighted imaging (DWI) pulse sequence.

[0204] (9) The method according to any one of (1) to (8) further includes: after generating the MR data and before identifying the first subset, suppressing EMI in the MR data detected by an auxiliary coil of the MRI system.

[0205] (10) A method according to any one of (1) to (9), wherein the EMI is narrowband EMI, and wherein the MR data includes sensor domain data in multiple frequency or time intervals, and wherein the EMI exists in a certain frequency or time interval among the multiple frequency or time intervals.

[0206] (11) The method according to any one of (1) to (10), wherein the EMI exists in no more than a threshold number of adjacent frequency or time intervals among the multiple frequency or time intervals.

[0207] (12) A method according to any one of (1) to (11), wherein the EMI exists in the nth frequency or time interval among the multiple frequency or time intervals, and wherein applying the filtering to the first subset of MR data includes: calculating a weighted linear combination of data in multiple frequency or time intervals including the nth frequency or time interval using weights determined by coefficients of the filtering.

[0208] (13) A method according to any one of (1) to (12), wherein the MR data includes data in multiple frequency or time intervals, the EMI exists in multiple adjacent frequency or time intervals, and applying the filter to the first subset of the MR data includes: applying the following filter, which has a length at least equal to the number of adjacent frequency or time intervals in the multiple adjacent frequency or time intervals.

[0209] (14) A method according to any one of (1) to (13), wherein identifying the first subset of the MR data includes: identifying data in a single frequency or time interval or a set of adjacent frequency or time intervals of the MR data that is affected by EMI.

[0210] (15) A method according to any one of (1) to (14), wherein identifying the first subset of the MR data is performed by analyzing a portion of the MR data acquired during at least one predetermined echo signal of a pulse sequence used to acquire the MR data.

[0211] (16) A method according to any one of (1) to (15), wherein identifying the first subset of the MR data includes: determining whether data in a frequency or time interval or in a set of adjacent frequency or time intervals has an amplitude greater than a threshold.

[0212] (17) A method according to any one of (1) to (16), wherein generating the MR image includes: modifying the MR data by replacing the first subset of the MR data with the second subset of the MR data to obtain modified MR data; and generating the MR image using the modified MR data.

[0213] (18) A method according to any one of (1) to (17), wherein the MRI system includes an RF coil configured to transmit radio frequency pulses, i.e., RF pulses, and determining the first subset of the MR data includes: transforming the MR data into a reference frame of the transmitted RF pulses.

[0214] (19) A magnetic resonance imaging system, or MRI system, comprises: a magnetic system having a plurality of magnetic components for generating a magnetic field for performing MRI by acquiring MR data; and at least one processor configured to: identify a first subset of the MR data that is affected by electromagnetic interference (EMI); suppress EMI in the first subset of the MR data to obtain a second subset of the MR data by: applying a filter to the first subset of the MR data to suppress contribution of MR spin echo signals in the first subset of the MR data, thereby obtaining signal-suppressed MR data; suppress EMI in the signal-suppressed MR data to obtain EMI-suppressed MR data; and apply the inverse of the filter to the EMI-suppressed MR data to obtain the second subset of the MR data; generate an MR image using the second subset of the MR data; and output the generated MR image.

[0215] (20) at least one tangible computer-readable storage medium storing processor-executable instructions, which, when executed by the at least one processor, cause the at least one processor to perform a method for suppressing electromagnetic interference (EMI) in magnetic resonance data (MR data) obtained by a magnetic resonance imaging system (MRI system), the method comprising: identifying a first subset of the MR data that is affected by EMI; suppressing EMI in the first subset of the MR data to obtain a second subset of the MR data by: applying a filter to the first subset of the MR data to suppress contribution of MR spin echo signals in the first subset of the MR data, thereby obtaining signal-suppressed MR data; suppressing EMI in the signal-suppressed MR data to obtain EMI-suppressed MR data; and applying an inverse of the filter to the EMI-suppressed MR data to obtain the second subset of the MR data; generating an MR image using the second subset of the MR data; and outputting the generated MR image.

[0216] (21) A method for generating an MR image by suppressing electromagnetic interference (EMI) in magnetic resonance data (MR data), the MR data being acquired using at least one radio frequency receive coil section (RF receive coil section) of an MRI system, the suppression being used to remove zipper line noise artifacts that would otherwise be visible in the MR image, the MRI system being in communication with a computer including a processor, the method comprising: using the processor, identifying a noisy subset of the MR data for which EMI is to be suppressed; using the processor, applying a filter to the noisy subset of the MR data to suppress contributions of one or more MR signals to the noisy subset to obtain signal-suppressed MR data; using the processor, suppressing EMI in the signal-suppressed MR data to obtain EMI-suppressed MR data; using the processor, applying an inverse of the filter to the EMI-suppressed MR data to obtain a denoised subset of the MR data in which EMI has been at least partially suppressed; and using the processor, generating the MR image using the denoised subset of the MR data.

[0217] (22) The method according to (21) further includes: obtaining the MR data using the at least one RF receiving coil section of the MRI system.

[0218] (23) A method according to (21) or (22), wherein applying the filtering to the noisy subset of the MR data includes: suppressing the contribution of one or more spin echo MR signals to the noisy subset of the MR data.

[0219] (24) The method of any one of (21) to (23), wherein suppressing EMI in the signal-suppressed MR data comprises: using component decomposition to obtain the EMI-suppressed MR data.

[0220] (25) A method according to any one of (21) to (24), wherein the noisy subset of the MR data includes multiple data parts for corresponding multiple frequency or time intervals, and wherein suppressing EMI in the noisy subset of the MR data includes: for each specific data part among the multiple data parts, applying the filtering to the specific data part to obtain a corresponding signal-suppressed MR data part; suppressing EMI in the corresponding signal-suppressed MR data part to obtain a corresponding EMI-suppressed MR data part; and applying the inverse of the filtering to the EMI-suppressed MR data part.

[0221] (26) A method according to any one of (21) to (25), wherein suppressing EMI in the corresponding signal-suppressed MR data portion includes: determining a component decomposition of the corresponding signal-suppressed MR data portion; modifying the component decomposition by setting at least one singular value of the component decomposition to a predetermined value or by multiplying at least one singular value of the component decomposition by a predetermined weight; and obtaining the corresponding EMI-suppressed MR data portion using the modified component decomposition.

[0222] (27) A method according to any one of (21) to (26), wherein at least one RF coil includes a plurality of RF coils, and wherein each of the plurality of data portions includes measurements made by each of the plurality of RF coils for a corresponding frequency or time interval in the plurality of frequency or time intervals.

[0223] (28) The method according to any one of (21) to (27), wherein the data in the corresponding signal suppressed data portion is organized into N c ×M matrix, where N c is an integer representing the number of RF coils and M is an integer representing the number of measurements performed by each of the RF coils, and wherein determining the component decomposition of the corresponding signal suppressed MR data portion comprises: determining the N c Singular value decomposition of the .×.M matrix.

[0224] (29) The method according to any one of (21) to (28) further includes: obtaining the MR data using the at least one RF receiving coil unit of the MRI system during operation of the MRI system according to a spin echo pulse sequence or a gradient echo pulse sequence.

[0225] (30) A method according to any one of (21) to (29), wherein the spin echo pulse sequence is selected from the following group, which consists of a T1 pulse sequence, a T2 pulse sequence, a fluid attenuated inversion recovery (FLAIR) pulse sequence and a diffusion weighted imaging (DWI) pulse sequence.

[0226] (31) The method according to any one of (21) to (30) further includes: after generating the MR data and before identifying the noisy subset, suppressing EMI in the MR data detected by an auxiliary RF coil of the MRI system.

[0227] (32) A method according to any one of (21) to (31), wherein the EMI is narrowband EMI, and wherein the MR data includes sensor domain data organized in multiple frequency or time intervals, and wherein the EMI exists in a frequency or time interval among the multiple frequency or time intervals.

[0228] (33) A method according to any one of (21) to (32), wherein the EMI exists in no more than a threshold number of adjacent frequency or time intervals among the multiple frequency or time intervals.

[0229] (34) A method according to any one of (21) to (33), wherein the EMI exists in the nth frequency or time interval among the multiple frequency or time intervals, and wherein applying the filtering to the noisy subset of the MR data includes: calculating a weighted linear combination of data in multiple frequency or time intervals including the nth frequency or time interval using weights determined by coefficients of the filtering.

[0230] (35) A method according to any one of (21) to (34), wherein identifying the first subset of the MR data includes: identifying data in a single frequency or time interval or a set of adjacent frequency or time intervals of the MR data that is affected by EMI.

[0231] (36) A method according to any one of (21) to (35), wherein the MR data includes data in multiple frequency or time intervals, the EMI exists in multiple adjacent frequency or time intervals, and applying the filter to the noisy subset of the MR data includes: applying a convolution filter, the convolution filter having a length at least equal to the number of adjacent frequency or time intervals in the multiple adjacent frequency or time intervals.

[0232] (37) A method according to any one of (21) to (36), wherein identifying the noisy subset of the MR data is performed by analyzing a portion of the MR data acquired during at least one predetermined echo signal of a pulse sequence used to acquire the MR data.

[0233] (38) A method according to any one of (21) to (37), wherein identifying the noisy subset of the MR data includes: determining whether data in one frequency or time interval or in a set of adjacent frequency or time intervals has an amplitude greater than a threshold.

[0234] (39) A method according to any one of (21) to (38), wherein generating the MR image comprises: modifying the MR data by replacing the noisy subset of the MR data with the denoised subset of the MR data to obtain modified MR data; and generating the MR image using the modified MR data.

[0235] (40) A magnetic resonance imaging system, or MRI system, comprising: a magnetic system having a plurality of magnetic components for generating a magnetic field for performing MRI by acquiring magnetic resonance data, or MR data; and a processor configured to perform a method for generating an MR image by suppressing electromagnetic interference, or EMI, in the MR data, wherein the suppression is used to remove zipper line noise artifacts that would otherwise be visible in the MR image: using the processor, identifying a noisy subset of the MR data for which EMI is to be suppressed; using the processor, applying a filter to the noisy subset of the MR data to suppress contributions of one or more MR signals to the noisy subset to obtain signal-suppressed MR data; using the processor, suppressing EMI in the signal-suppressed MR data to obtain EMI-suppressed MR data; using the processor, applying an inverse of the filter to the EMI-suppressed MR data to obtain a denoised subset of the MR data in which EMI has been at least partially suppressed; and using the processor, generating the MR image using the denoised subset of the MR data.

[0236] (41) at least one tangible computer-readable storage medium storing instructions executable by a processor, the instructions, when executed by the processor, causing the processor to perform a method for generating an MR image by suppressing electromagnetic interference (EMI) in magnetic resonance data (MR data), the MR data being acquired using at least one radio frequency receive coil section (RF receive coil section) of an MRI system, the suppression being used to remove zipper line noise artifacts that would otherwise be visible in the MR image, the MRI system being in communication with a computer including the processor, the method comprising: using the processor, identifying a noisy subset of the MR data for which EMI is to be suppressed; using the processor, applying a filter to the noisy subset of the MR data to suppress contributions of one or more MR signals to the noisy subset to obtain signal-suppressed MR data; using the processor, suppressing EMI in the signal-suppressed MR data to obtain EMI-suppressed MR data; using the processor, applying an inverse of the filter to the EMI-suppressed MR data to obtain a denoised subset of the MR data in which EMI has been at least partially suppressed; and using the processor, generating the MR image using the denoised subset of the MR data.

[0237] Thus, after describing several aspects and embodiments of the technology set forth in this disclosure, it should be understood that various changes, modifications and improvements will be easily conceived by those skilled in the art. Such changes, modifications and improvements are intended to be within the spirit and scope of the technology described herein. For example, a person of ordinary skill in the art will easily conceive of various other ways and / or structures for performing functions and / or obtaining results and / or one or more than one advantages described herein, and such variations and / or modifications are each considered to be within the scope of the embodiments described herein. Those skilled in the art will recognize or be able to determine many equivalents of the specific embodiments described herein using only routine experiments. Therefore, it should be understood that the foregoing embodiments are presented only by way of example, and within the scope of the appended claims and their equivalents, except for specific descriptions, embodiments of the present invention may be implemented in other ways. In addition, if the features, systems, articles, materials, kits and / or methods described herein are not mutually inconsistent, any combination of two or more such features, systems, articles, materials, kits and / or methods is included within the scope of this disclosure.

[0238] The above embodiments can be implemented in any of a number of ways. One or more aspects and embodiments of the performance of the process or method disclosed herein can utilize executable program instructions of a device (e.g., a computer, a processor, or other device) to perform the process or method, or control the performance of the process or method. In this regard, various inventive concepts can be embodied as a computer-readable storage medium (or multiple computer-readable storage media) (e.g., a computer memory, one or more floppy disks, compact disks, optical disks, tapes, flash memories, circuit configurations in field programmable gate arrays or other semiconductor devices, or other tangible computer storage media) encoded with one or more programs, which, when executed on one or more computers or other processors, are used to implement the method of one or more embodiments in the various embodiments described above. One or more computer-readable media can be transportable, so that one or more programs stored on the one or more computer-readable media can be loaded onto one or more different computers or other processors to implement various aspects in the above aspects. In some embodiments, the computer-readable medium can be a tangible (e.g., non-transient) computer-readable medium. In some embodiments, the computer-readable medium can include a persistent memory.

[0239] The term "program" or "software" as used herein refers in a general sense to any type of computer code or computer executable instruction set that can be used to program a computer or other processor to implement the various aspects described above. In addition, it should be understood that, according to one aspect, one or more computer programs that perform the methods of the present disclosure when executed do not need to reside on a single computer or processor, but can be distributed in a modular manner among multiple different computers or processors to implement various aspects of the present disclosure.

[0240] Computer executable instructions may take a variety of forms, such as program modules, etc., that are executed by one or more computers or other devices. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform specific tasks or implement specific abstract data types. Typically, the functionality of the program modules may be combined or distributed as desired in various embodiments.

[0241] In addition, the data structure may be stored in a computer-readable medium in any suitable form. To simplify the illustration, the data structure may be shown as having fields that are related by position in the data structure. Likewise, this relationship may be achieved by assigning a storage unit with a position in the computer-readable medium for conveying the relationship between the fields to the fields. However, any suitable mechanism may be used to establish the relationship between the information in the fields of the data structure, including by using pointers, tags or other mechanisms for establishing the relationship between data elements.

[0242] When implemented in software, the software code can be executed on any suitable processor or collection of processors, whether located in a single computer or distributed among multiple computers.

[0243] Furthermore, it should be appreciated that a computer may be embodied in any of a number of forms such as, by way of non-limiting example, a rack-mount computer, a desktop computer, a laptop computer, or a tablet computer, etc. Additionally, a computer may be embedded in a device not generally regarded as a computer but having suitable processing capabilities, including a personal digital assistant (PDA), a smart phone, or any other suitable portable or fixed electronic device.

[0244] In addition, a computer may have one or more input and output devices. These devices may be used to present a user interface, etc. Examples of output devices that may be used to provide a user interface include: a printer or display screen for visual presentation of output and a speaker or other sound generating device for audible presentation of output. Examples of input devices that may be used for a user interface include: a keyboard and a pointing device such as a mouse, a touch pad, and a digitizing tablet. As another example, a computer may receive input information through speech recognition or in other audible formats.

[0245] Such computers may be interconnected by one or more networks of any suitable form, including local or wide area networks, such as enterprise networks and intelligent networks (IN) or the Internet, etc. Such networks may be based on any suitable technology and may operate according to any suitable protocol, and may include wireless networks, wired networks, or fiber optic networks.

[0246] In addition, as described, some aspects may be embodied as one or more than one method. The actions performed as part of the method may be ordered in any suitable manner. Therefore, even if shown as sequential actions in the illustrative embodiments, embodiments may be constructed that perform actions in a different order than that illustrated, which may include performing some actions simultaneously.

[0247] All definitions, as defined and used herein, should be understood to control over dictionary definitions, definitions in documents incorporated by reference, and / or ordinary meanings of the defined terms.

[0248] As used herein, the indefinite articles "a" and "an" should be understood to mean "at least one", unless explicitly indicated to the contrary.

[0249] As used herein in the specification and claims, the phrase "and / or" should be understood to refer to "either or both" of the elements so combined (i.e., elements that are presented combined in some cases and separately in other cases). Multiple elements listed with "and / or" should be interpreted in the same manner, i.e., "one or more than one" of the elements so combined. In addition to the elements specifically identified by the "and / or" clause, other elements may optionally be present, whether related or unrelated to those specifically identified elements. Thus, as a non-limiting example, a reference to "A and / or B", when used in conjunction with open language such as "comprising", may refer to A only (optionally including elements other than B) in one embodiment; may refer to B only (optionally including elements other than A) in another embodiment; may refer to both A and B (optionally including other elements) in yet another embodiment; and so on.

[0250] As used herein in the specification and claims, the phrase "at least one" when referring to a list of one or more than one elements should be understood to mean at least one element selected from any one or more than one element of the elements in the list of elements, but not necessarily including at least one element of each and every element specifically listed in the list of elements, and not excluding any combination of elements in the list of elements. This definition also allows that elements other than the elements specifically identified in the list of elements to which the phrase "at least one" refers may optionally be present, whether related or unrelated to the specifically identified elements. Thus, as a non-limiting example, "at least one of A and B" (or equivalently "at least one of A or B", or equivalently "at least one of A and / or B") may mean, in one embodiment, optionally including more than one at least one A, without the presence of B (and optionally including elements other than B); in another embodiment, it may mean optionally including more than one at least one B, without the presence of A (and optionally including elements other than A); in yet another embodiment, it may mean optionally including more than one at least one A and optionally including more than one at least one B (and optionally including other elements); and so on.

[0251] In the claims and in the above description, all transitional phrases such as "comprising," "including," "carrying," "having," "containing," "involving," "holding," and "comprising" shall be understood to be open-ended, i.e., meaning including but not limited to. Only the transitional phrases "consisting of" and "consisting essentially of" shall be closed or semi-closed transitional phrases, respectively.

[0252] The terms "approximately" and "about" may be used in some embodiments to mean within ±20% of a target value, in some embodiments to mean within ±10% of a target value, in some embodiments to mean within ±5% of a target value, and in some embodiments to mean within ±2% of a target value. The terms "approximately" and "about" may include the target value.

Claims

1. A method for suppressing electromagnetic interference (EMI) in magnetic resonance data (MR data) obtained by a magnetic resonance imaging system (MRI system), the method comprising: Use at least one computer hardware processor to: identifying a first subset of the MR data affected by EMI; Suppressing EMI in the first subset of the MR data to obtain a second subset of the MR data by: applying filtering to the first subset of the MR data to suppress contributions of MR spin echo signals in the first subset of the MR data, thereby obtaining signal-suppressed MR data; suppressing EMI in the signal-suppressed MR data to obtain EMI-suppressed MR data; as well as applying an inverse of the filtering to the EMI suppressed MR data to obtain the second subset of the MR data; generating an MR image using the second subset of the MR data; as well as The generated MR image is output.

2. The method according to claim 1, wherein: Suppressing EMI in the MR data through the signal includes: Using component decomposition to obtain the EMI suppressed MR data; or applying a domain transform to the signal suppressed MR data, Using component decomposition to obtain the EMI suppressed MR data; and The inverse of the domain transform is applied.

3. The method according to claim 2, wherein: The first subset of the MR data includes a plurality of data portions for a respective plurality of frequency or time intervals, and wherein suppressing EMI in the first subset of the MR data includes: For each specific data portion among the plurality of data portions, applying the filtering to the particular data portion to obtain a corresponding signal suppressed MR data portion; suppressing EMI in the corresponding signal-suppressed MR data portion to obtain a corresponding EMI-suppressed MR data portion; and The inverse of the filtering is applied to the EMI suppressed MR data portion.

4. The method according to claim 3, wherein: Suppressing EMI in the corresponding signal suppressed MR data portion includes: determining a component decomposition of the corresponding signal suppressed MR data portion; modifying the component decomposition by setting at least one component value of the component decomposition to a predetermined value or by multiplying at least one component value of the component decomposition by a predetermined weight; and The corresponding EMI-suppressed MR data portion is obtained using a modified component decomposition.

5. The method according to claim 4, in, The MRI system includes a plurality of radio frequency coils, i.e., a plurality of RF coils, and Wherein, each of the plurality of data portions comprises measurements made by each of the plurality of RF coils for a corresponding frequency or time interval of the plurality of frequency or time intervals.

6. The method according to claim 5, in, The data in the corresponding signal suppressed MR data portion is organized as N c ×M matrix, where N c is an integer representing the number of RF coils, and M represents one or more further dimensions of the number of measurements performed by each of said RF coils, and Wherein, determining the component decomposition of the corresponding signal suppressed MR data portion comprises: determining the N c Singular values ​​or higher-order singular value decomposition of a ×M matrix.

7. The method according to claim 1, further comprising: Prior to identifying the first subset of the MR data, the MR data is generated by operating the MRI system according to a spin echo pulse sequence or a gradient echo pulse sequence.

8. The method according to claim 7, further comprising: After generating the MR data and before identifying the first subset, EMI is suppressed in the MR data detected by an auxiliary coil of the MRI system.

9. The method according to claim 1, wherein: The EMI is narrowband EMI, and wherein the MR data includes sensor domain data in a plurality of frequency or time intervals, and wherein the EMI is present in a frequency or time interval of the plurality of frequency or time intervals.

10. The method according to claim 9, wherein: The EMI exists in no more than a threshold number of adjacent frequency or time intervals among the plurality of frequency or time intervals.

11. The method according to claim 9, wherein: The EMI is present in an nth frequency or time interval among the multiple frequency or time intervals, and wherein applying the filtering to the first subset of MR data includes: calculating a weighted linear combination of data in multiple frequency or time intervals including the nth frequency or time interval using weights determined by coefficients of the filtering.

12. The method according to claim 1, wherein: The MR data includes data in multiple frequency or time intervals, The EMI exists in multiple adjacent frequency or time intervals, and Applying the filter to the first subset of the MR data includes applying a convolution filter having a length at least equal to the number of adjacent frequency or time bins in the plurality of adjacent frequency or time bins.

13. The method according to claim 1, wherein: Identifying the first subset of the MR data comprises: Data in a single frequency or time interval or a set of adjacent frequency or time intervals of the MR data that are affected by EMI are identified.

14. The method according to claim 13, wherein: Identifying the first subset of the MR data is performed by: analyzing a portion of the MR data acquired during at least one predetermined echo signal of a pulse sequence used to acquire the MR data, or It is determined whether the data in the single frequency or time interval or in the set of adjacent frequency or time intervals has a magnitude greater than a threshold.

15. A magnetic resonance imaging system, i.e., an MRI system, comprising: a magnetic system having a plurality of magnetic components to generate a magnetic field for performing MRI by acquiring MR data; as well as at least one processor configured to: identifying a first subset of the MR data affected by electromagnetic interference (EMI); Suppressing EMI in the first subset of the MR data to obtain a second subset of the MR data by: applying filtering to the first subset of the MR data to suppress contributions of MR spin echo signals in the first subset of the MR data, thereby obtaining signal-suppressed MR data; suppressing EMI in the signal-suppressed MR data to obtain EMI-suppressed MR data; as well as applying an inverse of the filtering to the EMI suppressed MR data to obtain the second subset of the MR data; generating an MR image using the second subset of the MR data; as well as The generated MR image is output.

Images