Magnetic resonance imaging method and magnetic resonance imaging system

Abstract

The embodiment of the application provides a magnetic resonance imaging method and a magnetic resonance imaging system, the method comprising: acquiring first image data using a first scanning sequence; performing filtering processing on the first image data to obtain second image data; estimating a radio frequency field map according to the first image data and the second image data; acquiring scanning image data using a second scanning sequence; and correcting the scanning image data according to the estimated radio frequency field map to obtain corrected scanning image data.

Description

Technical Field

[0001] This application relates to the field of medical device technology, and in particular to a magnetic resonance imaging method and a magnetic resonance imaging system. Background Technology

[0002] In magnetic resonance imaging (MRI), the object under investigation is placed in the imaging space of a static magnetic field B0, causing the proton spins within the object to align with the direction of the static magnetic field, thereby generating a magnetization vector. Then, a high-frequency magnetic field is formed by transmitting a radio frequency pulse at the resonant frequency, causing the magnetic resonance phenomenon to occur. The magnetic resonance phenomenon causes the proton spin direction to flip, thus changing the proton magnetization vector. When the spin returns the protons to their initial magnetization vector state in the direction of the static magnetic field, a magnetic resonance signal is generated.

[0003] During magnetic resonance imaging, the radiofrequency field B1 becomes increasingly uneven with the increase of the static magnetic field strength and the increase of the patient's body size. Uneven distribution of B1 will produce dielectric artifacts in the image, resulting in uneven image, changes in tissue contrast, and even loss of signal, thus leading to a lack of sufficient image information to provide a reliable clinical diagnosis. Summary of the Invention

[0004] To address at least one of the above-mentioned problems, embodiments of this application provide a magnetic resonance imaging method and a magnetic resonance imaging system.

[0005] According to one aspect of the embodiments of this application, a magnetic resonance imaging method is provided, the method comprising:

[0006] First image data is acquired using a first scan sequence;

[0007] The first image data is filtered to obtain the second image data;

[0008] Estimate the radio frequency field map based on the first image data and the second image data;

[0009] The second scanning sequence is used to acquire scanned image data. Based on the estimated radio frequency field pattern, the scanned image data is corrected to obtain corrected scanned image data.

[0010] According to one aspect of the embodiments of this application, a magnetic resonance imaging system is provided, the system comprising:

[0011] Scanning unit;

[0012] A controller configured to perform the magnetic resonance imaging method described in the foregoing aspect.

[0013] One of the beneficial effects of the embodiments of this application is that: first image data is acquired using a first scanning sequence; the first image data is filtered to obtain second image data; a radio frequency field pattern is estimated based on the first image data and the second image data; and the scanned image data is corrected based on the estimated radio frequency field pattern. Therefore, dielectric artifacts in the image can be minimized, missing signals and contrast in the image can be compensated, the uniformity and consistency of the image can be improved, image quality can be enhanced, and the confidence of the diagnosis can be increased.

[0014] Referring to the following description and accompanying drawings, specific implementation methods of the embodiments of this application are disclosed in detail, indicating how the principles of the embodiments of this application can be adopted. It should be understood that the implementation methods of this application are not limited in scope. Within the spirit and scope of the appended claims, the implementation methods of this application include many changes, modifications, and equivalents. Attached Figure Description

[0015] The accompanying drawings, which form part of the specification, are used to provide a further understanding of the embodiments of this application and illustrate the implementation methods of this application, together with the textual description, to explain the principles of this application. Obviously, the drawings described below are merely some embodiments of this application, and those skilled in the art can obtain other implementation methods based on these drawings without creative effort. In the drawings:

[0016] Figure 1 This is a schematic diagram of a magnetic resonance imaging system according to an embodiment of this application;

[0017] Figure 2 This is a schematic diagram of a magnetic resonance imaging method according to an embodiment of this application;

[0018] Figure 3 This is a schematic diagram of operation 204 of the present application embodiment;

[0019] Figure 4 This is a schematic diagram of operation 303 in this application embodiment;

[0020] Figure 5 This is a schematic diagram of a magnetic resonance imaging method according to an embodiment of this application;

[0021] Figure 6 This is a schematic diagram of the second scanning sequence according to an embodiment of this application;

[0022] Figure 7 This is a schematic diagram of the image correction process according to an embodiment of this application;

[0023] Figure 8 This is a schematic diagram of the image correction process according to an embodiment of this application;

[0024] Figure 9 This is a schematic diagram of scanned image data according to an embodiment of this application;

[0025] Figure 10 This is a schematic diagram of the corrected scanned image data according to an embodiment of this application. Detailed Implementation

[0026] Referring to the accompanying drawings, the foregoing and other features of the embodiments of this application will become apparent from the following description. Specific embodiments of this application are specifically disclosed in the description and drawings, illustrating partial implementations in which the principles of the embodiments of this application can be adopted. It should be understood that this application is not limited to the described embodiments; rather, the embodiments of this application include all modifications, variations, and equivalents falling within the scope of the appended claims.

[0027] In the embodiments of this application, the terms "first," "second," etc., are used to distinguish different elements by name, but do not indicate the spatial arrangement or chronological order of these elements, and these elements should not be limited by these terms. The term "and / or" includes any one or more of the terms listed in association and all combinations thereof. The terms "comprising," "including," "having," etc., refer to the presence of the stated features, elements, components, or assemblies, but do not exclude the presence or addition of one or more other features, elements, components, or assemblies.

[0028] In the embodiments of this application, the singular forms "a," "the," etc., including the plural forms, should be broadly understood as "a kind" or "a class" rather than limited to the meaning of "an." Furthermore, the term "the" should be understood to include both the singular and plural forms, unless the context explicitly indicates otherwise. Additionally, the term "according to" should be understood as "at least partially based on…," and the term "based on" should be understood as "at least partially based on…," unless the context explicitly indicates otherwise.

[0029] Features described and / or illustrated for one embodiment may be used in the same or similar manner in one or more other embodiments, combined with features in other embodiments, or substituted for features in other embodiments. The term "comprising / including" as used herein means the presence of a feature, integral, step, or component, but does not exclude the presence or addition of one or more other features, integrals, steps, or components.

[0030] For ease of understanding, Figure 1 A magnetic resonance imaging (MRI) system 100 according to some embodiments of the present invention is shown.

[0031] The MRI system 100 includes a scanning unit 111. The scanning unit 111 is used to perform magnetic resonance scanning on an object (e.g., a human body) 170 to generate image data of a region of interest of the object 170, which may be a predetermined anatomical location or anatomical tissue.

[0032] The operation of the MRI system 100 is controlled by an operator workstation 110, which includes an input device 114, a control panel 116, and a display 118. The input device 114 may be a joystick, keyboard, mouse, trackball, touch-activated screen, voice control, or any similar or equivalent input device. The control panel 116 may include a keyboard, touch-activated screen, voice control, buttons, sliders, or any similar or equivalent control device. The operator workstation 110 is coupled to and communicates with a computer system 120, which enables the operator to control the generation and viewing of images on the display 118. The computer system 120 includes multiple components that communicate with each other via an electrical and / or data connection module 122. The connection module 122 may be a direct wired connection, a fiber optic connection, a wireless communication link, etc. The computer system 120 may include a central processing unit (CPU) 124, a memory 126, and an image processor 128. In some embodiments, the image processor 128 may be replaced by image processing functions implemented in the CPU 124. Computer system 120 can be connected to archival media devices, permanent or backup storage, or a network. Computer system 120 can be coupled to and communicate with a separate MRI system controller 130.

[0033] The MRI system controller 130 includes a set of components that communicate with each other via an electrical and / or data connection module 132. The connection module 132 can be a direct wired connection, a fiber optic connection, a wireless communication link, etc. The MRI system controller 130 may include a CPU 131, a sequence pulse generator 133 communicating with an operator workstation 110, a transceiver (or RF transceiver) 135, a memory 137, and an array processor 139. In some embodiments, the sequence pulse generator 133 may be integrated into the resonant assembly 140 of the scanning unit 111 of the MRI system 100. The MRI system controller 130 may receive commands from the operator workstation 110, coupled to the scanning unit 111, to instruct the MRI scan sequence to be performed during an MRI scan, for controlling the scanning unit 111 to perform the aforementioned magnetic resonance scan procedure. The MRI system controller 130 is also coupled to and communicates with a gradient driver system 150, which is coupled to a gradient coil assembly 142 to generate a magnetic field gradient during an MRI scan.

[0034] The sequence pulse generator 133 may also receive data from a physiological acquisition controller 155, which receives signals from multiple different sensors, such as electrocardiogram (ECG) signals from electrodes attached to the patient, connected to the subject or patient 170 undergoing an MRI scan. The sequence pulse generator 133 is coupled to and communicates with a scan room interface system 145, which receives signals from various sensors associated with the state of the resonant assembly 140. The scan room interface system 145 is also coupled to and communicates with a patient positioning system 147, which sends and receives signals to control the movement of the patient table to the desired position for the MRI scan.

[0035] MRI system controller 130 provides gradient waveforms to gradient driver system 150, the gradient driver system including G x (x direction), G y (y-direction) and G z (z-direction) amplifiers, etc. Each G x G y and G z Gradient amplifiers excite corresponding gradient coils in gradient coil assembly 142 to generate magnetic field gradients for spatial encoding of MR signals during MRI scans. Gradient coil assembly 142 is disposed within resonant assembly 140, which also includes a superconducting magnet with a superconducting coil 144 that provides a static, uniform longitudinal magnetic field B0 throughout the cylindrical imaging volume 146 during operation. Resonant assembly 140 also includes an RF body coil 148 that provides a transverse magnetic field B1 during operation, which is substantially perpendicular to B0 throughout the cylindrical imaging volume 146. Resonant assembly 140 may also include an RF surface coil 149 for imaging different anatomical structures of a patient undergoing an MRI scan. RF body coil 148 and RF surface coil 149 may be configured to operate in transmit and receive modes, transmit mode, or receive mode.

[0036] The x-direction can also be called the frequency coding direction or k in the K-space. x The direction, the y-direction, can be called the phase encoding direction or k in K-space. y Direction. G x It can be used for frequency coding or signal readout, and is often referred to as the frequency coding gradient or readout gradient. G y It can be used for phase coding, and is often referred to as the phase coding gradient. G z It can be used for slice (layer) location selection to obtain K-space data. It should be noted that the layer selection direction, phase encoding direction, and frequency encoding direction can be modified according to actual needs.

[0037] The MRI scan subject or patient 170 can be positioned within the cylindrical imaging volume 146 of the resonance assembly 140. The transceiver 135 in the MRI system controller 130 generates RF excitation pulses amplified by the RF amplifier 162 and provides them to the RF body coil 148 via the transmit / receive switch (T / R switch) 164.

[0038] As described above, the RF body coil 148 and RF surface coil 149 can be used to transmit RF excitation pulses and / or receive resulting MR signals from a patient undergoing an MRI scan. MR signals emitted by nuclei excited within the patient during an MRI scan can be sensed and received by the RF body coil 148 or RF surface coil 149 and transmitted back to the preamplifier 166 via a T / R switch 164. The T / R switch 164 can be controlled by a signal from the sequence pulse generator 133 to electrically connect the RF amplifier 162 to the RF body coil 148 during transmit mode and to connect the preamplifier 166 to the RF body coil 148 during receive mode. The T / R switch 164 can also enable the RF surface coil 149 to be used in either transmit or receive mode.

[0039] In some implementations, the MR signal sensed and received by the RF body coil 148 or the RF surface coil 149 and amplified by the preamplifier 166 is stored as a raw k-space data array in memory 137 for post-processing. A reconstructed magnetic resonance image can be obtained by transforming / processing this stored raw k-space data.

[0040] In some implementations, the MR signal sensed and received by the RF body coil 148 or RF surface coil 149 and amplified by the preamplifier 166 is demodulated, filtered, and digitized in the receiving section of the transceiver 135 and transmitted to the memory 137 in the MRI system controller 130. For each image to be reconstructed, the data is rearranged into separate k-space data arrays, and each of these separate k-space data arrays is input to the array processor 139, which is operated to perform a Fourier transform on the data into an array of image data.

[0041] The array processor 139 uses a transformation method, most commonly Fourier transform, to create an image from the received MR signal. These images are transmitted to the computer system 120 and stored in the memory 126. In response to a command received from the operator workstation 110, the image data may be stored in long-term memory, or it may be further processed by the image processor 128 and transmitted to the operator workstation 110 for display on the monitor 118.

[0042] In various implementations, components of the computer system 120 and the MRI system controller 130 may be implemented on the same computer system or multiple computer systems. It should be understood that... Figure 10 The MRI system 100 shown is for illustrative purposes. Suitable MRI systems may include more, fewer, and / or different components.

[0043] The MRI system controller 130 and image processor 128 may each include a computer processor and a storage medium, either individually or jointly. The storage medium records a program for predetermined data processing to be executed by the computer processor. For example, the storage medium may store programs for performing scan processing (e.g., scan procedures, imaging sequences), image reconstruction, image processing, etc. For instance, it may store programs for implementing the magnetic resonance imaging method of the embodiments of the present invention. The storage medium may include, for example, a ROM, floppy disk, hard disk, optical disk, magneto-optical disk, CD-ROM, or a non-volatile memory card.

[0044] The aforementioned "imaging sequence" (hereinafter also referred to as a scan sequence or pulse sequence) refers to a combination of pulses with specific amplitude, width, direction, and timing applied during magnetic resonance imaging (MRI) scanning. These pulses typically include, for example, radio frequency (RF) pulses and gradient pulses. The RF pulses may include, for example, RF excitation pulses, RF refocusing pulses, inversion recovery pulses, etc. The gradient pulses may include, for example, the gradient pulses used for slice selection, gradient pulses used for phase encoding, gradient pulses used for frequency encoding, gradient pulses used for phase shifting (phase shifting), gradient pulses used for discrete phase (associated phase), etc.

[0045] Typically, multiple scanning sequences can be pre-set in a magnetic resonance imaging system to allow selection of sequences that meet clinical testing needs, such as imaging sites, imaging functions, and imaging effects.

[0046] Currently, a relatively simple method to reduce dielectric artifacts involves placing a dielectric pad between the area to be inspected and the receiving coil. The displacement current in the dielectric pad can generate a local radio frequency field to enhance the B1 field. At the same time, the dielectric pad can make the shape of the imaging area closer to a sphere, thereby reducing the radio frequency inhomogeneity inherent in elliptical shapes. However, the effectiveness of such physical methods is quite limited.

[0047] In the field of algorithms, methods to mitigate dielectric artifacts include image-based post-processing filtering, such as surface coil strength correction, nonparametric, non-uniformity pre-normalization (N3), and improved N3 bias correction (N4). However, these filtering methods cannot be used for quantitative data analysis, such as signal-to-noise ratio measurements. To address this issue, some correction methods based on pre-scanned image data have been proposed, which correct non-uniform receiving coils before actual imaging by obtaining low-resolution corrected scan images. However, these methods cannot compensate for the non-uniformity of the RF field B1, which leads to spatial variations in the flip angle.

[0048] To address the inhomogeneity of the radiofrequency field B1, numerous radiofrequency shimming methods have been proposed, such as redesigning the radiofrequency pulse, coil, and power to equalize the distribution of the radiofrequency flip angle. However, applying these methods may require modifications to the current scanning workflow. Therefore, a method for pre-defining the radiofrequency field B1 has been proposed. This involves obtaining the radiofrequency field through offline simulation of the body coil and pre-storing it in the MRI system, using this pre-defined radiofrequency field to correct the image. However, due to the complex interactions between the patient, coil, and magnetic field, it is difficult to accurately simulate the B1 field when the patient is inside the scanning cavity at higher field strengths (e.g., above 1.5T).

[0049] To address at least one of the aforementioned problems, this application proposes a method for estimating the B1 field (B1map) when the patient is located within the scanning cavity using pre-scanned image data, and then correcting the image data using the estimated B1 field. This method can minimize dielectric artifacts, compensate for missing signals and contrast in the image, improve image uniformity and consistency, enhance image quality, and increase diagnostic confidence.

[0050] The following description is based on specific examples.

[0051] This application provides a magnetic resonance imaging method. Figure 2 This is a schematic diagram of a magnetic resonance imaging method according to an embodiment of this application, as shown below. Figure 2 As shown, the method includes:

[0052] 201. Acquire first image data using the first scan sequence;

[0053] 202. Filter the first image data to obtain the second image data;

[0054] 203. Estimate the radio frequency field map based on the first image data and the second image data;

[0055] 204. Use the second scanning sequence to acquire scanned image data, and correct the scanned image data according to the estimated radio frequency field pattern to obtain corrected scanned image data.

[0056] In some embodiments, a pre-scan (or reference scan) needs to be performed before the formal diagnostic scan. During the pre-scan, the subject enters the scanning chamber, scan parameters are set, a scan sequence for the pre-scan is transmitted, shimming data is determined, and system settings are optimized (e.g., center frequency correction, determining transmit gain, receive gain, and phase calibration). For example, in 201, during this pre-scan, a first scan sequence can be used to scan the subject, a first coil can be used to receive magnetic resonance signals, and first image data can be acquired based on these signals. The first image data acquired using the body coil can be low-resolution image data, and more specifically, a low-resolution proton density-weighted image, which is generally considered relatively uniform. This example only uses a body coil, but the embodiments of this application are not intended to limit the scope; other types of coils that obtain relatively uniform low-resolution proton density-weighted images are also applicable to this application.

[0057] In some embodiments, the first image data may be, for example, image data with a resolution of 64×64. This is merely an example and is not intended to limit the scope of this application. In some embodiments, the first scanning sequence may include a spoiled gradient recalled echo (SPGR) sequence, which is a combination of frequency pulses that apply a phase disturbance to the gradient echo sequence. The principle is to interfere with the phase of the proton group in the tissue after the previous magnetic resonance signal acquisition and before the next radio frequency excitation pulse, thereby accelerating the phase loss and eliminating the residual transverse magnetization vector. The first image data acquired based on the first scanning sequence can be expressed by the following formula (1):

[0058]

[0059] Among them, echo time The repetition time TR = 1.5 ms << T1, and the actual transverse relaxation time is... The longitudinal relaxation time is T1, the flip angle α = 1°, cosα ≈ 1, M0 represents the macroscopic magnetization vector, and ρ represents the proton density, which is positively correlated with M0. Since the perturbed gradient echo sequence can obtain a proton density-weighted image in a short time, relatively uniform first image data can be obtained by using the perturbed gradient echo sequence. However, this embodiment is not limited to this; other sequences that can quickly obtain a proton density-weighted image are also applicable to this application, and will not be exemplified here.

[0060] In some embodiments, the first image data can be approximated as: For the radio frequency transmission field of the first coil, For the radio frequency receiving field of the first coil, Indicates spatial location. In this embodiment, the radio frequency field of the first coil is defined as... In step 202, the first image data is subjected to homomorphic filtering to obtain the second image data. This second image data can be approximated as follows: This homomorphic filtering process can improve the uniformity of the first image data. This homomorphic filtering process is merely an example of one filtering method, and the embodiments of this application are not intended to limit it; other filtering methods may also be applicable. The same treatment applies to this application.

[0061] In some embodiments, at 203, a radio frequency field map can be estimated based on the first image data and the second image data. The radio frequency field map can be determined based on the ratio of the first image data to the second image data. A field diagram can be viewed as the spatial signal distribution caused by the field strength distribution of a radio frequency (RF) field. For example, an RF field diagram. The radio frequency field map can be estimated using the following formula (2), which is equal to the arithmetic square root of the ratio of the first image data to the second image data.

[0062]

[0063] As can be seen from the above embodiments, in the pre-scan, the radio frequency field pattern of the first coil can be estimated based on the first scan sequence and the first image data acquired by the first coil.

[0064] In some embodiments, at 204, a formal scan is performed. The subject can be scanned using a second scanning sequence, and a second coil is used to receive magnetic resonance signals. The scanned image data is acquired based on the magnetic resonance signals. The second coil includes surface coils (or local coils, specifically determined by the imaging region). The scanned image data is higher resolution image data relative to the first image data, for example, 512×512 resolution image data. This is merely an example, and the embodiments of this application are not intended to be limiting.

[0065] In some embodiments, the second scan sequence includes a spin echo sequence. Figure 6This is a schematic diagram of the second scanning sequence according to an embodiment of this application. Within a repetition time, multiple radio frequency refocusing pulses (e.g., 180°) are applied after a radio frequency excitation pulse (e.g., 90°), and multiple echoes are acquired. These echoes are filled into multiple phase encoding lines in K-space to obtain scanned image data. Spin echoes typically utilize radio frequency refocusing pulses to refocus the phase of the proton group, gradually increasing the transverse magnetization vector so that echoes can be acquired after the radio frequency refocusing pulse ends. Scanning sequences using spin echo methods include, but are not limited to, spin echo sequences (SE), fast spin echo sequences (FSE), and single-excitation (SS) FSE, etc., which will not be exemplified here.

[0066] The following explains how to use RF field maps The scanned image data was corrected.

[0067] Figure 3 This is a schematic diagram of operation 204 of the embodiment of this application, as shown below. Figure 3 As shown, operation 204 includes:

[0068] 301, Use the first scan sequence to acquire the third image data;

[0069] 302, Determine the correction factor based on the third image data;

[0070] 303, Update the correction factor based on the estimated radio frequency field map;

[0071] 304. The scanned image data is corrected according to the correction factor to obtain the corrected scanned image data.

[0072] In some embodiments, 301 can also be performed during pre-scanning. That is, during pre-scanning, the subject can be scanned using a first scanning sequence. As mentioned above, a first coil is used to acquire first image data, and a second coil is used to receive magnetic resonance signals, from which third image data is acquired. In this embodiment, the order of acquiring the first and third image data is not limited. For example, the first coil can be used to acquire the first image data first, and then the second coil can be used to acquire the third image data, or the second coil can be used to acquire the third image data first, and then the first coil can be used to acquire the first image data, or the third and first image data can be acquired simultaneously. These are not all exemplified here. In addition, a switch is required between the first and second coils to receive the magnetic resonance signal, or a switch may not be required to receive the magnetic resonance signal. This embodiment does not limit this. The implementation of the second coil is as described above, that is, the second coil is used to obtain the third image data and the formal scan image data. The third image data acquired using the second coil can reflect the receiving sensitivity of the second coil. The third image data can be low-resolution image data, and further, it can be a low-resolution proton density-weighted image. For example, the third image data is an image with the same resolution as the first image data. That is, during the pre-scanning process, using the same first scan sequence but different receiving coils, the first image data and the third image data can be acquired separately. This third image data can be represented as...

[0073] In some embodiments, at 302, a correction factor can be determined based on the third image data and the first image data. For example, the initial correction factor P can be equal to the ratio of the first image data to the third image data, i.e. Alternatively, the correction factor can be determined based on the third image data and the second image data. For example, the initial correction factor P can be equal to the ratio of the second image data to the third image data, i.e.

[0074] Figure 4 This is a schematic diagram of implementation method 303 in this application, as shown below. Figure 4 As shown, operation 303 includes:

[0075] 401, Determine the center angle;

[0076] 402, Convert the radio frequency field map into an angle map based on the center angle;

[0077] 403. Update the correction factor based on the trigonometric function values ​​of the angle diagram and the radio frequency field diagram.

[0078] In some embodiments, at 401, the center angle may be determined based on the flip angle of the radio frequency transmission pulses in the second scan sequence. For example, the center angle is equal to the flip angle of the radio frequency transmission pulses in the second scan sequence. For example, if the magnetic resonance image is obtained by performing an FSE sequence, and the flip angle is set to 90 degrees when the sequence is performed, then the center angle is determined to be 90 degrees.

[0079] In some embodiments, in 402, the radio frequency field map is... Convert to an angle diagram θ. For example, convert the radio frequency field diagram. After normalization, we get B. map For example, to To achieve normalization, x is the value at which the excitation reaches a 90° flip at the center angle. The value of x can be an empirical value, which can be preset by the magnetic resonance system after verification from multiple aspects. For example, the range of x can be 1.05 to 1.55, but this embodiment does not limit it. The values ​​at each position on the normalized graph are multiplied... (90°), which gives the corresponding angle diagram θ.

[0080] In some embodiments, shading signals The effect on image signals typically follows a trigonometric function relationship. This trigonometric function can be of any form, such as sine, cosine, tangent, etc., which will not be listed here. Artifact signals It will be affected by the PSD of the scan sequence used (such as repetition time, flip angle, echo time, etc.) and the radio frequency transmission field. The sensitivity of an image is affected by imaging tissue parameters (e.g., longitudinal relaxation time T1, transverse relaxation time T2). Therefore, artifact signals... Under a preset scanning sequence, the function with the subject (different tissues have different longitudinal relaxation times T1 and lateral relaxation times T2) and the flip angle as variables can be regarded as the spatial signal distribution value caused by the field strength distribution of the radio frequency emission field.

[0081] For example, the artifact signal can be estimated using the following formula (3).

[0082]

[0083] Where θ is the angle value in the angle diagram, f(θ) can be a sine function value, C1~C nThe weight parameter is greater than 0 and can be any value between 0 and 1, or a value greater than or equal to 1. n is the number of times the trigonometric function value is adjusted based on the weight parameter; n is greater than 0 and can be an integer or a decimal. For example, n can be 1 or 2, or a number between 0 and 2. The aforementioned weight parameter can be an empirical value, which is then incorporated into the magnetic resonance imaging system after verification from multiple aspects. For example, in one example, substituting a suitable empirical value into formula (3) yields... This is merely an example, and the embodiments in this application are not intended to be limiting. As mentioned above, radio frequency field patterns After normalization, we get B. map The value of power is related to the second scan sequence and can also be adjusted empirically, predetermined by the magnetic resonance system. For example, when the excitation pulse is 90° and the refocusing pulse is 180°, power = 3. This is merely an example, and the embodiments of this application are not intended to limit it. When determining B... map After powering, the artifact signal can be obtained. Artifact signal That is, it can be used as the trigonometric function value of that angle diagram.

[0084] In some embodiments, in 403, the correction factor P is based on When determined, updating the correction factor based on the trigonometric function values ​​of the angle diagram and the radio frequency field diagram includes: dividing the correction factor by the trigonometric function values ​​and the radio frequency field diagram to obtain the updated correction factor. For example, the updated correction factor P' can be obtained by the following formula (4):

[0085]

[0086] In some embodiments, in 403, the correction factor P is based on When determined, updating the correction factor based on the trigonometric function values ​​of the angle diagram and the radio frequency field diagram includes: dividing the correction factor by the trigonometric function values ​​and then multiplying it by the radio frequency field diagram to obtain the updated correction factor. For example, the updated correction factor P' can be obtained by the following formula (5):

[0087]

[0088] In some embodiments, for the updated correction factor P', since it is calculated from low-resolution image data, in order to correct the high-resolution image data (scanned image data), P' can be further reformatted. In step 304, the reformatted correction factor P' is multiplied by the scanned image data to correct the scanned image data, thereby obtaining the corrected scanned image data.

[0089] In some embodiments, if the next subject is scanned, the imaging method described above will be repeated.

[0090] The principle of using the formulas (1)-(5) above to correct scanned image data is explained below.

[0091] This application embodiment addresses scanned image data. By performing correction and combining it with the following formula (6), the first corrected image can be obtained.

[0092]

[0093] If the correction is performed using the principle of formula (6), then the initial correction factor is determined based on the ratio of the first image data to the third image data. If it can be estimated Then divide the acquired image data by... This allows the removal of redundant signals to obtain the ideal signal, thus completing the correction. Specifically, the previously estimated artifact signals can be eliminated. With radio frequency field diagram The product is considered as

[0094] In some embodiments, the second corrected image can also be obtained by combining the following formula (7).

[0095] If the correction is performed using the principle of formula (7), then the initial correction factor is determined based on the ratio of the second image data to the third image data. If it can be estimated Then divide the acquired image data by... This allows the removal of redundant signals to obtain the ideal signal, thus completing the correction. Specifically, the previously estimated artifact signals can be eliminated. With radio frequency field diagram The ratio is considered as

[0096] By combining the above formulas Figure 7 and Figure 8 Assuming the artifact signals of the second coil are consistent during pre-scan and formal scan, by calculation The non-uniform radio frequency receiving field of the second coil (surface coil) in the scanned image data can be detected. eliminate. Figure 9 This is a schematic diagram of a scanned image obtained using traditional imaging methods. Figure 10 This is a schematic diagram of a corrected scan image obtained using the magnetic resonance imaging method according to an embodiment of this application, as shown below. Figure 9 and10 As shown, the above method can minimize dielectric artifacts in the image, compensate for missing signals and contrast, and improve the uniformity and consistency of the image.

[0097] Figure 5 This is a flowchart of a magnetic resonance imaging method according to an embodiment of this application, as follows: Figure 5 As shown, the method includes:

[0098] 501, Perform a pre-scan, acquire first image data using a first scan sequence and a first coil, and acquire third image data using a first scan sequence and a second coil;

[0099] 502, Perform homomorphic filtering on the first image data to obtain the second image data;

[0100] 503, Estimate the radio frequency field map based on the first image data and the second image data;

[0101] 504, Determine the correction factor based on the third image data;

[0102] 505, Perform the formal scan, using the second scan sequence and the second coil to acquire scan image data;

[0103] 506, Update the correction factor based on the RF field diagram;

[0104] 507. Correct the scanned image data according to the updated correction factor to obtain the corrected scanned image data.

[0105] The specific implementation methods for 501-507 have been described above and will not be repeated here.

[0106] It should be noted that the radio frequency field map in embodiment 503 of this application may not be estimated based on the first image data and the second image data. Instead, it may be obtained by simulating the receiving coil or by using a B1map fast acquisition sequence scan using a pre-designed scanning sequence, and stored in the magnetic resonance system in advance. For specific simulation methods, please refer to relevant technologies. This application embodiment is not intended to limit the scope of the application.

[0107] Furthermore, the above uses formula (2) as an example to illustrate how to estimate the radio frequency field map based on the first image data and the second image data. However, the embodiments of this application are not intended to limit the scope of the invention. For example, the first corrected image can also be obtained by combining the first image data, the third image data, and the scanned image data with formula (6). The second corrected image is obtained by combining the second image data, the third image data, and the scanned image data with formula (7). And estimate the radio frequency field pattern according to formula (8). The embodiments described in this application are not intended to be limiting.

[0108]

[0109] It should be noted that the above image data (e.g., the first image data and the third image data) can be the original image data or the image data after preprocessing. Such preprocessing includes, but is not limited to, normalization, low-pass filtering, and regularization. The embodiments of this application are not intended to limit this.

[0110] It is worth noting that the above figures are merely illustrative of embodiments of this application, and the application is not limited thereto. For example, the execution order between various operations can be appropriately adjusted, and other operations can be added or some operations can be removed. Those skilled in the art can make appropriate modifications based on the above description, and are not limited to the description in the above figures.

[0111] The above embodiments are merely illustrative examples of embodiments of this application, but this application is not limited thereto, and appropriate modifications can be made based on the above embodiments. For example, the above embodiments can be used alone, or one or more of the above embodiments can be combined.

[0112] Through the above embodiments, a first image data is acquired using a first scanning sequence; the first image data is filtered to obtain second image data; a radio frequency field pattern is estimated based on the first image data and the second image data; and the scanned image data is corrected based on the estimated radio frequency field pattern. This approach can minimize dielectric artifacts in the image, compensate for missing signals and contrast, improve image uniformity and consistency, enhance image quality, and increase diagnostic confidence.

[0113] This application also provides a method for determining a radio frequency (RF) field map. The method includes: acquiring first image data using a first scanning sequence; filtering the first image data to obtain second image data; and estimating the RF field map based on the first image data and the second image data. The implementation of this method can be referred to the foregoing embodiments, and will not be repeated here. The estimated RF field map can be used not only for correcting scanned image data but also for other scenarios, and this application does not limit it to these applications.

[0114] This application also provides a magnetic resonance imaging system. The configuration of this magnetic resonance imaging system is as follows: Figure 1 As shown, the repeated parts will not be repeated.

[0115] In some embodiments, with Figure 1The difference between the aforementioned magnetic resonance imaging system and the controller 130 is that the controller 130 is configured to perform the aforementioned magnetic resonance imaging method.

[0116] In some embodiments, the controller 130 (which may also be a processor) includes a computer processor and a storage medium on which a program for predetermined data processing to be executed by the computer processor is recorded. For example, the storage medium may store programs for performing scanning processing (e.g., waveform design / conversion, etc.), image reconstruction, image processing, etc. For example, it may store a radio frequency field pattern determination method for implementing the embodiments of this application, the specific implementation of which is as described above and will not be repeated here.

[0117] The aforementioned storage media may include, for example, ROM, floppy disk, hard disk, optical disk, magneto-optical disk, CD-ROM, or non-volatile memory card.

[0118] This application also provides a computer-readable program, wherein when the program is executed in a device or MRI system, the program causes the computer to perform the methods described in the foregoing embodiments in the device or MRI system.

[0119] This application also provides a storage medium storing a computer-readable program, wherein the computer-readable program causes a computer to perform the methods described in the foregoing embodiments in a device or MRI system.

[0120] The apparatus and methods described above in this application can be implemented in hardware or in combination with software. This application relates to a computer-readable program that, when executed by a logic component, enables the logic component to implement the apparatus or components described above, or to implement the various methods or steps described above. This application also relates to storage media for storing the above programs, such as hard disks, magnetic disks, optical disks, DVDs, flash memory, etc.

[0121] The methods / apparatus described in conjunction with the embodiments of this application can be directly embodied in hardware, software modules executed by a processor, or a combination of both. For example, one or more and / or combinations of one or more functional block diagrams shown in the figures can correspond to various software modules in a computer program flow, or to various hardware modules. These software modules can correspond to the various steps shown in the figures, respectively. These hardware modules can be implemented, for example, using a field-programmable gate array (FPGA) to embed these software modules.

[0122] The software module can reside in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, hard disk, removable disk, CD-ROM, or any other form of storage medium known in the art. A storage medium can be coupled to the processor, enabling the processor to read information from and write information to the storage medium; or the storage medium can be an integral part of the processor. The processor and storage medium can reside in an ASIC. The software module can be stored in the memory of a mobile terminal or in a memory card that can be inserted into the mobile terminal. For example, if the device (such as a mobile terminal) uses a high-capacity MEGA-SIM card or a high-capacity flash memory device, the software module can be stored in the MEGA-SIM card or the high-capacity flash memory device.

[0123] One or more and / or one or more combinations of functional blocks described in the accompanying drawings can be implemented as a general-purpose processor, digital signal processor (DSP), application-specific integrated circuit (ASIC), field-programmable gate array (FPGA), or other programmable logic device, discrete gate or transistor logic device, discrete hardware component, or any suitable combination thereof for performing the functions described herein. One or more and / or one or more combinations of functional blocks described in the accompanying drawings can also be implemented as a combination of computing devices, such as a combination of a DSP and a microprocessor, multiple microprocessors, one or more microprocessors in communication with a DSP, or any other such configuration.

[0124] The present application has been described above with reference to specific embodiments. However, those skilled in the art should understand that these descriptions are exemplary and not intended to limit the scope of protection of the present application. Those skilled in the art can make various modifications and variations to the present application based on the principles thereof, and these modifications and variations are also within the scope of the present application.

Claims

1. A magnetic resonance imaging method, characterized in that, The method includes: First image data is acquired using a first scan sequence; The first image data is filtered to obtain the second image data; Estimate the radio frequency field map based on the first image data and the second image data; The second scanning sequence is used to acquire scanned image data. Based on the estimated radio frequency field pattern, the scanned image data is corrected to obtain corrected scanned image data.

2. The method according to claim 1, wherein, The first scanning sequence includes a scrambled gradient echo sequence, and the second scanning sequence includes a spin echo sequence.

3. The method according to claim 1, wherein, The filtering process includes homomorphic filtering.

4. The method according to claim 1, wherein, Estimating the radio frequency field map based on the first image data and the second image data includes: determining the radio frequency field map based on the ratio of the first image data and the second image data.

5. The method according to claim 4, wherein, The radio frequency field map is determined based on the square root of the ratio of the first image data to the second image data.

6. The method according to claim 1, wherein, Based on the estimated radio frequency field pattern, the scanned image data is corrected to obtain corrected scanned image data, including: Use the first scan sequence to acquire third image data; The correction factor is determined based on the third image data; The correction factor is updated based on the estimated radio frequency field map; The scanned image data is corrected according to the correction factor to obtain the corrected scanned image data.

7. The method according to claim 6, wherein, The first image data is acquired using a first coil, and the third image data and the scanned image data are acquired using a second coil.

8. The method according to claim 7, wherein, The first coil includes a body coil, and the second coil includes a surface coil.

9. The method according to claim 6, wherein, Updating the correction factor based on the estimated radio frequency field map includes: Determine the center angle; The radio frequency field map is converted into an angle map based on the center angle. The correction factor is updated based on the trigonometric function values ​​of the angle diagram and the radio frequency field diagram.

10. The method according to claim 9, wherein, Updating the correction factor based on the trigonometric function values ​​of the angle diagram and the radio frequency field diagram includes: dividing the correction factor by the trigonometric function values ​​and the radio frequency field diagram to obtain the updated correction factor, or dividing the correction factor by the trigonometric function values ​​and then multiplying it by the radio frequency field diagram to obtain the updated correction factor.

11. The method according to claim 6, wherein, The first image data and the third image data are low-resolution proton density-weighted image data.

12. The method according to claim 6, wherein, Determining the correction factor based on the third image data includes: The correction factor is determined based on the third image data and the first image data; or... The correction factor is determined based on the third image data and the second image data.

13. The method according to claim 12, wherein, Determining the correction factor based on the third image data and the first image data includes: determining the correction factor based on the ratio of the first image data to the third image data; Determining the correction factor based on the third image data and the second image data includes: determining the correction factor based on the ratio of the second image data to the third image data.

14. The method according to claim 12, wherein, When determining the correction factor based on the ratio of the first image data and the third image data, the correction factor is divided by the trigonometric function value and the radio frequency field map to obtain an updated correction factor; when determining the correction factor based on the ratio of the second image data and the third image data, the correction factor is divided by the trigonometric function value and then multiplied by the radio frequency field map to obtain an updated correction factor.

15. The method of claim 1, comprising: Perform a pre-scan, wherein the first image data is acquired using the first scan sequence; as well as, Perform a formal scan, in which the scanned image data is acquired using the second scan sequence.

16. The method of claim 6, comprising: Perform a pre-scan, wherein the first image data and the third image data are acquired using the first scan sequence; as well as, Perform a formal scan, in which the scanned image data is acquired using the second scan sequence.

17. A magnetic resonance imaging system, characterized in that, The system includes: Scanning unit; A controller configured to perform the magnetic resonance imaging method according to any one of claims 1 to 16.

Images