Relaxation time determination method and device, equipment, medium and magnetic resonance imaging system

Abstract

The invention relates to a relaxation time determination method and device, equipment, a medium and a magnetic resonance imaging system. The method comprises the following steps: acquiring magnetic resonance images of a to-be-detected object at different echo times; the magnetic resonance image comprises at least two substance components; and determining the relaxation time of each substance component according to the echo time and the gray value of each magnetic resonance image and the proportion of each substance component in each magnetic resonance image. Since the magnetic resonance image comprises at least two substance components, and the proportion of each substance component in the magnetic resonance image is considered in the process of determining the relaxation time, the relaxation time can be determined according to the echo time and the gray value of each magnetic resonance image and the proportion of each substance component in each magnetic resonance image, and the relaxation time can be determined according to the relaxation time and the gray value of each magnetic resonance image and the proportion of each substance component in each magnetic resonance image. And the relaxation time of each substance component can be accurately determined.

Description

Technical Field

[0001] The present application relates to the field of medical technology, and in particular to a method, device, equipment, medium and magnetic resonance imaging system for determining relaxation time. Background Art

[0002] With the development of medical technology, magnetic resonance images can now include at least one material component. Medical parameters of this material component can often be determined from the magnetic resonance images. For example, this medical parameter can be the T2 relaxation time of the material component. Quantitatively determining the T2 relaxation time of a material component can reflect its specificity and plays an important role in the analysis and research of medical images.

[0003] However, conventional techniques can only determine the T2 relaxation time of a single material component present in an MRI image. Therefore, when an MRI image includes multiple material components, conventional techniques cannot accurately determine the T2 relaxation time of each material component. Summary of the Invention

[0004] Based on this, it is necessary to provide a relaxation time determination method, device, equipment, medium and magnetic resonance imaging system to address the above technical problems, which can accurately determine the T2 relaxation time of each material component in the magnetic resonance image.

[0005] In a first aspect, the present application provides a method for determining relaxation time, comprising:

[0006] Acquiring magnetic resonance images of the object to be measured at different echo times; the magnetic resonance images include at least two material components;

[0007] The relaxation time of each of the material components is determined according to the echo time and the grayscale value of each of the magnetic resonance images and the proportion of each of the material components in each of the magnetic resonance images.

[0008] In one embodiment, determining the relaxation time of each material component based on the echo time and grayscale value of each magnetic resonance image and the proportion of each material component in each magnetic resonance image includes:

[0009] Constructing a preset relaxation time estimation model based on the grayscale estimation items of each of the material components;

[0010] The relaxation time estimation model is used to determine the relaxation time of each material component based on the echo time and grayscale value of each magnetic resonance image and the proportion of each material component in each magnetic resonance image.

[0011] In one embodiment, the determining the relaxation time of each of the material components using the relaxation time estimation model and based on the echo time and grayscale value of each of the magnetic resonance images and the proportion of each of the material components in each of the magnetic resonance images includes:

[0012] The echo time and grayscale value of each magnetic resonance image are used as known parameters, and the proportion and relaxation time of each material component are used as unknown variables. These are substituted into the relaxation time estimation model for calculation to obtain the relaxation time of each material component.

[0013] In one embodiment, the determining the relaxation time of each of the material components using the relaxation time estimation model and based on the echo time and grayscale value of each of the magnetic resonance images and the proportion of each of the material components in each of the magnetic resonance images includes:

[0014] The proportion of each material component, the echo time and the grayscale value of each magnetic resonance image are used as known parameters, and the relaxation time of each material component is used as an unknown variable. The parameters are substituted into the relaxation time estimation model for calculation to obtain the relaxation time of each material component.

[0015] In one embodiment, the method further comprises:

[0016] detecting the number of material components in each of the magnetic resonance images;

[0017] A grayscale estimation item of each material component is determined according to the number of material components in each magnetic resonance image.

[0018] In one embodiment, the magnetic resonance image includes a first material component and a second material component, and the relaxation time estimation model includes a first grayscale estimation item corresponding to the first material component and a second grayscale estimation item corresponding to the second material component; the first grayscale estimation item includes the relationship between the proportion of the first material component, the initial grayscale value, the echo time and the relaxation time; the second grayscale estimation item includes the relationship between the proportion of the second material component, the initial grayscale value, the echo time and the relaxation time.

[0019] In a second aspect, the present application further provides a device for determining relaxation time, comprising:

[0020] An acquisition module, configured to acquire magnetic resonance images of the object under test at different echo times; the magnetic resonance images include at least two material components;

[0021] The determination module is configured to determine the relaxation time of each of the material components according to the echo time and grayscale value of each of the magnetic resonance images and the proportion of each of the material components in each of the magnetic resonance images.

[0022] In a third aspect, the present application further provides a computer device comprising a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the steps of the method for determining the relaxation time in the first aspect are implemented.

[0023] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method for determining the relaxation time in the first aspect.

[0024] In a fifth aspect, the present application further provides a magnetic resonance imaging system, the magnetic resonance imaging system comprising an image acquisition device and a computer device, the image acquisition device being connected to the computer device;

[0025] The image acquisition device is used to acquire magnetic resonance images of the object to be measured at different echo times, and send the magnetic resonance images to the computer device;

[0026] The computer device is used to execute the steps of the method for determining the relaxation time in the first aspect.

[0027] The above-mentioned relaxation time determination method, device, equipment, medium and magnetic resonance imaging system obtain magnetic resonance images of the object to be measured at different echo times; the magnetic resonance images include at least two material components; based on the echo time and grayscale value of each magnetic resonance image, and the proportion of each material component in each magnetic resonance image, the relaxation time of each material component is determined. Because the magnetic resonance images of the embodiment of the present application include at least two material components, and the proportion of each material component in the magnetic resonance image is taken into account in the process of determining the relaxation time, the embodiment of the present application can accurately determine the relaxation time of each material component based on the echo time and grayscale value of each magnetic resonance image, and the proportion of each material component in each magnetic resonance image. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the following briefly introduces the drawings required for use in the embodiments of the present application or related technical descriptions. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying any creative work.

[0029] Figure 1 FIG. 1 is an application environment diagram of a method for determining relaxation time in one embodiment;

[0030] Figure 2 Schematic diagram of a method for determining relaxation time in one embodiment;

[0031] Figure 3 Schematic diagram of a relaxation time determination step in one embodiment;

[0032] Figure 4 is a flow chart of a method for determining relaxation time in another embodiment;

[0033] Figure 5 is a schematic structural diagram of a magnetic resonance imaging system in one embodiment;

[0034] Figure 6 FIG. 4 is a structural block diagram of a device for determining relaxation time in one embodiment. DETAILED DESCRIPTION

[0035] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0036] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this application belongs; the terms used herein are only for the purpose of describing specific embodiments and are not intended to limit this application; the terms "including" and "having" and any variations thereof in the specification and claims of this application and the above-mentioned figure descriptions are intended to cover non-exclusive inclusions.

[0037] In the description of the embodiments of this application, the technical terms "first" and "second" are used only to distinguish different objects and should not be understood to indicate or imply relative importance or implicitly specify the quantity, specific order, or primary and secondary relationship of the indicated technical features. In the description of the embodiments of this application, the meaning of "plurality" is more than two, unless otherwise clearly and specifically defined.

[0038] References herein to "embodiments" mean that a particular feature, structure, or characteristic described in connection with the embodiments may 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 refer to the same embodiment, nor does it constitute an independent or alternative embodiment that is mutually exclusive of other embodiments. It is understood, both explicitly and implicitly, by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0039] With the advancement of medical technology, magnetic resonance imaging (MRI) technology can enhance the magnetic field outside the subject, causing protons in the subject to generate a macroscopic magnetization vector. Radiofrequency excitation pulses are then transmitted to the subject, causing the macroscopic magnetization vector to precess around the magnetic field, generating a magnetic resonance signal. This signal is then processed to produce a magnetic resonance image. Currently, MRI images can include at least one material component, and medical parameters of this material component can often be determined from the MRI image. For example, this medical parameter can be the T2 relaxation time (i.e., transverse relaxation time) of the material component. Quantitative determination of the T2 relaxation time of a material component can reflect its specificity and plays an important role in the analysis and research of medical images.

[0040] However, conventional techniques can only determine the T2 relaxation time of a single material component present in an MRI image. Therefore, when factors such as the partial volume effect exist in an MRI image, resulting in a single voxel in the MRI image containing multiple material components, conventional techniques cannot accurately determine the T2 relaxation time of each material component.

[0041] After introducing the background technology of the method for determining the relaxation time provided by the embodiment of the present application, the following briefly describes the implementation environment involved in the method for determining the relaxation time provided by the embodiment of the present application. The method for determining the relaxation time provided by the embodiment of the present application can be applied to Figure 1The computer device shown in FIG. This computer device can be a terminal or a server, and includes a processor, memory, an input / output interface, a communication interface, a display unit, and an input device. The processor, memory, and input / output interface are connected via a system bus, while the communication interface, display unit, and input device are connected to the system bus via the input / output interface. The processor of the computer device provides computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operating system and computer program stored in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and external devices. The communication interface of the computer device is used to communicate with external terminals via wired or wireless communication, which can be achieved via Wi-Fi, a mobile cellular network, NFC (near-field communication), or other technologies. When executed by the processor, the computer program implements a method for determining relaxation time. The display unit of the computer device is used to produce a visually visible image, and can be a display screen, a projection device, or a virtual reality imaging device. The display screen can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covering the display screen, or a button, trackball or touchpad set on the computer device casing, or an external keyboard, touchpad or mouse.

[0042] Those skilled in the art will understand that Figure 1 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific terminal may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0043] In one embodiment, Figure 2 As shown, a method for determining relaxation time is provided, which is applied to Figure 1 The computer device in the example is used to illustrate the process, including the following steps:

[0044] S201 , obtaining magnetic resonance images of a test object at different echo times; the magnetic resonance images include at least two material components.

[0045] The subject to be measured refers to the subject undergoing magnetic resonance imaging, for example, a patient. The echo time is the time between the transmission of a radiofrequency pulse and the reception of a signal peak. An MRI image may include at least two material components, for example, including but not limited to at least two of water, fat, and brain tissue metabolites (e.g., lactic acid, lipids, etc.).

[0046] In the embodiments of the present application, the computer device may optionally obtain magnetic resonance images of the subject under test at different echo times from a preset database; alternatively, the computer device may perform magnetic resonance imaging of the subject under test based on different echo times to obtain magnetic resonance images of the subject under test at different echo times. Of course, the embodiments of the present application do not limit the specific implementation method for obtaining magnetic resonance images.

[0047] S202 , determining the relaxation time of each material component according to the echo time and grayscale value of each magnetic resonance image and the proportion of each material component in each magnetic resonance image.

[0048] The grayscale value refers to the signal amplitude of the magnetic resonance image, and the relaxation time may be the T2 relaxation time (i.e., the transverse relaxation time). The T2 relaxation time refers to the time it takes for the transverse magnetization vector to decay to 37% of its maximum value.

[0049] In an embodiment of the present application, the computer device can respectively obtain the echo time and grayscale value of each magnetic resonance image. Optionally, the computer device can directly obtain the echo time and grayscale value of each magnetic resonance image; or the computer device can first extract the region of interest of each magnetic resonance image from each magnetic resonance image, and then obtain the echo time and grayscale value of the region of interest in each magnetic resonance image. It should be noted that the regions of interest in each magnetic resonance image of the same object to be tested correspond to the same part, that is, the regions of interest in each magnetic resonance image of the same object to be tested can all be the head, legs, etc. In addition, the computer device can also determine the proportion of each material component in each magnetic resonance image. Optionally, the computer device can determine the value of the proportion of each material component in each magnetic resonance image, or the computer device can set the proportion of each material component in each magnetic resonance image as an unknown variable.

[0050] Thus, optionally, if the value of the proportion of each material component in each magnetic resonance image can be determined in advance, the computer device can determine the relaxation time of each material component based on the echo time, grayscale value and the proportion of each material component in each magnetic resonance image; or, if the proportion of each material component in each magnetic resonance image is set as an unknown variable in advance, the computer device can determine the relaxation time of each material component and the proportion of each material component in each magnetic resonance image based on the echo time and grayscale value of each magnetic resonance image. Of course, the embodiment of the present application does not limit the specific implementation method for determining the relaxation time of each material component.

[0051] In the above-mentioned relaxation time determination method, magnetic resonance images of the object to be measured are obtained at different echo times; the magnetic resonance images include at least two material components; and the relaxation time of each material component is determined based on the echo time and grayscale value of each magnetic resonance image, as well as the proportion of each material component in each magnetic resonance image. Because the magnetic resonance images of the embodiment of the present application include at least two material components, and the proportion of each material component in the magnetic resonance image is taken into account during the relaxation time determination process, the embodiment of the present application can accurately determine the relaxation time of each material component based on the echo time and grayscale value of each magnetic resonance image, as well as the proportion of each material component in each magnetic resonance image.

[0052] In one embodiment, a method for determining the relaxation time of each material component is provided, namely, the above-mentioned step S202 of "determining the relaxation time of each material component according to the echo time and grayscale value of each magnetic resonance image and the proportion of each material component in each magnetic resonance image" is provided. Figure 3 Shown, including:

[0053] S301: Construct a preset relaxation time estimation model based on the grayscale estimation items of each material component.

[0054] In an embodiment of the present application, the computer device may pre-determine the grayscale estimation item of each material component. In one embodiment, the specific implementation of "pre-determining the grayscale estimation item of each material component" includes:

[0055] Detect the amount of material components in each magnetic resonance image.

[0056] A grayscale estimation item for each material component is determined based on the number of portions of the material component in each magnetic resonance image.

[0057] Specifically, the computer device may detect the number of material components in each magnetic resonance image and determine the number of grayscale estimation items based on the number of material components in each magnetic resonance image. Thus, the grayscale estimation item for each material component may be determined based on the number of grayscale estimation items. For example, assuming that the number of material components detected in each magnetic resonance image is three, the computer device may determine the number of grayscale estimation items to be three, and may determine a grayscale estimation item Sa corresponding to material component a, a grayscale estimation item Sb corresponding to material component b, and a grayscale estimation item Sc corresponding to material component c, respectively.

[0058] Thus, the computer device can construct a preset relaxation time estimation model based on the grayscale estimation items of each material component. For example, the computer device can sum the grayscale estimation items of each material component to construct the preset relaxation time estimation model. For example, assuming that the grayscale estimation items include a grayscale estimation item Sa corresponding to material component a, a grayscale estimation item Sb corresponding to material component b, and a grayscale estimation item Sc corresponding to material component c, the relaxation time estimation model can be: S = Sa + Sb + Sc.

[0059] S302 : Determine the relaxation time of each material component using a relaxation time estimation model based on the echo time and grayscale value of each magnetic resonance image and the proportion of each material component in each magnetic resonance image.

[0060] In an embodiment of the present application, optionally, if the value of the proportion of each material component in each magnetic resonance image can be determined in advance, the computer device can utilize the relaxation time estimation model, and based on the echo time of each magnetic resonance image, the gray value and the proportion of each material component in each magnetic resonance image, determine the relaxation time of each material component. Alternatively, if the proportion of each material component in each magnetic resonance image is set as an unknown variable in advance, the computer device can utilize the relaxation time estimation model, and based on the echo time and the gray value of each magnetic resonance image, determine the relaxation time of each material component and the proportion of each material component in each magnetic resonance image. Of course, the embodiment of the present application does not limit the specific implementation method for determining the relaxation time of each material component.

[0061] In this embodiment, a preset relaxation time estimation model can be accurately constructed based on the grayscale estimation items of each material component, so that the accurate relaxation time estimation model can be used to accurately determine the relaxation time of each material component based on the echo time and grayscale value of each magnetic resonance image, as well as the proportion of each material component in each magnetic resonance image.

[0062] In one embodiment, the magnetic resonance image includes a first material component and a second material component, and the relaxation time estimation model includes a first grayscale estimation item corresponding to the first material component and a second grayscale estimation item corresponding to the second material component, wherein the first grayscale estimation item includes the relationship between the proportion of the first material component, the initial grayscale value, the echo time and the relaxation time; the second grayscale estimation item includes the relationship between the proportion of the second material component, the initial grayscale value, the echo time and the relaxation time.

[0063] For example, assuming that the proportion of the first material component is , the proportion of the second material component is , the T2 relaxation time corresponding to the first material component is , the T2 relaxation time corresponding to the second material component is , initial grayscale value represents the initial value of the signal when there is no T2 relaxation, the echo time is t, and the gray value of the magnetic resonance image is S. Then the gray value S of the magnetic resonance image and the echo time t satisfy the double exponential decay. The relaxation time estimation model is shown as follows:

[0064]

[0065] in, represents the first grayscale estimation term, Represents the second grayscale estimation item.

[0066] In one embodiment, a method for determining the relaxation time of each material component is provided, namely, the method of “determining the relaxation time of each material component using a relaxation time estimation model based on the echo time and grayscale value of each magnetic resonance image and the proportion of each material component in each magnetic resonance image” in S302 above, including:

[0067] The echo time and grayscale value of each magnetic resonance image are used as known parameters, and the proportion and relaxation time of each material component are used as unknown variables. They are substituted into the relaxation time estimation model for calculation to obtain the relaxation time of each material component.

[0068] In an embodiment of the present application, the computer device can pre-set the proportion of each material component in the magnetic resonance image as an unknown variable, and use the echo time and grayscale value of each magnetic resonance image as known parameters, so that the unknown variables and known parameters are substituted into the relaxation time estimation model for calculation to obtain the relaxation time of each material component. For example, assuming that the echo time of each magnetic resonance image is t1, t2, ..., tn, and the grayscale value of each magnetic resonance image is S1, S2, ..., Sn, the computer device can use the Matlab Curve Fitting toolbox to substitute the echo time and grayscale value of each magnetic resonance image into the relaxation time estimation model to calculate the proportion of each material component and the relaxation time of each material component.

[0069] In this embodiment, the echo time and grayscale value of each magnetic resonance image can be used as known parameters, and the proportion and relaxation time of each material component can be used as unknown variables. They can be substituted into the relaxation time estimation model for calculation to accurately obtain the proportion and relaxation time of each material component.

[0070] In one embodiment, another implementation method for determining the relaxation time of each material component is provided, namely, the method of "using a relaxation time estimation model and determining the relaxation time of each material component based on the echo time and grayscale value of each magnetic resonance image and the proportion of each material component in each magnetic resonance image" in S302 above, including:

[0071] The proportion of each material component, the echo time and grayscale value of each magnetic resonance image are used as known parameters, and the relaxation time of each material component is used as an unknown variable. They are substituted into the relaxation time estimation model for calculation to obtain the relaxation time of each material component.

[0072] In the embodiment of the present application, the computer device can use the component analysis method to determine the value of the proportion of each material component in each magnetic resonance image in advance, and use the value of the proportion of each material component in the magnetic resonance image, the echo time and grayscale value of each magnetic resonance image as known parameters, and the relaxation time of each material component as an unknown variable, so as to substitute the unknown variables and known parameters into the relaxation time estimation model for calculation, and the relaxation time of each material component can be obtained. For example, assuming that the echo time of each magnetic resonance image is t1, t2, ..., tn, the grayscale value of each magnetic resonance image is S1, S2, ..., Sn, and the value of the proportion of each material component is 2,…, n, the computer equipment can use the MatlabCurve Fitting toolbox to substitute the echo time and grayscale value of each magnetic resonance image and the proportion of each material component into the relaxation time estimation model to calculate the relaxation time of each material component.

[0073] In this embodiment, the proportion of each material component, the echo time and grayscale value of each magnetic resonance image can be used as known parameters, and the relaxation time of each material component can be used as an unknown variable and substituted into the relaxation time estimation model for calculation to accurately obtain the relaxation time of each material component.

[0074] In an optional embodiment, if Figure 4 As shown, a method for determining relaxation time is provided, which is applied to a computer device and includes:

[0075] S401, acquiring magnetic resonance images of the object to be measured at different echo times; the magnetic resonance images include at least two material components;

[0076] S402, detecting the number of material components in each magnetic resonance image;

[0077] S403, determining a grayscale estimation item of each material component according to the number of material components in each magnetic resonance image;

[0078] S404, constructing a preset relaxation time estimation model based on the grayscale estimation items of each material component;

[0079] S405 , the echo time and grayscale value of each magnetic resonance image are used as known parameters, and the proportion and relaxation time of each material component are used as unknown variables, and are substituted into a relaxation time estimation model for calculation to obtain the relaxation time of each material component.

[0080] In the above-mentioned relaxation time determination method, magnetic resonance images of the object to be measured are obtained at different echo times; the magnetic resonance images include at least two material components; and the relaxation time of each material component is determined based on the echo time and grayscale value of each magnetic resonance image, as well as the proportion of each material component in each magnetic resonance image. Because the magnetic resonance images of the embodiment of the present application include at least two material components, and the proportion of each material component in the magnetic resonance image is taken into account during the relaxation time determination process, the embodiment of the present application can accurately determine the relaxation time of each material component based on the echo time and grayscale value of each magnetic resonance image, as well as the proportion of each material component in each magnetic resonance image.

[0081] It should be understood that, although the steps in the flowcharts of the above embodiments are shown in sequence as indicated by the arrows, these steps are not necessarily performed in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and these steps can be performed in other orders. Moreover, at least a portion of the steps in the flowcharts of the above embodiments may include multiple steps or multiple stages, and these steps or stages are not necessarily performed at the same time, but can be performed at different times. The execution order of these steps or stages is not necessarily to be performed in sequence, but can be performed in turn or alternately with other steps or at least a portion of steps or stages in other steps.

[0082] In one embodiment, Figure 5 As shown, a magnetic resonance imaging system is provided, which includes an image acquisition device 21 and a computer device 22, and the image acquisition device 21 is connected to the computer device 22;

[0083] The image acquisition device 21 is used to acquire magnetic resonance images of the object to be measured at different echo times and send the magnetic resonance images to the computer device;

[0084] The computer device 22 is configured to execute the steps of the method for determining the relaxation time in any one of the above embodiments.

[0085] The magnetic resonance image includes at least two material components. The specific structural diagram of the computer device 22 can be referred to Figure 1 In the embodiment of the present application, the image acquisition device 21 can acquire magnetic resonance images of the object to be measured at different echo times in real time or at regular intervals, and send the magnetic resonance images of the object to be measured at different echo times to the computer device, so that the computer device 22 can receive the magnetic resonance images of the object to be measured at different echo times, and determine the relaxation time of each material component based on the echo time and grayscale value of each magnetic resonance image and the proportion of each material component in each magnetic resonance image.

[0086] Based on the same inventive concept, embodiments of the present application further provide a relaxation time determination device for implementing the aforementioned relaxation time determination method. The solution provided by this device is similar to the solution described in the aforementioned method. Therefore, the specific limitations of one or more relaxation time determination device embodiments provided below can be found in the limitations of the relaxation time determination method described above and will not be further elaborated here.

[0087] In an exemplary embodiment, Figure 6 As shown, a relaxation time determination device is provided, comprising: an acquisition module 31 and a determination module 32, wherein:

[0088] The acquisition module 31 is used to acquire magnetic resonance images of the object to be measured at different echo times; the magnetic resonance images include at least two material components.

[0089] The determination module 32 is configured to determine the relaxation time of each material component according to the echo time and grayscale value of each magnetic resonance image and the proportion of each material component in each magnetic resonance image.

[0090] In one embodiment, the determination module 32 includes:

[0091] A model building unit, used to build a preset relaxation time estimation model based on the grayscale estimation items of each material component;

[0092] The determination unit is configured to determine the relaxation time of each material component by using a relaxation time estimation model and based on the echo time and grayscale value of each magnetic resonance image and the proportion of each material component in each magnetic resonance image.

[0093] In one embodiment, the determining unit includes:

[0094] The first determination subunit is used to substitute the echo time and grayscale value of each magnetic resonance image as known parameters, and the proportion and relaxation time of each material component as unknown variables into the relaxation time estimation model for calculation to obtain the relaxation time of each material component.

[0095] In one embodiment, the determining unit includes:

[0096] The second determination subunit is used to substitute the proportion of each material component, the echo time and grayscale value of each magnetic resonance image as known parameters, and the relaxation time of each material component as an unknown variable into the relaxation time estimation model for calculation to obtain the relaxation time of each material component.

[0097] In one embodiment, the relaxation time determination device further comprises:

[0098] A detection module, for detecting the number of material components in each magnetic resonance image;

[0099] The grayscale estimation item determination module is used to determine the grayscale estimation item of each material component according to the number of material components in each magnetic resonance image.

[0100] In one embodiment, the magnetic resonance image includes a first material component and a second material component, and the relaxation time estimation model includes a first grayscale estimation item corresponding to the first material component and a second grayscale estimation item corresponding to the second material component; the first grayscale estimation item includes the relationship between the proportion of the first material component, the initial grayscale value, the echo time and the relaxation time; the second grayscale estimation item includes the relationship between the proportion of the second material component, the initial grayscale value, the echo time and the relaxation time.

[0101] Each module in the relaxation time determination device can be implemented in whole or in part by software, hardware, or a combination thereof. Each module can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in the computer device in the form of software, so that the processor can call and execute the corresponding operations of each module.

[0102] In an exemplary embodiment, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as shown in FIG. Figure 1As shown. The computer device includes a processor, memory, an input / output interface, a communication interface, a display unit, and an input device. The processor, memory, and input / output interface are connected via a system bus, and the communication interface, display unit, and input device are connected to the system bus via the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and computer program in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and external devices. The communication interface of the computer device is used to communicate with external terminals via wired or wireless means, and the wireless means can be implemented via Wi-Fi, a mobile cellular network, near field communication (NFC), or other technologies. When executed by the processor, the computer program implements a method for determining relaxation time. The display unit of the computer device is used to form a visually visible image, and can be a display screen, a projection device, or a virtual reality imaging device. The display screen can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covering the display screen, or a button, trackball or touchpad set on the computer device casing, or an external keyboard, touchpad or mouse.

[0103] Those skilled in the art will understand that Figure 1 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0104] In an exemplary embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the following steps are implemented:

[0105] Acquiring magnetic resonance images of the object to be tested at different echo times; the magnetic resonance images include at least two material components;

[0106] The relaxation time of each material component is determined according to the echo time and grayscale value of each magnetic resonance image and the proportion of each material component in each magnetic resonance image.

[0107] In one embodiment, the relaxation time of each material component is determined based on the echo time and grayscale value of each magnetic resonance image and the proportion of each material component in each magnetic resonance image. When the processor executes the computer program, the following steps are further implemented:

[0108] According to the grayscale estimation items of each material component, a preset relaxation time estimation model is constructed;

[0109] The relaxation time estimation model is used to determine the relaxation time of each material component based on the echo time and grayscale value of each magnetic resonance image and the proportion of each material component in each magnetic resonance image.

[0110] In one embodiment, the relaxation time estimation model is used to determine the relaxation time of each material component based on the echo time and grayscale value of each magnetic resonance image and the proportion of each material component in each magnetic resonance image. When the processor executes the computer program, the following steps are further performed:

[0111] The echo time and grayscale value of each magnetic resonance image are used as known parameters, and the proportion and relaxation time of each material component are used as unknown variables. They are substituted into the relaxation time estimation model for calculation to obtain the relaxation time of each material component.

[0112] In one embodiment, the relaxation time estimation model is used to determine the relaxation time of each material component based on the echo time and grayscale value of each magnetic resonance image and the proportion of each material component in each magnetic resonance image. When the processor executes the computer program, the following steps are further performed:

[0113] The proportion of each material component, the echo time and grayscale value of each magnetic resonance image are used as known parameters, and the relaxation time of each material component is used as an unknown variable. They are substituted into the relaxation time estimation model for calculation to obtain the relaxation time of each material component.

[0114] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0115] Detecting the number of material components in each magnetic resonance image;

[0116] A grayscale estimation item for each material component is determined based on the number of portions of the material component in each magnetic resonance image.

[0117] In one embodiment, the magnetic resonance image includes a first material component and a second material component, and the relaxation time estimation model includes a first grayscale estimation item corresponding to the first material component and a second grayscale estimation item corresponding to the second material component; the first grayscale estimation item includes the relationship between the proportion of the first material component, the initial grayscale value, the echo time and the relaxation time; the second grayscale estimation item includes the relationship between the proportion of the second material component, the initial grayscale value, the echo time and the relaxation time.

[0118] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the following steps are implemented:

[0119] Acquiring magnetic resonance images of the object to be tested at different echo times; the magnetic resonance images include at least two material components;

[0120] The relaxation time of each material component is determined according to the echo time and grayscale value of each magnetic resonance image and the proportion of each material component in each magnetic resonance image.

[0121] In one embodiment, the relaxation time of each material component is determined based on the echo time and grayscale value of each magnetic resonance image and the proportion of each material component in each magnetic resonance image. When executed by the processor, the computer program further implements the following steps:

[0122] According to the grayscale estimation items of each material component, a preset relaxation time estimation model is constructed;

[0123] The relaxation time estimation model is used to determine the relaxation time of each material component based on the echo time and grayscale value of each magnetic resonance image and the proportion of each material component in each magnetic resonance image.

[0124] In one embodiment, the relaxation time estimation model is used to determine the relaxation time of each material component based on the echo time and grayscale value of each magnetic resonance image and the proportion of each material component in each magnetic resonance image. When executed by the processor, the computer program further implements the following steps:

[0125] The echo time and grayscale value of each magnetic resonance image are used as known parameters, and the proportion and relaxation time of each material component are used as unknown variables. They are substituted into the relaxation time estimation model for calculation to obtain the relaxation time of each material component.

[0126] In one embodiment, the relaxation time estimation model is used to determine the relaxation time of each material component based on the echo time and grayscale value of each magnetic resonance image and the proportion of each material component in each magnetic resonance image. When executed by the processor, the computer program further implements the following steps:

[0127] The proportion of each material component, the echo time and grayscale value of each magnetic resonance image are used as known parameters, and the relaxation time of each material component is used as an unknown variable. They are substituted into the relaxation time estimation model for calculation to obtain the relaxation time of each material component.

[0128] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0129] Detecting the number of material components in each magnetic resonance image;

[0130] A grayscale estimation item for each material component is determined based on the number of portions of the material component in each magnetic resonance image.

[0131] In one embodiment, the magnetic resonance image includes a first material component and a second material component, and the relaxation time estimation model includes a first grayscale estimation item corresponding to the first material component and a second grayscale estimation item corresponding to the second material component; the first grayscale estimation item includes the relationship between the proportion of the first material component, the initial grayscale value, the echo time and the relaxation time; the second grayscale estimation item includes the relationship between the proportion of the second material component, the initial grayscale value, the echo time and the relaxation time.

[0132] In one embodiment, a computer program product is provided, comprising a computer program, which, when executed by a processor, implements the following steps:

[0133] Acquiring magnetic resonance images of the object to be tested at different echo times; the magnetic resonance images include at least two material components;

[0134] The relaxation time of each material component is determined according to the echo time and grayscale value of each magnetic resonance image and the proportion of each material component in each magnetic resonance image.

[0135] In one embodiment, the relaxation time of each material component is determined based on the echo time and grayscale value of each magnetic resonance image and the proportion of each material component in each magnetic resonance image. When executed by the processor, the computer program further implements the following steps:

[0136] According to the grayscale estimation items of each material component, a preset relaxation time estimation model is constructed;

[0137] The relaxation time estimation model is used to determine the relaxation time of each material component based on the echo time and grayscale value of each magnetic resonance image and the proportion of each material component in each magnetic resonance image.

[0138] In one embodiment, the relaxation time estimation model is used to determine the relaxation time of each material component based on the echo time and grayscale value of each magnetic resonance image and the proportion of each material component in each magnetic resonance image. When executed by the processor, the computer program further implements the following steps:

[0139] The echo time and grayscale value of each magnetic resonance image are used as known parameters, and the proportion and relaxation time of each material component are used as unknown variables. They are substituted into the relaxation time estimation model for calculation to obtain the relaxation time of each material component.

[0140] In one embodiment, the relaxation time estimation model is used to determine the relaxation time of each material component based on the echo time and grayscale value of each magnetic resonance image and the proportion of each material component in each magnetic resonance image. When executed by the processor, the computer program further implements the following steps:

[0141] The proportion of each material component, the echo time and grayscale value of each magnetic resonance image are used as known parameters, and the relaxation time of each material component is used as an unknown variable. They are substituted into the relaxation time estimation model for calculation to obtain the relaxation time of each material component.

[0142] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0143] Detecting the number of material components in each magnetic resonance image;

[0144] A grayscale estimation item for each material component is determined based on the number of portions of the material component in each magnetic resonance image.

[0145] In one embodiment, the magnetic resonance image includes a first material component and a second material component, and the relaxation time estimation model includes a first grayscale estimation item corresponding to the first material component and a second grayscale estimation item corresponding to the second material component; the first grayscale estimation item includes the relationship between the proportion of the first material component, the initial grayscale value, the echo time and the relaxation time; the second grayscale estimation item includes the relationship between the proportion of the second material component, the initial grayscale value, the echo time and the relaxation time.

[0146] It should be noted that the user information (including but not limited to relevant information of the object to be tested, user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0147] Those skilled in the art will understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, database or other media used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The databases involved in the various embodiments provided herein may include at least one of a relational database and a non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the various embodiments provided herein may be, but are not limited to, general-purpose processors, central processing units (CPUs), graphics processing units (GPUs), digital signal processors (DSPs), programmable logic devices (PLDs), quantum computing-based data processing logic devices, artificial intelligence (AI) processors, and the like.

[0148] The technical features of the above embodiments can be combined arbitrarily. In order to make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0149] The above embodiments merely illustrate several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that a person skilled in the art may make various modifications and improvements without departing from the spirit of the present invention, all of which fall within the scope of protection of the present application. Therefore, the scope of protection of the present application shall be determined by the appended claims.

Claims

1. A method for determining relaxation time, characterized in that: The method comprises: Acquiring magnetic resonance images of the object to be measured at different echo times; the magnetic resonance images include at least two material components; The relaxation time of each of the material components is determined according to the echo time and the grayscale value of each of the magnetic resonance images and the proportion of each of the material components in each of the magnetic resonance images.

2. The method according to claim 1, characterized in that Determining the relaxation time of each of the material components according to the echo time and the grayscale value of each of the magnetic resonance images and the proportion of each of the material components in each of the magnetic resonance images includes: Constructing a preset relaxation time estimation model based on the grayscale estimation items of each of the material components; The relaxation time estimation model is used to determine the relaxation time of each material component based on the echo time and grayscale value of each magnetic resonance image and the proportion of each material component in each magnetic resonance image.

3. The method according to claim 2, characterized in that The method of using the relaxation time estimation model and determining the relaxation time of each material component based on the echo time and grayscale value of each magnetic resonance image and the proportion of each material component in each magnetic resonance image includes: The echo time and grayscale value of each magnetic resonance image are used as known parameters, and the proportion and relaxation time of each material component are used as unknown variables. These are substituted into the relaxation time estimation model for calculation to obtain the relaxation time of each material component.

4. The method according to claim 2, characterized in that The method of using the relaxation time estimation model and determining the relaxation time of each material component based on the echo time and grayscale value of each magnetic resonance image and the proportion of each material component in each magnetic resonance image includes: The proportion of each material component, the echo time and the grayscale value of each magnetic resonance image are used as known parameters, and the relaxation time of each material component is used as an unknown variable. The parameters are substituted into the relaxation time estimation model for calculation to obtain the relaxation time of each material component.

5. The method according to any one of claims 2 to 4, characterized in that The method further comprises: detecting the number of material components in each of the magnetic resonance images; A grayscale estimation item of each material component is determined according to the number of material components in each magnetic resonance image.

6. The method according to any one of claims 2 to 4, characterized in that The magnetic resonance image includes a first material component and a second material component, and the relaxation time estimation model includes a first grayscale estimation item corresponding to the first material component and a second grayscale estimation item corresponding to the second material component; the first grayscale estimation item includes the relationship between the proportion of the first material component, the initial grayscale value, the echo time and the relaxation time; the second grayscale estimation item includes the relationship between the proportion of the second material component, the initial grayscale value, the echo time and the relaxation time.

7. A device for determining relaxation time, characterized in that: The device comprises: An acquisition module, configured to acquire magnetic resonance images of the object under test at different echo times; the magnetic resonance images include at least two material components; The determination module is configured to determine the relaxation time of each of the material components according to the echo time and grayscale value of each of the magnetic resonance images and the proportion of each of the material components in each of the magnetic resonance images.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

9. 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 method according to any one of claims 1 to 6 are implemented.

10. A magnetic resonance imaging system, characterized in that: The magnetic resonance imaging system includes an image acquisition device and a computer device, wherein the image acquisition device is connected to the computer device; The image acquisition device is used to acquire magnetic resonance images of the object to be measured at different echo times, and send the magnetic resonance images to the computer device; The computer device is configured to execute the steps of the method for determining the relaxation time according to any one of claims 1 to 6.

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