Echo time calculation method and device, storage medium and magnetic resonance imaging system

Abstract

The invention relates to an echo time calculation method and device, a storage medium and a magnetic resonance imaging system, and the method comprises the steps: obtaining the signal amplitude of an echo signal; fitting the echo signal through an amplitude fitting function by taking the signal amplitude as a reference to obtain a parameter group in the amplitude fitting function; the amplitude fitting function comprises a time variable and a parameter group; according to the method, the second parameter in the parameter set is extracted as the target echo time, the signal amplitude in the echo signal can be used as the reference, the amplitude fitting function is optimized to obtain the parameter set, and therefore the accurate target echo time is obtained, and the problem that the echo time cannot be accurately calculated is solved.

Description

Technical Field

[0001] The present application relates to the field of magnetic resonance imaging technology, and in particular to an echo time calculation method, device, storage medium and magnetic resonance imaging system. Background Art

[0002] The basic principle of magnetic resonance imaging is to generate a macroscopic magnetization vector in the protons of the object under test by applying an external magnetic field, and to stimulate the macroscopic magnetization vector to precess around the magnetic field by applying a radio frequency pulse sequence, thereby generating a magnetic resonance signal. After collecting the magnetic resonance signal, the magnetic resonance signal is reconstructed through spatial phase encoding technology to obtain a tissue image of the object under test, forming a magnetic resonance image.

[0003] The echo time in magnetic resonance imaging refers to the time interval from the midpoint of the pulse that generates the macroscopic transverse magnetization vector to the midpoint of the echo, which is of great significance in magnetic resonance imaging. For example, the accurate calculation of the echo time is conducive to quantitative imaging and diffusion imaging. However, due to factors such as instrument accuracy, measurement errors, tissue characteristics of the object being measured, and external interference, the echo signal is often mixed with a lot of noise, which affects the calculation of the echo time and makes it impossible to obtain an accurate echo time.

[0004] With regard to the problem in related technologies that the echo time cannot be accurately calculated, no effective solution has been proposed so far. Summary of the invention

[0005] Based on this, it is necessary to provide an echo time calculation method, device, storage medium and magnetic resonance imaging system that can solve the problem that the echo time cannot be accurately calculated in the related art in order to solve the above technical problems.

[0006] In a first aspect, an echo time calculation method is provided in this embodiment, comprising:

[0007] Obtaining the signal amplitude of the echo signal;

[0008] The echo signal is fitted by an amplitude fitting function based on the signal amplitude to obtain a parameter group in the amplitude fitting function; the amplitude fitting function includes a time variable and the parameter group;

[0009] A second parameter in the parameter group is extracted as a target echo time.

[0010] In some of the embodiments, it also includes:

[0011] generating the echo signal by using an echo sequence;

[0012] The echo sequence includes a gradient echo sequence or a spin echo sequence.

[0013] In some of the embodiments, it also includes:

[0014] Based on the parameter group and the time variable, the amplitude fitting function is established using Gaussian distribution.

[0015] In some embodiments, the amplitude fitting function is:

[0016]

[0017] Among them, S 0 represents the fitting amplitude in the echo signal; t represents the fitting amplitude S 0 The corresponding time variable; [k 1 ,k 2 ,k 3 ] represents the parameter group to be solved, k 1 represents the first parameter, k 2 represents the second parameter, k 3 Represents the third parameter.

[0018] In some embodiments, the step of fitting the echo signal by an amplitude fitting function based on the signal amplitude to obtain a parameter group in the amplitude fitting function includes:

[0019] Establishing an error model based on the amplitude fitting function;

[0020] According to the error model and the signal amplitude, the parameter group in the amplitude fitting function is optimized to obtain a fitting result.

[0021] In some of the embodiments, optimizing the parameter group in the amplitude fitting function according to the error model and the signal amplitude to obtain the fitting result includes:

[0022] The parameter group is iteratively updated through a nonlinear least squares algorithm to generate the fitting result.

[0023] In some of these embodiments, the nonlinear least squares algorithm is a Levenberg-Marquardt algorithm.

[0024] In a second aspect, a magnetic resonance imaging system is provided in this embodiment, comprising:

[0025] A magnetic resonance scanning device for applying an echo sequence to form a radio frequency field and receiving an echo signal through a radio frequency coil;

[0026] A controller is used to execute the echo time calculation method described in the first aspect above.

[0027] In a third aspect, a computer device is provided in this embodiment, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the echo time calculation method described in the first aspect when executing the computer program.

[0028] In a fourth aspect, in this embodiment, a storage medium is provided, on which a computer program is stored, and when the program is executed by a processor, the echo time calculation method described in the first aspect is implemented.

[0029] Compared with the related art, an echo time calculation method, device, storage medium and magnetic resonance imaging system provided in this embodiment obtain the signal amplitude of the echo signal; fit the echo signal through an amplitude fitting function based on the signal amplitude to obtain a parameter group in the amplitude fitting function; the amplitude fitting function includes a time variable and the parameter group; extract the second parameter in the parameter group as the target echo time, and can use the signal amplitude in the echo signal as a reference to optimize the amplitude fitting function to obtain the parameter group, thereby extracting the second parameter to obtain an accurate target echo time, thereby solving the problem of being unable to accurately calculate the echo time.

[0030] Details of one or more embodiments of the present application are set forth in the following drawings and description to make other features, objects, and advantages of the present application more readily apparent. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0032] Figure 1 is a hardware structure block diagram of a terminal of an echo time calculation method in an embodiment;

[0033] Figure 2 is a flow chart of a method for calculating echo time in one embodiment;

[0034] Figure 3 is a flow chart of a method for calculating echo time in a preferred embodiment;

[0035] Figure 4 It is a structural block diagram of an echo time calculation device in an embodiment.

[0036] In the figure: 102, processor; 104, memory; 106, transmission device; 108, input and output device; 10, signal amplitude acquisition module; 20, echo signal fitting module; 30, echo time calculation module. DETAILED DESCRIPTION

[0037] In order to more clearly understand the purpose, technical solutions and advantages of the present application, the present application is described and illustrated below in conjunction with the accompanying drawings and embodiments.

[0038] Unless otherwise defined, the technical terms or scientific terms involved in this application shall have the general meaning understood by people with ordinary skills in the technical field to which this application belongs. The words "one", "a", "a", "the", "these" and the like in this application do not represent quantitative restrictions, and they can be singular or plural. The terms "include", "comprise", "have" and any variants thereof involved in this application are intended to cover non-exclusive inclusions; for example, a process, method and system, product or device comprising a series of steps or modules (units) is not limited to the listed steps or modules (units), but may include unlisted steps or modules (units), or may include other steps or modules (units) inherent to these processes, methods, products or devices. The words "connect", "connected", "coupled" and the like involved in this application are not limited to physical or mechanical connections, but may include electrical connections, whether directly or indirectly. The "multiple" involved in this application refers to two or more. "And / or" describes the association relationship of associated objects, indicating that there can be three relationships. For example, "A and / or B" can mean: A exists alone, A and B exist at the same time, and B exists alone. Usually, the character " / " indicates that the objects associated with each other are in an "or" relationship. The terms "first", "second", "third", etc. involved in this application are only used to distinguish similar objects and do not represent a specific ordering of the objects.

[0039] The method embodiment provided in this embodiment can be executed in a terminal, a computer or a similar computing device. For example, running on a terminal, Figure 1 FIG. 4 is a hardware structure diagram of a terminal of the echo time calculation method of this embodiment. Figure 1 As shown, the terminal may include one or more ( Figure 1 Only one is shown in the figure) processor 102 and memory 104 for storing data, wherein processor 102 may include but is not limited to a processing device such as a microprocessor MCU or a programmable logic device FPGA. The above terminal may also include a transmission device 106 and an input and output device 108 for communication functions. It can be understood by those skilled in the art that Figure 1 The structure shown is for illustration only and does not limit the structure of the above terminal. Figure 1 More or fewer components as shown, or with Figure 1 Different configurations shown.

[0040] The memory 104 can be used to store computer programs, for example, software programs and modules of application software, such as the computer program corresponding to the echo time calculation method in this embodiment. The processor 102 executes various functional applications and data processing by running the computer program stored in the memory 104, that is, to implement the above method. The memory 104 may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 104 may further include a memory remotely arranged relative to the processor 102, and these remote memories may be connected to the terminal via a network. Examples of the above network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0041] The transmission device 106 is used to receive or send data via a network. The above network includes a wireless network provided by the communication provider of the terminal. In one example, the transmission device 106 includes a network adapter (Network Interface Controller, referred to as NIC), which can be connected to other network devices through a base station so as to communicate with the Internet. In one example, the transmission device 106 can be a radio frequency (Radio Frequency, referred to as RF) module, which is used to communicate with the Internet wirelessly.

[0042] The basic principle of magnetic resonance imaging is to generate a macroscopic magnetization vector in the protons of the object under test by applying an external magnetic field, and to stimulate the macroscopic magnetization vector to precess around the magnetic field by applying a radio frequency pulse sequence, thereby generating a magnetic resonance signal. After collecting the magnetic resonance signal, the magnetic resonance signal is reconstructed through spatial phase encoding technology to obtain a tissue image of the object under test, forming a magnetic resonance image.

[0043] The echo time in magnetic resonance imaging refers to the time interval from the midpoint of the pulse that generates the macroscopic transverse magnetization vector to the midpoint of the echo, which is of great significance in magnetic resonance imaging. For example, the accurate calculation of the echo time is conducive to quantitative imaging and diffusion imaging. However, due to factors such as instrument accuracy, measurement errors, tissue characteristics of the object being measured, and external interference, the echo signal is often mixed with a lot of noise, which affects the calculation of the echo time and makes it impossible to obtain an accurate echo time.

[0044] In this embodiment, a method for calculating echo time is provided. Figure 2 is a flow chart of the echo time calculation method of this embodiment, such as Figure 2 As shown, the method comprises the following steps:

[0045] Step S210, obtaining the signal amplitude of the echo signal.

[0046] Specifically, an echo sequence is applied to generate an echo signal. The echo sequence generally includes a radio frequency pulse for excitation signal and a radio frequency pulse or gradient field for phase focusing, which can eventually generate a magnetic resonance echo signal with a signal amplitude gradually increasing and then gradually decreasing, wherein the maximum signal intensity generated is the signal amplitude of the echo signal.

[0047] Step S220, based on the signal amplitude, the echo signal is fitted by an amplitude fitting function to obtain a parameter group in the amplitude fitting function; the amplitude fitting function includes a time variable and a parameter group.

[0048] Specifically, an amplitude fitting function is set to fit the echo signal in magnetic resonance imaging, wherein the amplitude fitting function includes a time variable and a parameter group, the parameter group has an initial value, and the time variable corresponds to the timing of the echo signal. In one embodiment, the amplitude fitting function can be expressed in the form of a product of a Gaussian distribution and a constant.

[0049] The amplitude fitting function is iteratively optimized based on the signal amplitude obtained by real sampling. The initial value of the parameter group in the amplitude fitting function is continuously updated during the iterative optimization process, and finally the parameter group to be solved is obtained.

[0050] Step S230: extracting the second parameter in the parameter group as the target echo time.

[0051] Specifically, the parameter group includes a first parameter, a second parameter and a third parameter. In the iterative optimization process of the amplitude fitting function, the second parameter is used to fit the time variable corresponding to the amplitude. Therefore, after obtaining the parameter group to be solved, the second parameter is extracted as the target echo time.

[0052] The above steps obtain the signal amplitude of the echo signal as a benchmark, fit the echo signal through the amplitude fitting function, obtain the parameter group to be solved in the amplitude fitting function after iterative optimization, extract the second parameter in the parameter group as the target echo time, and make the amplitude fitting function close to the waveform of the actual sampled echo signal through fitting, so as to obtain the accurate fitting amplitude, so as to accurately calculate the echo time, which solves the problem that the echo signal is mixed with noise and the echo time cannot be accurately calculated.

[0053] In some embodiments, the method further comprises:

[0054] An echo signal is generated using an echo sequence; the echo sequence includes a gradient echo sequence or a spin echo sequence.

[0055] Among them, the echo sequence is a combination of the settings and time arrangements of relevant parameters such as RF pulses, gradient fields, and signal acquisition time. It usually includes RF pulses for excitation signals and RF pulses or gradient fields for phase focusing, which can ultimately produce a magnetic resonance echo signal with a signal amplitude that gradually increases and then gradually decreases.

[0056] In order to meet different requirements of magnetic resonance imaging, such as imaging speed and imaging quality, different echo sequences can be used to generate echo signals. In this embodiment, the echo sequence includes a gradient echo sequence (Gradient Recalled Echo, GRE) or a spin echo sequence (Spin Echoes, SE), which generates a gradient echo signal or a spin echo signal accordingly.

[0057] The spin echo sequence is the most basic pulse sequence in magnetic resonance imaging. It starts with a 90° excitation pulse. After generating the largest macroscopic transverse magnetization vector, a 180° pulse is applied in the X and Y planes. As a result, protons with a fast precession frequency are in the back and protons with a slow precession frequency are in the front. Then they continue to precess at the original frequency. After a delay of the same amount of time, the previously dephased proton group re-phases, and the phase difference between protons returns to zero. When the proton group phases re-phase, the transverse vector in the X and Y planes reaches its maximum again, generating the maximum signal strength. The proton group is then dephased again, and a gradually decaying signal can be detected in the receiving coil again, thus forming a spin echo signal that gradually rises and then gradually decreases.

[0058] The gradient echo sequence is to apply a gradient field in the readout direction, i.e., the frequency encoding direction, after the RF pulse is excited. This gradient field will cause a difference in magnetic field strength in the frequency encoding direction after being superimposed on the main magnetic field. The precession frequency of protons in this direction will also differ, thereby accelerating the dephasing of protons. The macroscopic transverse magnetization vector of the tissue will quickly decay to zero. This gradient field is called the de-phase gradient field. At this time, a gradient field with the same intensity and opposite direction is immediately applied in the frequency encoding direction. The precession frequency of protons with slow precession frequency under the action of the de-phase gradient field will be accelerated, and the precession frequency of protons with fast precession frequency will be slowed down. In this way, the dephasing of protons caused by the de-phase gradient field will be gradually corrected, and the macroscopic transverse magnetization vector of the tissue will gradually recover. After the same time as the de-phase gradient field, the dephasing of protons caused by the de-phase gradient field will be corrected, and the macroscopic transverse magnetization vector of the tissue will gradually recover until the peak value of the signal amplitude. This gradient field is called the phase-focused gradient field. Under the continued action of the phase-focused gradient field, the protons dephase in the opposite direction, and the macroscopic transverse magnetization vector of the tissue begins to decay until it reaches zero, generating a gradient echo signal with a signal amplitude that increases from zero to large and then from large to zero.

[0059] In this embodiment, an echo signal is generated by using an echo sequence, wherein the echo sequence includes a gradient echo sequence or a spin echo sequence. The echo signal generated by the gradient echo sequence or the spin echo sequence can provide an echo signal for subsequent fitting using an amplitude fitting function.

[0060] In some of the embodiments, the method further comprises: establishing an amplitude fitting function using Gaussian distribution based on the parameter group and the time variable.

[0061] Specifically, the amplitude fitting function can fit the echo signal in the form of the product of Gaussian distribution and a constant, wherein the parameter group includes a first parameter, a second parameter and a third parameter to be solved, all having initial values, and the time variable corresponds to the timing of the echo signal.

[0062] Among them, Gaussian distribution, also known as normal distribution, is an important probability distribution in statistics. It is widely used in nature and social sciences and is of great significance in many fields. Gaussian distribution has the characteristics of a bell-shaped curve, whose shape is determined by the mean (μ) and standard deviation (σ). The center of the curve is at the mean, and the standard deviation determines the width of the curve.

[0063] In this embodiment, the Gaussian distribution is expressed in the exponential form of the ratio of the square of the difference between the time variable and the second parameter to the square of the third parameter, and the product of the Gaussian distribution and the first parameter variable represents the amplitude fitting function.

[0064] For the amplitude fitting function in all the above embodiments, there is the following expression:

[0065]

[0066] Among them, S 0 represents the fitting amplitude in the echo signal; t represents the fitting amplitude S 0 The corresponding time variable; [k 1 ,k 2 ,k 3 ] represents the parameter group to be solved, k 1 represents the first parameter, k 2 represents the second parameter, k 3 Represents the third parameter.

[0067] Specifically, the collected echo signal is fitted with an amplitude fitting function so that the waveform of the amplitude fitting function is close to the waveform of the echo signal, thereby taking the second parameter as the final target echo time.

[0068] The first parameter, the second parameter and the third parameter do not represent a specific ordering of the objects, and the amplitude fitting function is not limited to the one expression form shown.

[0069] In this embodiment, Gaussian distribution is adopted, and an amplitude fitting function is established based on a parameter group and a time variable, which can provide an amplitude fitting function for fitting a real sampled echo signal, thereby providing a more accurate signal amplitude obtained by fitting for the subsequent calculation of an accurate echo time.

[0070] In some of the embodiments, the above-mentioned method of fitting the echo signal by using the amplitude fitting function based on the signal amplitude to obtain the parameter group in the amplitude fitting function includes the following steps:

[0071] An error model is established based on the amplitude fitting function; according to the error model and the signal amplitude, the parameter group in the amplitude fitting function is optimized to obtain a fitting result.

[0072] Specifically, an error model is established based on the amplitude fitting function, and the amplitude fitting function is linearized by bringing the initial values ​​of the parameter variables into the error model. By solving the linearized error model, a fitting result is obtained, which includes an amplitude fitting function of the echo signal that is optimized and close to the actual sampling, and the parameter variables that are updated and optimized.

[0073] In this embodiment, the established amplitude fitting function is optimized based on the signal amplitude of the echo signal, so as to obtain an amplitude fitting function of the echo signal close to the actual sampling as a fitting result.

[0074] In some of the embodiments, the above-mentioned optimization of the parameter group in the amplitude fitting function according to the error model and the signal amplitude to obtain the fitting result includes the following steps:

[0075] The parameter group is iteratively updated through the nonlinear least squares algorithm to generate the fitting results.

[0076] Specifically, for the linearized error model obtained above, the least square method is used to solve the deviation value of the parameter group, and it is determined whether the deviation of each parameter group meets the termination condition. If the termination condition is not met, the initial value of the parameter group is updated by the obtained deviation value, and then the deviation value of the parameter variable is continuously brought into the linearized error model to solve the deviation value of the parameter variable. The deviation value of the parameter group refers to the deviation between the parameter variable to be solved and the real sampled echo signal.

[0077] The above process is iterated and solved until the deviation value of each parameter group meets the termination condition, then the iterative update is stopped, and the most recently updated parameter group is updated with the deviation that meets the requirements to obtain the final fitting result.

[0078] Among them, the nonlinear least squares method is an algorithm for solving the minimum error between the benchmark (observation value) and the amplitude fitting function (theoretical value) for the nonlinear relationship. By solving this problem by the nonlinear least squares method, the amplitude fitting function can be optimized to make it closer to the benchmark obtained by real sampling. The least squares method used in this embodiment includes but is not limited to the Levenberg-Margquardt algorithm, the Gauss-Newton Iteration Method, and the gradient descent algorithm.

[0079] Furthermore, the nonlinear least squares algorithm used is the Levenberg-Marquardt algorithm.

[0080] Among them, the Levenberg-Marquardt algorithm is an improved algorithm based on the Gauss-Newton iterative algorithm. Specifically, it uses gradient to solve the maximum (minimum) value. Based on the advantages of Newton's method and gradient descent method, Newton's method and gradient descent method are integrated during iteration. In the solution process, first determine whether Newton's method is applicable based on whether the current error is approximately zero. If so, Newton's method is used to solve the parameter variables; if not, the gradient descent method is used to solve the parameter variables to find the optimal solution.

[0081] The iterative optimization process in the Levenberg-Marquardt algorithm is as follows:

[0082] The partial derivatives of the amplitude fitting function with respect to each parameter variable are calculated according to the current initial values ​​of the parameter variables to form a Jacobi matrix. The approximate Hessian matrix is ​​calculated according to the Jacobi matrix to approximate the quadratic form of the amplitude fitting function. The initial values ​​of the current parameter variables are updated according to the approximate Hessian matrix and the gradient information, and the adjustment factor (lambda) is used to balance the gradient descent method and the Newton method according to the problem to be solved. The size of the parameter variable update (i.e., the deviation value) is detected. If the termination condition is met (such as the deviation value is less than a certain threshold), the iteration is stopped, otherwise the iterative update is continued until the termination condition is met.

[0083] In this embodiment, the amplitude fitting function is optimized based on the real sampled echo signal by adopting the nonlinear least squares method, and an amplitude fitting function close to the real sampled echo signal is obtained as the fitting result, so that the second parameter variable in the fitting result can be extracted as the target echo time.

[0084] The present embodiment is described and illustrated below through preferred embodiments.

[0085] Figure 3 is a flow chart of the echo time calculation method of the preferred embodiment, such as Figure 3 As shown, the echo time calculation method includes the following steps:

[0086] Step S310: Generate an echo signal using an echo sequence and obtain the signal amplitude of the echo signal; the echo sequence includes a gradient echo sequence or a spin echo sequence.

[0087] Step S320: Based on the parameter group and the time variable, an amplitude fitting function is established using Gaussian distribution.

[0088] Among them, the amplitude fitting function is:

[0089]

[0090] Among them, S 0 represents the fitting amplitude in the echo signal; t represents the fitting amplitude S 0 The corresponding time variable; [k 1 ,k 2 ,k 3 ] represents the parameter group to be solved, k 1 represents the first parameter, k 2 represents the second parameter, k 3 Represents the third parameter.

[0091] Step S330: establishing an error model based on the amplitude fitting function.

[0092] Step S340, using a nonlinear least squares algorithm, taking the signal amplitude as a reference, and using an error model to iteratively update the parameter group in the amplitude fitting function to obtain a fitting result.

[0093] Step S350: extract the second parameter in the fitting result as the target echo time.

[0094] It should be noted that the steps shown in the above process or the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0095] Based on the same inventive concept, the embodiment of the present application also provides an echo time calculation device for implementing the echo time calculation method involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations of one or more echo time calculation device embodiments provided below can refer to the limitations of the echo time calculation method above, and will not be repeated here.

[0096] Figure 4 is a structural block diagram of the echo time calculation device of this embodiment, such as Figure 4As shown, the device includes: a signal amplitude acquisition module 10, an echo signal fitting module 20 and an echo time calculation module 30.

[0097] The signal amplitude acquisition module 10 is used to acquire the signal amplitude of the echo signal.

[0098] The echo signal fitting module 20 is used to fit the echo signal by an amplitude fitting function based on the signal amplitude to obtain a parameter group in the amplitude fitting function; the amplitude fitting function includes a time variable and a parameter group.

[0099] The echo time calculation module 30 is used to extract the second parameter in the parameter group as the target echo time.

[0100] Through the device provided in this embodiment, the signal amplitude of the echo signal is obtained as a reference, the echo signal is fitted by the amplitude fitting function, and the parameter group to be solved in the amplitude fitting function is obtained after iterative optimization. The second parameter in the parameter group is extracted as the target echo time. The amplitude fitting function can be made close to the waveform of the actual sampled echo signal through fitting, and an accurate fitting amplitude can be obtained, so that the echo time can be accurately calculated, which solves the problem that the echo signal is mixed with noise and the echo time cannot be accurately calculated.

[0101] It should be noted that the above modules can be functional modules or program modules, and can be implemented by software or hardware. For modules implemented by hardware, the above modules can be located in the same processor; or the above modules can be located in different processors in any combination.

[0102] The present application also provides a magnetic resonance imaging system, comprising: a magnetic resonance scanning device for applying an echo sequence to form a radio frequency field and receiving echo signals through a radio frequency coil;

[0103] The controller is used to execute the echo time calculation method in the above embodiment.

[0104] After receiving the scanning instruction, the magnetic resonance imaging system obtains the pulse sequence corresponding to the scanning instruction (i.e., the echo sequence in the above embodiment), and performs magnetic resonance scanning based on the pulse waveform corresponding to the echo sequence transmitted by the magnetic resonance scanning device, so as to execute the pulse sequence. The magnetic resonance scanning device includes various coils, such as RF transmitting coils, RF receiving coils, etc., and gradient coils, etc. The coils of the magnetic resonance scanning device can receive magnetic resonance signals (i.e., the echo signals in the above embodiment) or transmit corresponding pulses, and the controller obtains the received echo signals and calculates the echo time accordingly.

[0105] In this embodiment, a computer device is further provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor is configured to run the computer program to execute the steps in any one of the above method embodiments.

[0106] Optionally, the computer device may further include a transmission device and an input / output device, wherein the transmission device is connected to the processor, and the input / output device is connected to the processor.

[0107] It should be noted that the specific examples in this embodiment can refer to the examples described in the above embodiments and optional implementation modes, and will not be repeated in this embodiment.

[0108] In addition, in combination with the echo time calculation method provided in the above embodiments, a storage medium may be provided in this embodiment to implement the method. The storage medium stores a computer program, and when the computer program is executed by a processor, any one of the echo time calculation methods in the above embodiments is implemented.

[0109] It should be understood that the specific embodiments described herein are only used to explain the application, rather than to limit it. Based on the embodiments provided in this application, all other embodiments obtained by ordinary technicians in this field without creative work are within the protection scope of this application.

[0110] Obviously, the drawings are only some examples or embodiments of the present application. For ordinary technicians in the field, the present application can also be applied to other similar situations based on these drawings without creative work. In addition, it is understandable that although the work done in this development process may be complicated and lengthy, for ordinary technicians in the field, certain changes in design, manufacturing or production based on the technical content disclosed in this application are only conventional technical means and should not be regarded as insufficient content disclosed in this application.

[0111] The term "embodiment" in this application refers to a specific feature, structure or characteristic described in conjunction with the embodiment that can be included in at least one embodiment of the present application. The appearance of this phrase in various places in the specification does not necessarily mean the same embodiment, nor does it mean that it is mutually exclusive with other embodiments and is independent or optional. It is clearly or implicitly understood by those of ordinary skill in the art that the embodiments described in this application can be combined with other embodiments without conflict.

[0112] The above-mentioned embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of patent protection. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the scope of protection of the present application. Therefore, the scope of protection of the present application shall be subject to the attached claims.

Claims

1. A method for calculating echo time, characterized in that: include: Obtaining the signal amplitude of the echo signal; The echo signal is fitted by an amplitude fitting function based on the signal amplitude to obtain a parameter group in the amplitude fitting function; the amplitude fitting function includes a time variable and the parameter group; A second parameter in the parameter group is extracted as a target echo time.

2. The echo time calculation method according to claim 1, characterized in that: Also includes: generating the echo signal by using an echo sequence; The echo sequence includes a gradient echo sequence or a spin echo sequence.

3. The echo time calculation method according to claim 1, characterized in that: Also includes: Based on the parameter group and the time variable, the amplitude fitting function is established using Gaussian distribution.

4. The echo time calculation method according to any one of claims 1 or 3, characterized in that: The amplitude fitting function is: Among them, S0 represents the fitting amplitude in the echo signal; t represents the time variable corresponding to the fitting amplitude S0; [k1, k2, k3] represents the parameter group to be solved, k1 represents the first parameter, k2 represents the second parameter, and k3 represents the third parameter.

5. The echo time calculation method according to claim 1, characterized in that: The step of fitting the echo signal by an amplitude fitting function based on the signal amplitude to obtain a parameter group in the amplitude fitting function includes: Establishing an error model based on the amplitude fitting function; According to the error model and the signal amplitude, the parameter group in the amplitude fitting function is optimized to obtain a fitting result.

6. The echo time calculation method according to claim 5, characterized in that: The step of optimizing the parameter group in the amplitude fitting function according to the error model and the signal amplitude to obtain a fitting result includes: The parameter group is iteratively updated through a nonlinear least squares algorithm to generate the fitting result.

7. The echo time calculation method according to claim 6, characterized in that: The nonlinear least squares algorithm is the Levenberg-Marquardt algorithm.

8. A magnetic resonance imaging system, characterized in that: include: A magnetic resonance scanning device for applying an echo sequence to form a radio frequency field and receiving an echo signal through a radio frequency coil; A controller, used to execute the echo time calculation method described in any one of claims 1 to 7.

9. A computer device comprising a memory and a processor, characterized in that: A computer program is stored in the memory, and the processor is configured to run the computer program to execute the echo time calculation method according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the echo time calculation method according to any one of claims 1 to 7 are implemented.

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