Methods, systems, media, and electronic devices for locating epileptic lesions

Abstract

This invention provides a method, system, medium, and electronic device for locating epileptic lesions. The method includes the following steps: reconstructing a non-magnetic perturbation transverse relaxation rate (R2) image based on multi-echo spin echo data from the brain; constructing a paramagnetic brain iron image based on the multi-echo gradient echo data from the brain, the non-magnetic perturbation transverse relaxation rate (R2) image, and an amplitude attenuation kernel; updating the amplitude attenuation kernel based on the paramagnetic brain iron image; updating the paramagnetic brain iron image based on the updated amplitude attenuation kernel until both the paramagnetic brain iron image and the amplitude attenuation kernel converge; and locating the epileptic lesion based on the converged paramagnetic brain iron image. The epileptic lesion localization method, system, medium, and electronic device of this invention achieves epileptic lesion localization based on paramagnetic brain iron images, effectively improving localization accuracy and efficiency.

Description

Technical Field

[0001] This invention relates to the field of biomedical engineering, and in particular to a method, system, medium, and electronic device for locating epileptic lesions. Background Technology

[0002] Epilepsy, one of the most common and critical neurological disorders, is characterized by recurrent, unpredictable seizures caused by abnormal neuronal activity. This condition can occur at any age and can cause a variety of symptoms, including loss of consciousness, seizures, and behavioral changes.

[0003] The pathogenesis of epilepsy is complex and diverse, but research shows that iron plays a crucial role in the central nervous system, influencing the seizure process both directly and indirectly, and is of significant pathophysiological importance. For example, stroke, neurological trauma, and intracranial hemorrhage can all trigger seizures. These conditions are often associated with increased permeability of the blood-brain barrier in epilepsy patients, allowing iron in the form of hemosiderin, ferritin, and hemoglobin to leak into tissues. Iron metabolism disorders are closely linked to oxidative stress, which is an important marker of many structural, genetic, or immune-related epilepsy subtypes. Oxidative stress not only exacerbates dysfunction and damage to central nervous system cells but also promotes iron overload and ferroptosis. Iron overload can further promote lipid peroxidation, impair protein function, and, in conjunction with elevated extracellular glutamate levels, may cause a redistribution of iron in the cortex and subcortical structures. In addition, pharmacological effects such as reducing iron deposition, altering ferritin levels, and alleviating oxidative damage can alleviate iron-mediated epileptic symptoms. It is noteworthy that iron-mediated neurotoxicity is not only correlated with seizure intensity, but its spatial distribution characteristics may also reveal the core location of the epileptogenic network. Therefore, specific dynamic monitoring of intracranial iron content is crucial for achieving accurate diagnosis and treatment of epilepsy.

[0004] Given the central role of iron in the pathogenesis of epilepsy, developing a specific and non-invasive in vivo iron localization technique is crucial. Magnetic Resonance Imaging (MRI), with its superior contrast and high-resolution imaging capabilities, provides a comprehensive pathway for acquiring in vivo information. However, current MRI iron imaging techniques face several significant limitations. For example, although methods such as susceptibility-weighted imaging (SWI), R2* relaxation rate, and quantitative susceptibility mapping (QSM) have been attempted to quantify iron content in the brains of epilepsy patients, these techniques lack sufficient specificity to distinguish paramagnetic iron deposits from diamagnetic substances (such as calcifications) due to interference from other magnetic components in brain tissue (such as calcifications). This limitation results in unsatisfactory sensitivity and specificity for iron detection in clinical settings. Therefore, developing new techniques or improving existing techniques to effectively overcome these limitations is essential to improve the diagnostic accuracy of epilepsy-related iron abnormalities. Summary of the Invention

[0005] In view of the above-mentioned problems, the purpose of this invention is to provide a method, system, medium, and electronic device for locating epileptic lesions, which realizes the localization of epileptic lesions based on paramagnetic brain iron imaging, effectively improving the localization accuracy and efficiency.

[0006] In a first aspect, the present invention provides a method for locating epileptic lesions, the method comprising the following steps: reconstructing a non-magnetic perturbation transverse relaxation rate R2 image based on magnetic resonance multi-echo spin echo data of the brain; constructing a paramagnetic brain iron image based on the magnetic resonance multi-echo gradient echo data of the brain, the non-magnetic perturbation transverse relaxation rate R2 image, and an amplitude attenuation kernel; updating the amplitude attenuation kernel based on the paramagnetic brain iron image; updating the paramagnetic brain iron image based on the updated amplitude attenuation kernel until both the paramagnetic brain iron image and the amplitude attenuation kernel converge; and locating the epileptic lesion based on the converged paramagnetic brain iron image.

[0007] In one implementation of the first aspect, reconstructing a non-magnetic perturbation transverse relaxation rate R2 image based on brain magnetic resonance multi-echo spin echo data includes:

[0008] The magnetic resonance multi-echo spin echo data were fitted to obtain the non-magnetic field perturbation transverse relaxation rate R2 image. Where M0 represents the proton density distribution, TE represents the echo time, and R2 represents the transverse relaxation decay rate of the non-magnetic field disturbance.

[0009] In one implementation of the first aspect, constructing a paramagnetic brain iron image based on the brain's magnetic resonance multi-echo gradient echo data, the non-magnetic perturbation transverse relaxation rate R2 image, and the amplitude attenuation kernel includes the following steps:

[0010] The gradient echo signal of the j-th echo in the magnetic resonance multi-echo gradient echo data is set. Where M0 represents the proton density distribution, a represents the amplitude decay kernel, and φ res Represents the residual phase unaffected by echo time, γ represents the gyromagnetic ratio, D represents the dipole nucleus in the direction of the main magnetic field, and χ represents the residual phase unaffected by echo time. para Indicating paramagnetic brain iron imaging, χ other This represents images of other magnetic materials, B0 represents magnetic flux density, and TE represents magnetic flux density. j Rj represents the echo time of the j-th echo, R2 represents the transverse relaxation decay rate of the non-magnetic field disturbance, and 2πf bg TE j This represents the background field phase signal generated by the j-th echo;

[0011] The gradient echo signal S(TE) is solved based on the objective function. j To obtain paramagnetic brain images, the objective function is:

[0012] Where N represents the total number of echoes in each scan. This represents the unwound phase signal at the j-th echo time. The transverse relaxation decay rate of the magnetic field disturbance is represented by λ1, λ2, and λ3, which represent weighting coefficients, and f is the weighting coefficient. bg χ represents the background field generated by non-brain tissue, χ represents the total magnetic susceptibility, TV(·) represents the total variational regularization operator, and |‖‖| represents the norm.

[0013] In one implementation of the first aspect, according to Get The value of M, where M j This represents the gradient echo signal amplitude of the j-th echo.

[0014] In one implementation of the first aspect, the background field phase signal is obtained by the following steps:

[0015] Phase unwrapping of the phase signal of the magnetic resonance multi-echo gradient echo data is performed based on the Laplace operator;

[0016] The background field phase signal is obtained by fitting the phase signal after phase unwrapping based on the spherical harmonic function algorithm.

[0017] In one implementation of the first aspect, updating the amplitude attenuation kernel based on the paramagnetic brain image includes:

[0018] according to Obtain the updated amplitude decay kernel a, where R2 represents the transverse relaxation decay rate of the non-magnetic field disturbance. χ represents the transverse relaxation decay rate of the magnetic field disturbance. para Indicating paramagnetic brain iron imaging, χ other || represents the image of other magnetic materials.

[0019] In one implementation of the first aspect, locating epileptic lesions based on convergent paramagnetic brain iron images includes the following steps:

[0020] Set a threshold for lesions;

[0021] In the converged paramagnetic brain iron image, regions with an intensity greater than the lesion threshold are identified as epileptic lesions.

[0022] In a second aspect, the present invention provides an epileptic lesion localization system, the system comprising a reconstruction module, a construction module, an update module, an iteration module and a localization module;

[0023] The reconstruction module is used to reconstruct the non-magnetic field perturbation transverse relaxation rate R2 image based on magnetic resonance multi-echo spin echo data of the brain.

[0024] The construction module is used to construct paramagnetic brain iron images based on the magnetic resonance multi-echo gradient echo data of the brain, the non-magnetic field perturbation transverse relaxation rate R2 image, and the amplitude attenuation kernel.

[0025] The update module is used to update the amplitude attenuation kernel based on the paramagnetic brain iron image;

[0026] The iterative module is used to update the paramagnetic brain image based on the updated amplitude attenuation kernel until both the paramagnetic brain image and the amplitude attenuation kernel converge.

[0027] The localization module is used to locate epileptic foci based on convergent paramagnetic brain iron images.

[0028] Thirdly, the present invention provides a storage medium on which a computer program is stored, which, when executed by a processor, implements the above-described method for locating epileptic lesions.

[0029] Fourthly, the present invention provides an electronic device, comprising: a processor and a memory;

[0030] The memory is used to store computer programs;

[0031] The processor is used to execute the computer program stored in the memory, so that the electronic device performs the above-described method for locating epileptic lesions.

[0032] As described above, the epilepsy lesion localization method, system, medium, and electronic device of the present invention have the following beneficial effects:

[0033] (1) Based on dual-modal data of multi-echo gradient echo (mGRE) and multi-echo spin echo (mSE), paramagnetic brain iron imaging was performed, which enabled precise localization of epileptic lesions.

[0034] (2) Based on paramagnetic magnetic susceptibility imaging, specific imaging reconstruction of brain iron content is achieved, which can accurately measure brain iron level and solve the problem of difficulty in distinguishing other magnetic substances coexisting in the same voxel in traditional methods.

[0035] (3) The use of automated processes greatly reduces the impact of human operation and subjective judgment, improves positioning efficiency and positioning accuracy, and has important clinical practice value;

[0036] (4) The output data is compatible with the DICOM standard and can be directly connected to the preoperative navigation system to support the entire process of decision-making from diagnosis to treatment. Attached Figure Description

[0037] Figure 1 The flowchart shown is an embodiment of the epilepsy lesion localization method of the present invention;

[0038] Figure 2 The image shown is a schematic diagram of a paramagnetic brain iron imaging model of the present invention in one embodiment;

[0039] Figure 3 A schematic diagram showing paramagnetic brain iron images of a typical epilepsy patient in one embodiment;

[0040] Figure 4 The diagram shown is a schematic diagram of the location of an epileptic focus in one embodiment of the epileptic focus location method of the present invention;

[0041] Figure 5 The diagram shows a comparison of epileptic lesions between paramagnetic brain iron images and PET images in one embodiment of the present invention.

[0042] Figure 6 The diagram shown is a structural schematic of the epilepsy lesion localization system of the present invention in one embodiment;

[0043] Figure 7 The diagram shown is a structural schematic of an embodiment of the electronic device of the present invention. Detailed Implementation

[0044] The following specific examples illustrate the implementation of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that, unless otherwise specified, the following embodiments and features described therein can be combined with each other.

[0045] It should be noted that the illustrations provided in the following embodiments are only schematic representations of the basic concept of the present invention. Therefore, the drawings only show the components related to the present invention and are not drawn according to the actual number, shape and size of the components in the actual implementation. In the actual implementation, the form, quantity and proportion of each component can be arbitrarily changed, and the layout of the components may also be more complex.

[0046] The epilepsy lesion localization method, system, medium, and electronic device of the present invention utilize the unique influence of the paramagnetic properties of iron on magnetic resonance signals. By accelerating the magnetization dephase process, the signal amplitude is attenuated, and characteristic phase accumulation is generated as the echo time increases, thereby constructing an iron-specific magnetic susceptibility separation model and ultimately realizing the localization of iron-specific epilepsy lesions.

[0047] The technical solutions of the present invention will now be described in detail with reference to the accompanying drawings.

[0048] like Figure 1 As shown, in one embodiment, the epilepsy lesion localization method of the present invention includes steps S1-S5.

[0049] Step S1: Reconstruct the non-magnetic field perturbation transverse relaxation rate R2 image based on brain magnetic resonance multi-echo spin echo data.

[0050] Specifically, the non-magnetic field disturbance transverse relaxation rate R2 image is obtained by fitting a multi-echo spin echo image. As the echo time increases, the amplitude of the multi-echo spin echo signal gradually decays. The non-magnetic field disturbance transverse relaxation rate R2 image is fitted using a single exponential decay model. The fitting process is as follows: Where M0 represents the proton density distribution, TE represents the echo time, and R2 represents the transverse relaxation decay rate of the non-magnetic field disturbance.

[0051] Step S2: Construct a paramagnetic brain iron image based on the magnetic resonance multi-echo gradient echo data of the brain, the non-magnetic field perturbation transverse relaxation rate R2 image, and the amplitude attenuation kernel.

[0052] Specifically, multi-echo gradient echo sequences are a variant of gradient echo sequences that generate images by acquiring multiple echoes within a single TR cycle. This technique has significant applications in MRI, particularly when acquiring a wide range of contrast information. The MRI multi-echo gradient echo data includes amplitude and phase signals, which can be used to establish susceptibility equations for paramagnetic brain iron and other magnetic materials. Figure 2 As shown, the red spheres represent the distribution of iron within the voxel; all materials are modeled as ideal spheres. Paramagnetic materials (χ²) para ) and other magnetic materials (χ other All of these will interfere with the magnetic field, causing the amplitude signal of the magnetic resonance multi-echo gradient echo data to vary with the echo time (TE). j This leads to attenuation. Simultaneously, the phase signals generated by these materials with different magnetic properties may partially or completely cancel each other out, affecting the overall phase signal of the acquired magnetic resonance multi-echo gradient echo data. Furthermore, the transverse relaxation attenuation rate R² of the tissue's inherent non-magnetic perturbation, independent of magnetic field disturbance, and the background field phase signal (2πf) must also be considered. bg TE j Therefore, given a magnetic flux density (B0), the gradient echo signal of the j-th echo of the magnetic resonance multi-echo gradient echo data is expressed as:

[0053]

[0054] Where M0 represents the proton density distribution; a represents the amplitude decay nucleus, indicating the ability of the magnetic susceptibility material to influence the relaxation decay rate; φ res Represents the residual phase unaffected by echo time, γ represents the gyromagnetic ratio, D represents the dipole nucleus in the direction of the main magnetic field, and χ represents the residual phase unaffected by echo time. para Indicating paramagnetic brain iron imaging, χ other This represents images of other magnetic materials, B0 represents magnetic flux density, and TE represents magnetic flux density. j Rj represents the echo time of the j-th echo, R2 represents the transverse relaxation decay rate of the non-magnetic field disturbance, and 2πf bg TE j Let || represent the background field phase signal generated by the j-th echo, and || represent the absolute value operation.

[0055] In this invention, the transverse relaxation decay rate of the magnetic field disturbance The solution can be obtained by modeling using a single exponential model, i.e., based on... Get The value of M, where M j The gradient echo signal amplitude of the j-th echo is represented by N, and N represents the total number of echoes in each scan.

[0056] In this invention, the phase signal of the magnetic resonance multi-echo gradient echo data is unwrapped based on the Laplace operator, and the unwrapped phase signal is fitted based on the Sophisticated Harmonic Artifact Reduction for Phase data with Variable-kernel (V-SHARP) algorithm to obtain the background field phase signal 2πf. bg TE j .

[0057] Based on the assumption that the magnetic material is an ideal sphere, the amplitude attenuation kernel 'a' is initially set to a value, such as 323.5 Hz / ppm. Then, the obtained background field phase... Substitute R² into the objective function. Solve for the gradient echo signal based on the objective function. To obtain initial paramagnetic brain iron images. Specifically, the objective function is:

[0058]

[0059] in f represents the transverse relaxation decay rate of the magnetic field disturbance. λ1, λ2, and λ3 represent weighting coefficients, where λ1 represents the weight of the regularization term in solving the first term of the formula, λ2 represents the weight of the regularization term in solving the third term of the formula, and λ3 represents the weight of the total variational regularization term (TV(·)) in solving the formula. bg χ represents the background field generated by non-brain tissue, χ represents the total magnetic susceptibility, TV(·) represents the total variational regularization operator, and |‖‖| represents the norm.

[0060] Step S3: Update the amplitude attenuation kernel based on the paramagnetic brain iron image.

[0061] Specifically, due to the different transverse relaxation rates of different tissues to magnetic field disturbances The influence capabilities of each cell differ, therefore the amplitude attenuation nucleus of each voxel needs to be recalculated for the obtained paramagnetic brain iron images.

[0062] Step S4: Update the paramagnetic brain image based on the updated amplitude attenuation kernel until both the paramagnetic brain image and the amplitude attenuation kernel converge.

[0063] Specifically, after the amplitude attenuation kernel is updated, paramagnetic brain images are acquired again based on the objective function; then, the amplitude attenuation kernel is updated again based on the updated paramagnetic brain images. This process of alternating iterative calculation of the amplitude attenuation kernel and the paramagnetic brain images continues until both converge. The converged paramagnetic brain image is then the final high-quality paramagnetic brain image. Figure 3 The image shown is a paramagnetic brain iron image calculated from the magnetic resonance imaging data of a representative patient.

[0064] Preferably, if the absolute difference between the current amplitude attenuation kernel and the previous amplitude attenuation kernel is less than a preset difference (e.g., 0.3 Hz / ppm / voxel), and the tolerance of the objective function is less than a preset tolerance (e.g., 0.3), it is determined that both the paramagnetic brain iron image and the amplitude attenuation kernel have converged.

[0065] Step S5: Locate the epileptic focus based on convergent paramagnetic brain iron images.

[0066] Specifically, this invention uses a threshold segmentation method to locate epileptic foci in the cortical region. First, a foci threshold is set, such as 0.02 ppm (parts per million, dimensionless). Then, in the converged paramagnetic brain iron image, regions with intensity greater than the foci threshold are identified as epileptic foci. Figure 4 This is a schematic diagram of the epileptic lesion location obtained based on the threshold segmentation method.

[0067] like Figure 5 As shown, the localization results of the epilepsy lesion localization method of the present invention are highly consistent with the localization results of positron emission tomography (PET), and paramagnetic brain iron imaging can provide more accurate lesion localization.

[0068] The scope of protection of the epileptic lesion localization method described in this embodiment is not limited to the execution order of the steps listed in this embodiment. Any solution implemented by adding, subtracting, or replacing steps in the prior art based on the principle of this invention is included within the scope of protection of this invention.

[0069] This invention also provides an epilepsy lesion localization system, which can implement the epilepsy lesion localization method described in this invention. However, the implementation device of the epilepsy lesion localization system described in this invention includes, but is not limited to, the structure of the epilepsy lesion localization system listed in this embodiment. All structural modifications and substitutions of the prior art made according to the principles of this invention are included within the protection scope of this invention.

[0070] like Figure 6 As shown, in one embodiment, the epilepsy lesion localization system of the present invention includes a reconstruction module 61, a construction module 62, an update module 63, an iteration module 64, and a localization module 65.

[0071] The reconstruction module 61 is used to reconstruct the non-magnetic field perturbation transverse relaxation rate R2 image based on magnetic resonance multi-echo spin echo data of the brain.

[0072] The construction module 62 is connected to the reconstruction module 61 and is used to construct a paramagnetic brain iron image based on the magnetic resonance multi-echo gradient echo data of the brain, the non-magnetic field perturbation transverse relaxation rate R2 image, and the amplitude attenuation kernel.

[0073] The update module 63 is connected to the construction module 62 and is used to update the amplitude attenuation kernel based on the paramagnetic brain iron image.

[0074] The iteration module 64 is connected to the update module 63 and is used to update the paramagnetic brain image based on the updated amplitude attenuation kernel until both the paramagnetic brain image and the amplitude attenuation kernel converge.

[0075] The localization module 65 is connected to the iteration module 64 and is used to locate epileptic lesions based on convergent paramagnetic brain iron images.

[0076] The structure and principle of the reconstruction module 61, construction module 62, update module 63, iteration module 64 and positioning module 65 correspond one-to-one with the above-mentioned epileptic lesion positioning method, so they will not be described in detail here.

[0077] In the embodiments provided by this invention, it should be understood that the disclosed systems, apparatuses, or methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative. For instance, the division of modules / units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules or units may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection of apparatuses or modules or units may be electrical, mechanical, or other forms.

[0078] The modules / units described as separate components may or may not be physically separate. The components shown as modules / units may or may not be physical modules; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules / units can be selected to achieve the objectives of the embodiments of the present invention, depending on actual needs. For example, the functional modules / units in the various embodiments of the present invention may be integrated into one processing module, or each module / unit may exist physically separately, or two or more modules / units may be integrated into one module / unit.

[0079] Those skilled in the art will further recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0080] This invention also provides a computer-readable storage medium. Those skilled in the art will understand that all or part of the steps in the epilepsy lesion localization method of the above embodiments can be implemented by a program instructing a processor. The program can be stored in a computer-readable storage medium, which is a non-transitory medium, such as random access memory, read-only memory, flash memory, hard disk, solid-state drive, magnetic tape, floppy disk, optical disk, and any combination thereof. The storage medium can be any available medium accessible to a computer or a data storage device such as a server or data center that integrates one or more available media. This available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., digital video disc (DVD)), or a semiconductor medium (e.g., solid-state disk (SSD)).

[0081] This invention also provides an electronic device. The electronic device includes a processor and a memory.

[0082] The memory is used to store computer programs.

[0083] The memory includes various media capable of storing program code, such as ROM, RAM, magnetic disk, USB flash drive, memory card, or optical disk.

[0084] The processor is connected to the memory and is used to execute the computer program stored in the memory so that the electronic device performs the above-described method for locating epileptic lesions.

[0085] Preferably, the processor can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0086] like Figure 7 As shown, the electronic device of the present invention is embodied in the form of a general-purpose computing device. The components of the electronic device may include, but are not limited to: one or more processors or processing units 71, a memory 72, and a bus 73 connecting different system components (including the memory 72 and the processing unit 71).

[0087] Bus 73 represents one or more of several bus architectures, including a memory bus or memory controller, a peripheral bus, a graphics acceleration port, a processor, or a local bus using any of the various bus architectures. Examples of these architectures include, but are not limited to, the Industry Standard Architecture (ISA) bus, the Micro Channel Architecture (MAC) bus, the Enhanced ISA bus, the Video Electronics Standards Association (VESA) local bus, and the Peripheral Component Interconnect (PCI) bus.

[0088] Electronic devices typically include a variety of computer-readable media. These media can be any available media that can be accessed by the electronic device, including volatile and non-volatile media, and removable and non-removable media.

[0089] Memory 72 may include computer system readable media in the form of volatile memory, such as random access memory (RAM) 721 and / or cache memory 722. The electronic device may further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, storage system 723 may be used to read and write non-removable, non-volatile magnetic media (…). Figure 7 Not shown; usually referred to as a "hard drive"). Although Figure 7Not shown, a disk drive for reading and writing to a removable non-volatile disk (e.g., a "floppy disk") and an optical disk drive for reading and writing to a removable non-volatile optical disk (e.g., a CD-ROM, DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to bus 73 via one or more data media interfaces. Memory 72 may include at least one program product having a set (e.g., at least one) of program modules configured to perform the functions of the embodiments of the present invention.

[0090] A program / utility 724 having a set (at least one) of program modules 7241 may be stored, for example, in memory 72. Such program modules 7241 include, but are not limited to, an operating system, one or more application programs, other program modules, and program data. Each or some combination of these examples may include an implementation of a network environment. Program modules 7241 typically perform the functions and / or methods described in the embodiments of the present invention.

[0091] The electronic device can also communicate with one or more external devices (e.g., keyboard, pointing device, display, etc.), one or more devices that enable a user to interact with the electronic device, and / or any device that enables the electronic device to communicate with one or more other computing devices (e.g., network interface card, modem, etc.). This communication can be performed through input / output (I / O) interface 74. Furthermore, the electronic device can also communicate with one or more networks (e.g., local area network (LAN), wide area network (WAN), and / or public networks, such as the Internet) through network adapter 75. Figure 7 As shown, network adapter 75 communicates with other modules of the electronic device via bus 73. It should be understood that, although not shown in the figure, other hardware and / or software modules may be used in conjunction with the electronic device, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0092] The above embodiments are merely illustrative of the principles and effects of the present invention and are not intended to limit the invention. Any person skilled in the art can modify or alter the above embodiments without departing from the spirit and scope of the present invention. Therefore, all equivalent modifications or alterations made by those skilled in the art without departing from the spirit and technical concept disclosed in the present invention should still be covered by the claims of the present invention.

Claims

1. A method for locating epileptic lesions, characterized in that: The method includes the following steps: Reconstruction of non-magnetic field perturbation transverse relaxation rate R2 image based on brain magnetic resonance multi-echo spin echo data; Paramagnetic brain iron images were constructed based on the magnetic resonance multi-echo gradient echo data of the brain, the non-magnetic field perturbation transverse relaxation rate R2 image, and the amplitude attenuation kernel. The amplitude attenuation kernel is updated based on the paramagnetic brain iron images; The paramagnetic brain image is updated based on the updated amplitude attenuation kernel until both the paramagnetic brain image and the amplitude attenuation kernel converge. Localization of epileptic lesions based on convergent paramagnetic brain iron images; Reconstruction of non-magnetic perturbation transverse relaxation rate R2 images based on brain MRI multi-echo spin echo data includes: The magnetic resonance multi-echo spin echo data were fitted to obtain the non-magnetic field perturbation transverse relaxation rate R2 image. Where M0 represents the proton density distribution, TE represents the echo time, and R2 represents the transverse relaxation decay rate of the non-magnetic field disturbance. Constructing a paramagnetic brain iron image based on the brain's magnetic resonance multi-echo gradient echo data, the non-magnetic perturbation transverse relaxation rate R2 image, and the amplitude attenuation kernel includes the following steps: The gradient echo signal of the j-th echo in the magnetic resonance multi-echo gradient echo data is set. Where M0 represents the proton density distribution, a represents the amplitude decay kernel, and φ res Represents the residual phase unaffected by echo time, γ represents the gyromagnetic ratio, D represents the dipole nucleus in the direction of the main magnetic field, and χ represents the residual phase unaffected by echo time. para Indicating paramagnetic brain iron imaging, χ othe This represents images of other magnetic materials, B0 represents magnetic flux density, and TE represents magnetic flux density. j Rj represents the echo time of the j-th echo, R2 represents the transverse relaxation decay rate of the non-magnetic field disturbance, and 2πf bg TE j This represents the background field phase signal generated by the j-th echo; The gradient echo signal S(TE) is solved based on the objective function. j To obtain paramagnetic brain images, the objective function is: In this context, N represents the total number of echoes in each scan. This represents the unwound phase signal at the j-th echo time. The transverse relaxation decay rate of the magnetic field disturbance is represented by λ1, λ2, and λ3, which represent weighting coefficients, and f is the weighting coefficient. bg Let χ denote the background field generated by non-brain tissue, χ denote the total magnetic susceptibility, TV(·) denote the total variational regularization operator, |||| denote the norm, and argmin denote the χ that minimizes the function. para .

2. The method for locating epileptic lesions according to claim 1, characterized in that: according to Get The value of M, where M j This represents the gradient echo signal amplitude of the j-th echo.

3. The method for locating epileptic lesions according to claim 1, characterized in that: The background field phase signal is obtained using the following steps: Phase unwrapping of the phase signal of the magnetic resonance multi-echo gradient echo data is performed based on the Laplace operator; The background field phase signal is obtained by fitting the phase signal after phase unwrapping based on the spherical harmonic function algorithm.

4. The method for locating epileptic lesions according to claim 1, characterized in that: Updating the amplitude attenuation kernel based on the paramagnetic brain imaging includes: according to Obtain the updated amplitude decay kernel 'a', where R2 represents the transverse relaxation decay rate of the non-magnetic field disturbance. χ represents the transverse relaxation decay rate of the magnetic field disturbance. para Indicating paramagnetic brain iron imaging, χ other || represents the image of other magnetic materials.

5. The method for locating epileptic lesions according to claim 1, characterized in that: Localizing epileptic lesions based on convergent paramagnetic brain iron images includes the following steps: Set a threshold for lesions; In the converged paramagnetic brain iron image, regions with an intensity greater than the lesion threshold are identified as epileptic lesions.

6. An epileptic lesion localization system, characterized in that: The system includes a reconstruction module, a construction module, an update module, an iteration module, and a positioning module; The reconstruction module is used to reconstruct the non-magnetic field perturbation transverse relaxation rate R2 image based on magnetic resonance multi-echo spin echo data of the brain. The construction module is used to construct paramagnetic brain iron images based on the magnetic resonance multi-echo gradient echo data of the brain, the non-magnetic field perturbation transverse relaxation rate R2 image, and the amplitude attenuation kernel. The update module is used to update the amplitude attenuation kernel based on the paramagnetic brain iron image; The iterative module is used to update the paramagnetic brain image based on the updated amplitude attenuation kernel until both the paramagnetic brain image and the amplitude attenuation kernel converge. The localization module is used to locate epileptic lesions based on convergent paramagnetic brain iron images; Reconstruction of non-magnetic perturbation transverse relaxation rate R2 images based on brain MRI multi-echo spin echo data includes: The magnetic resonance multi-echo spin echo data were fitted to obtain the non-magnetic field perturbation transverse relaxation rate R2 image. Where M0 represents the proton density distribution, TE represents the echo time, and R2 represents the transverse relaxation decay rate of the non-magnetic field disturbance. Constructing a paramagnetic brain iron image based on the brain's magnetic resonance multi-echo gradient echo data, the non-magnetic perturbation transverse relaxation rate R2 image, and the amplitude attenuation kernel includes the following steps: The gradient echo signal of the j-th echo in the magnetic resonance multi-echo gradient echo data is set. Where M0 represents the proton density distribution, a represents the amplitude decay kernel, and φ res Represents the residual phase unaffected by echo time, γ represents the gyromagnetic ratio, D represents the dipole nucleus in the direction of the main magnetic field, and χ represents the residual phase unaffected by echo time. para Indicating paramagnetic brain iron imaging, X-ray other This represents images of other magnetic materials, B0 represents magnetic flux density, and TE represents magnetic flux density. j Rj represents the echo time of the j-th echo, R2 represents the transverse relaxation decay rate of the non-magnetic field disturbance, and 2πf bg TE j This represents the background field phase signal generated by the j-th echo; The gradient echo signal S(TE) is solved based on the objective function. j To obtain paramagnetic brain images, the objective function is: Where N represents the total number of echoes in each scan. This represents the unwound phase signal at the j-th echo time. The transverse relaxation decay rate of the magnetic field disturbance is represented by λ1, λ2, and λ3, which represent weighting coefficients, and f is the weighting coefficient. bg Let X represent the background field generated by non-brain tissue, X represent the total magnetic susceptibility, TV(·) represent the total variational regularization operator, |||| represent the norm, and argmin represent the χ² value that minimizes the function. para .

7. A storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the method for locating epileptic lesions as described in any one of claims 1 to 5.

8. An electronic device, characterized in that, include: Processor and memory; The memory is used to store computer programs; The processor is used to execute the computer program stored in the memory to cause the electronic device to perform the epileptic focus localization method according to any one of claims 1 to 5.

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