Epilepsy focus positioning method and system, medium and electronic equipment

Abstract

The invention provides an epilepsy focus positioning method, an epilepsy focus positioning system, a medium and electronic equipment. The epilepsy focus positioning method comprises the following steps: reconstructing a non-magnetic field disturbance transverse relaxation rate R2 image based on magnetic resonance multi-echo spin echo data of a brain; constructing a paramagnetic brain iron image based on the magnetic resonance multi-echo gradient echo data of the brain, the non-magnetic field disturbance transverse relaxation rate R2 image and the amplitude attenuation core; 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 the paramagnetic brain iron image and the amplitude attenuation kernel converge; and positioning an epilepsy focus based on the convergent paramagnetic brain iron image. According to the epilepsy focus positioning method and system, the medium and the electronic equipment, the epilepsy focus is positioned based on the paramagnetic brain iron image, and the positioning precision and the positioning efficiency are effectively improved.

Description

Technical Field

[0001] The present invention relates to the technical field of biomedical engineering, and in particular to an epileptic focus positioning method, system, medium and electronic equipment. Background Art

[0002] Epilepsy is one of the most common and critical neurological diseases, characterized by repeated and unexpected seizures caused by abnormal neuronal activity. This condition is not limited by age and can cause a variety of symptoms including loss of consciousness, convulsions and behavioral changes.

[0003] The pathogenesis of epilepsy is complex and diverse, but studies have shown that iron plays an important role in the central nervous system, either directly or indirectly affecting the process of epileptic seizures and having important pathophysiological significance. For example, stroke, neurotrauma, and intracerebral hemorrhage may induce epileptic seizures. These conditions are usually associated with increased permeability of the blood-brain barrier in patients with epilepsy, allowing iron in the form of hemosiderin, ferritin, and hemoglobin to leak into the tissue. Disturbances in iron metabolism are closely linked to oxidative stress, which is an important hallmark of many structural, genetic, or immune-related epilepsy subtypes. Oxidative stress not only exacerbates the dysfunction and damage of central nervous system cells, but also promotes the occurrence of iron overload and ferroptosis. Iron overload may further cause redistribution of iron in the cortex and subcortical structures by promoting lipid peroxidation, disrupting protein function, and associated with increased extracellular glutamate levels. In addition, pharmacological actions such as reducing iron deposition, changing ferritin levels, and alleviating oxidative damage can alleviate iron-mediated epilepsy symptoms. It is worth noting that iron-mediated neurotoxicity is not only related to the intensity of epileptic seizures, but its spatial distribution characteristics may also reveal the core location of the epileptogenic network. Therefore, specific dynamic monitoring of brain iron content is crucial for the accurate diagnosis and treatment of epilepsy.

[0004] Given the central role of iron in the pathogenesis of epilepsy, it is particularly necessary to develop a specific and non-invasive in vivo iron localization technology. Magnetic resonance imaging (MRI) provides a detailed way to obtain in vivo information with its excellent contrast and high-resolution biological tissue imaging capabilities. However, the current existing MRI iron imaging technology faces some significant limitations. For example, although methods such as susceptibility-weighted imaging (SWI), R2* relaxation rate, and quantitative susceptibility mapping (QSM) have been tried to quantify the iron content in the brain of patients with epilepsy, these technologies lack sufficient specificity to distinguish paramagnetic iron deposition from diamagnetic substances (such as calcifications) due to interference from other magnetic components in brain tissue (such as calcifications). This limitation results in suboptimal sensitivity and specificity when performing iron detection in clinical settings. Therefore, in order to improve the diagnostic accuracy of abnormal iron deposition associated with epilepsy, it is crucial to develop new technologies or improve existing technologies that can effectively overcome the above limitations. Summary of the invention

[0005] In view of the above problems, the purpose of the present invention is to provide an epileptic lesion localization method, system, medium, and electronic equipment, which can realize the localization of epileptic lesions based on paramagnetic brain iron imaging, and effectively improve 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 field 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 magnetic resonance multi-echo gradient echo data of the brain, the non-magnetic field 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 the paramagnetic brain iron image and the amplitude attenuation kernel converge; locating the epileptic lesion based on the converged paramagnetic brain iron image.

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

[0008] Fitting the magnetic resonance multi-echo spin echo data to obtain a non-magnetic field disturbance transverse relaxation rate R2 image Among them, M 0 represents the proton density distribution, TE represents the echo time, R 2 represents the transverse relaxation decay rate without magnetic field disturbance.

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

[0010] Set the gradient echo signal of the jth echo of the magnetic resonance multi-echo gradient echo data Among them, M 0 represents the proton density distribution, a represents the amplitude attenuation core, φ res represents the residual phase not affected by the echo time, γ represents the gyromagnetic ratio, D represents the dipole nucleus in the direction of the main magnetic field, and χ para represents paramagnetic brain iron imaging, χ other Indicates images of other magnetic materials, B 0 Indicates the magnetic induction intensity, TE j represents the echo time of the jth echo, R 2 represents the transverse relaxation decay rate without magnetic field disturbance, 2πf bg TE j represents the background field phase signal generated by the jth echo;

[0011] Based on the objective function, the gradient echo signal S(TE j ) to obtain paramagnetic brain iron images, the objective function is:

[0012] Where N represents the total number of echoes in each scan, represents the unwrapped phase signal of the jth echo time, represents the transverse relaxation decay rate of magnetic field disturbance, λ 1 , 2 and λ 3 represents the weight coefficient, f bg represents the background field generated by non-brain tissue, χ represents the total magnetic susceptibility, TV(·) represents the total variation regularization operator, and |‖‖| represents the norm.

[0013] In an implementation of the first aspect, according to Get The value of M j Represents the gradient echo signal amplitude of the jth echo.

[0014] In an implementation of the first aspect, the following steps are adopted to obtain the background field phase signal:

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

[0016] The phase signal after phase unwrapping is fitted based on a spherical harmonic function algorithm to obtain the background field phase signal.

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

[0018] according to Get the updated amplitude attenuation kernel a, where R 2 represents the transverse relaxation decay rate without magnetic field disturbance, represents the transverse relaxation decay rate of magnetic field disturbance, χ para represents paramagnetic brain iron imaging, χ other Represents images of other magnetic materials, and || represents absolute value operation.

[0019] In an implementation of the first aspect, localizing epileptic lesions based on convergent paramagnetic brain iron images comprises the following steps:

[0020] Set lesion threshold;

[0021] In the converged paramagnetic brain iron image, a region whose intensity is greater than the lesion threshold is determined to be an epileptic lesion.

[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 a non-magnetic field disturbance transverse relaxation rate R2 image based on the magnetic resonance multi-echo spin echo data of the brain;

[0024] The construction module 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 disturbance transverse relaxation rate R2 image and the amplitude attenuation kernel;

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

[0026] The iteration module is used to update the paramagnetic brain iron image based on the updated amplitude attenuation kernel until the paramagnetic brain iron image and the amplitude attenuation kernel converge;

[0027] The positioning module is used to locate epileptic lesions based on converged paramagnetic brain iron images.

[0028] In a third aspect, the present invention provides a storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-mentioned epileptic lesion localization method.

[0029] In a fourth aspect, 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 executes the above-mentioned epileptic lesion localization method.

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

[0033] (1) Paramagnetic brain iron imaging based on dual-modality data of multi-echo gradient echo (mGRE) and multi-echo spin echo (mSE) has achieved precise localization of epileptic lesions;

[0034] (2) Specific imaging reconstruction of brain iron content based on paramagnetic susceptibility imaging can accurately measure brain iron levels, solving the problem of traditional methods that are difficult to distinguish other magnetic substances coexisting in the same voxel;

[0035] (3) The use of automated processes greatly reduces the impact of manual operation and subjective judgment, improves positioning efficiency and 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. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 Shown is a flow chart of an epileptic focus localization method in one embodiment of the present invention;

[0038] Figure 2 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 a typical paramagnetic brain iron image of an epileptic patient in one embodiment;

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

[0041] Figure 5 Shown is a schematic diagram of the comparison of the paramagnetic brain iron image of the present invention and the PET image of the epileptic focus in one embodiment;

[0042] Figure 6 Shown is a schematic structural diagram of an epileptic focus localization system according to an embodiment of the present invention;

[0043] Figure 7 It is a schematic structural diagram of an electronic device of the present invention in one embodiment. DETAILED DESCRIPTION

[0044] The following describes the embodiments of the present invention by specific examples, and those skilled in the art can easily understand other advantages and effects of the present invention from the contents disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the following embodiments and features in the embodiments can be combined with each other without conflict.

[0045] It should be noted that the illustrations provided in the following embodiments are only schematic illustrations of the basic concept of the present invention, and thus the drawings only show components related to the present invention rather than being drawn according to the number, shape and size of components in actual implementation. In actual implementation, the type, quantity and proportion of each component may be changed arbitrarily, and the component layout may also be more complicated.

[0046] The epileptic lesion localization method, system, medium, and electronic device of the present invention utilize the unique influence of the paramagnetic properties of iron on the magnetic resonance signal, accelerate the magnetization dephasing process to cause signal amplitude attenuation, and produce characteristic phase accumulation as the echo time is prolonged, thereby constructing an iron-specific magnetic susceptibility separation model, and ultimately achieving iron-specific epileptic lesion localization.

[0047] The technical solutions in the embodiments of the present invention will be described in detail below in conjunction with the accompanying drawings in the embodiments of the present invention.

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

[0049] Step S1, reconstructing a non-magnetic field disturbance transverse relaxation rate R2 image based on the brain magnetic resonance multi-echo spin echo data.

[0050] Specifically, the non-magnetic field perturbation transverse relaxation rate R2 image is obtained by collecting a multi-echo spin echo image. As the echo time increases, the amplitude of the multi-echo spin echo signal will gradually decay, and the non-magnetic field perturbation transverse relaxation decay rate R2 image is fitted by a single exponential decay model. The fitting process is: Among them, M 0 represents the proton density distribution, TE represents the echo time, R 2 represents the transverse relaxation decay rate without magnetic field disturbance.

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

[0052] Specifically, the multi-echo gradient echo sequence is a variant of the gradient echo sequence, which generates images by collecting multiple echoes within one TR cycle. This technology has important application value in MRI, especially when multiple contrast information needs to be obtained. The magnetic resonance multi-echo gradient echo data includes amplitude signals and phase signals, which can be used to establish the magnetic susceptibility signal equation of paramagnetic brain iron and other magnetic substances. Figure 2 As shown in the figure, the red balls represent the distribution of iron elements in the voxel, and all materials are modeled as ideal spheres. para ) and other magnetic materials (χ other ) will interfere with the magnetic field, causing the amplitude signal of the magnetic resonance multi-echo gradient echo data to fluctuate with the echo time (TE j ) will be attenuated. At the same time, the phase signals generated by these materials with different magnetic properties may be partially or completely offset, affecting the phase signal of the overall acquired magnetic resonance multi-echo gradient echo data. In addition, the transverse relaxation attenuation rate R of the tissue inherent non-magnetic field perturbation that is not disturbed by the magnetic field must also be considered. 2 and background field phase signal (2πf bg TE j ). Therefore, at a given magnetic induction intensity (B 0 ), the gradient echo signal of the j-th echo of the magnetic resonance multi-echo gradient echo data is expressed as;

[0053]

[0054] Among them, M 0 represents the proton density distribution; a represents the amplitude decay core, which represents the ability of the magnetic susceptibility material to affect the relaxation decay rate; φ res represents the residual phase not affected by the echo time, γ represents the gyromagnetic ratio, D represents the dipole nucleus in the direction of the main magnetic field, and χ para represents paramagnetic brain iron imaging, χ other Indicates images of other magnetic materials, B 0 Indicates the magnetic induction intensity, TE j represents the echo time of the jth echo, R 2 represents the transverse relaxation decay rate without magnetic field disturbance, 2πf bg TE j represents the background field phase signal generated by the jth echo, and || represents the absolute value operation.

[0055] In the present invention, the transverse relaxation decay rate of the magnetic field disturbance is It can be solved by a single exponential model, that is, according to Get The value of M j represents the gradient echo signal amplitude of the jth echo, and N represents the total number of echoes in each scan.

[0056] In the present invention, the phase signal of the magnetic resonance multi-echo gradient echo data is phase unwrapped based on the Laplace operator, and the phase signal after phase unwrapping is fitted based on the spherical harmonic function algorithm (Sophisticated Harmonic Artifact Reduction for Phase data with Variable-kernel, V-SHARP) 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 takes an initial value, such as 323.5Hz / ppm, and then the background field phase is obtained. and R 2 Substitute into the objective function. Solve the gradient echo signal based on the objective function To obtain the initial paramagnetic brain iron image. Specifically, the objective function is:

[0058]

[0059] in represents the transverse relaxation decay rate of magnetic field disturbance. 1 , 2 and λ 3 represents the weight coefficient, λ 1 represents the weight of the regular term in the first term of the solution formula, λ 2 represents the weight of the regular term in solving the third term of the formula, λ 3 represents the weight of the total variation regularization term (TV(·)) in the solution formula. bg represents the background field generated by non-brain tissue, χ represents the total magnetic susceptibility, TV(·) represents the total variation regularization operator, and |‖‖| represents the norm.

[0060] Step S3: updating 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 perturbations The influence of each voxel is different, so it is necessary to recalculate the amplitude attenuation kernel of each voxel according to the obtained paramagnetic brain iron image.

[0062] Step S4, updating the paramagnetic brain iron image based on the updated amplitude attenuation kernel until the paramagnetic brain iron image and the amplitude attenuation kernel converge.

[0063] Specifically, after the amplitude attenuation kernel is updated, the paramagnetic brain iron image is acquired again based on the objective function; and then the amplitude attenuation kernel is continuously updated based on the updated paramagnetic brain iron image. The amplitude attenuation kernel and the paramagnetic brain iron image are calculated alternately and iteratively in this way until the paramagnetic brain iron image and the amplitude attenuation kernel converge. The converged paramagnetic brain iron image is the final high-quality paramagnetic brain iron image. Figure 3 Shown is a paramagnetic brain iron image calculated from magnetic resonance scan 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 (such as 0.3 Hz / ppm / voxel), and the tolerance of the objective function is less than a preset tolerance (such as 0.3), it is determined that the paramagnetic brain iron image and the amplitude attenuation kernel are both converged.

[0065] Step S5: localizing the epileptic lesion based on the converged paramagnetic brain iron image.

[0066] Specifically, the present invention locates epileptic lesions in the cortical area by threshold segmentation method. First, a lesion threshold is set, such as 0.02ppm (parts per million, dimensionless). Then, in the converged paramagnetic brain iron image, the area with an intensity greater than the lesion threshold is determined to be an epileptic lesion. Figure 4 This is a schematic diagram of epileptic lesion localization based on the threshold segmentation method.

[0067] like Figure 5 As shown, the positioning result of the epileptic lesion positioning method of the present invention is highly consistent with the positioning result of positron emission computed tomography (PET), and paramagnetic brain iron imaging can provide more accurate lesion positioning.

[0068] The protection scope of the epilepsy lesion localization method described in the embodiment of the present invention is not limited to the execution order of the steps listed in this embodiment. All solutions implemented by adding, reducing or replacing steps in the prior art based on the principles of the present invention are included in the protection scope of the present invention.

[0069] An embodiment of the present invention further provides an epilepsy lesion localization system, which can implement the epilepsy lesion localization method described in the present invention. However, the implementation device of the epilepsy lesion localization system described in the present invention includes but is not limited to the structure of the epilepsy lesion localization system listed in this embodiment. All structural deformations and replacements of the prior art made according to the principles of the present invention are included in the protection scope of the present 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 a non-magnetic field disturbance transverse relaxation rate R2 image based on the brain magnetic resonance multi-echo spin echo data.

[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 disturbance transverse relaxation rate R2 image and the amplitude attenuation kernel.

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

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

[0075] The positioning module 65 is connected to the iteration module 64 and is used to locate the epileptic focus based on the converged paramagnetic brain iron image.

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

[0077] In the several embodiments provided by the present invention, it should be understood that the disclosed system, device or method can be implemented in other ways. For example, the device embodiments described above are only schematic, for example, the division of modules / units is only a logical function division, and there may be other division methods in actual implementation, such as multiple modules or units can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or modules or units, which can be electrical, mechanical or other forms.

[0078] The modules / units described as separate components may or may not be physically separated, and the components displayed as modules / units may or may not be physical modules, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules / units may be selected according to actual needs to achieve the purpose of the embodiments of the present invention. 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 of ordinary skill in the art should further appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in terms of function in the above description. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0080] The embodiment of the present invention also provides a computer-readable storage medium. A person of ordinary skill in the art can understand that all or part of the steps in the epilepsy lesion localization method of the above embodiment can be completed by instructing a processor through a program, and the program can be stored in a computer-readable storage medium, and the storage medium is a non-transitory medium, such as a random access memory, a read-only memory, a flash memory, a hard disk, a solid-state hard disk, a magnetic tape, a floppy disk, an optical disc, and any combination thereof. The above storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or a data center that includes one or more available media. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a digital video disc (DVD)), or a semiconductor medium (e.g., a solid-state disk (SSD)), etc.

[0081] An embodiment of the present invention further provides an electronic device, which includes a processor and a memory.

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

[0083] The memory includes: ROM, RAM, disk, USB flash drive, memory card or CD and other media that can store program codes.

[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 executes the above-mentioned epileptic lesion localization method.

[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 gates or transistor logic devices, discrete hardware components.

[0086] like Figure 7 As shown, the electronic device of the present invention is in the form of a general 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 types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processor or a local bus using any of a variety of bus architectures. By way of example, these architectures include, but are not limited to, an Industry Standard Architecture (ISA) bus, a Micro Channel Architecture (MAC) bus, an Enhanced ISA bus, a Video Electronics Standards Association (VESA) local bus, and a Peripheral Component Interconnect (PCI) bus.

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

[0089] The 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, the storage system 723 may be used to read and write non-removable, non-volatile magnetic media ( Figure 7 not shown, usually called a "hard drive"). Although Figure 7 Not 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, a DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to the bus 73 via one or more data medium interfaces. The memory 72 may include at least one program product having a set (e.g., at least one) of program modules that are configured to perform the functions of the various 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 the memory 72, such program modules 7241 including but not limited to an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment. The program modules 7241 generally perform the functions and / or methods of the embodiments described herein.

[0091] The electronic device may also communicate with one or more external devices (e.g., keyboards, pointing devices, displays, 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 cards, modems, etc.). Such communication may be performed via input / output (I / O) interface 74. Furthermore, the electronic device may also communicate with one or more networks (e.g., local area networks (LANs), wide area networks (WANs), and / or public networks, such as the Internet) via network adapter 75. Figure 7 As shown, the network adapter 75 communicates with other modules of the electronic device via the bus 73. It should be understood that, although not shown in the figure, other hardware and / or software modules can 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 present invention. Anyone familiar with the art may 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 a person of ordinary skill in the art without departing from the spirit and technical concept disclosed by the present invention shall still be covered by the claims of the present invention.

Claims

1. A method for locating epileptic lesions, characterized in that: The method comprises the following steps: Reconstruction of non-magnetic field perturbation transverse relaxation rate R2 images based on brain MRI multi-echo spin echo data; constructing a paramagnetic brain iron image based on the brain magnetic resonance multi-echo gradient echo data, the non-magnetic field disturbance transverse relaxation rate R2 image and the 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; Convergence-based paramagnetic brain iron imaging for localization of epileptic lesions.

2. The epileptic lesion localization method according to claim 1, characterized in that: Reconstruction of non-magnetic field perturbation transverse relaxation rate R2 images based on brain magnetic resonance multi-echo spin echo data includes: Fitting the magnetic resonance multi-echo spin echo data to obtain a non-magnetic field disturbance 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 without magnetic field disturbance.

3. The epileptic focus localization method according to claim 1, characterized in that: Constructing a paramagnetic brain iron image based on the brain magnetic resonance multi-echo gradient echo data, the non-magnetic field disturbance transverse relaxation rate R2 image and the amplitude attenuation kernel comprises the following steps: Set the gradient echo signal of the jth echo of the magnetic resonance multi-echo gradient echo data Where M0 represents the proton density distribution, a represents the amplitude decay core, φ res represents the residual phase not affected by the echo time, γ represents the gyromagnetic ratio, D represents the dipole nucleus in the direction of the main magnetic field, and χ para represents paramagnetic brain iron imaging, χ other Indicates the image of other magnetic materials, B0 indicates the magnetic induction intensity, TE j represents the echo time of the jth echo, R2 represents the transverse relaxation decay rate of the non-magnetic field disturbance, 2πf bg TE j represents the background field phase signal generated by the jth echo; Based on the objective function, the gradient echo signal S(TE j ) to obtain paramagnetic brain iron images, the objective function is: Where N represents the total number of echoes in each scan, represents the unwrapped phase signal of the jth echo time, represents the transverse relaxation decay rate of magnetic field disturbance, λ1, λ2 and λ3 represent weight coefficients, and f bg represents the background field generated by non-brain tissue, χ represents the total magnetic susceptibility, TV(·) represents the total variation regularization operator, and |‖‖| represents the norm.

4. The epileptic focus localization method according to claim 3, characterized in that: according to Get The value of M j Represents the gradient echo signal amplitude of the jth echo.

5. The epileptic focus localization method according to claim 3, characterized in that: The following steps are used to obtain the background field phase signal: performing phase unwrapping on the phase signal of the magnetic resonance multi-echo gradient echo data based on a Laplace operator; The phase signal after phase unwrapping is fitted based on a spherical harmonic function algorithm to obtain the background field phase signal.

6. The epileptic focus localization method according to claim 1, characterized in that: Updating the amplitude attenuation kernel based on the paramagnetic brain iron image comprises: according to Get the updated amplitude decay kernel a, where R2 represents the transverse relaxation decay rate of non-magnetic field perturbations, represents the transverse relaxation decay rate of magnetic field disturbance, χ para represents paramagnetic brain iron imaging, χ other Represents images of other magnetic materials, and || represents absolute value operation.

7. The epileptic focus localization method according to claim 1, characterized in that: The localization of epileptic lesions based on convergence paramagnetic brain iron imaging includes the following steps: Set lesion threshold; In the converged paramagnetic brain iron image, a region whose intensity is greater than the lesion threshold is determined to be an epileptic lesion.

8. An epileptic focus 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 a non-magnetic field disturbance transverse relaxation rate R2 image based on the magnetic resonance multi-echo spin echo data of the brain; The construction module 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 disturbance transverse relaxation rate R2 image and the amplitude attenuation kernel; The updating module is used to update the amplitude attenuation kernel based on the paramagnetic brain iron image; The iteration module is used to update the paramagnetic brain iron image based on the updated amplitude attenuation kernel until the paramagnetic brain iron image and the amplitude attenuation kernel converge; The positioning module is used to locate epileptic lesions based on converged paramagnetic brain iron images.

9. A storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method for locating an epileptic lesion according to any one of claims 1 to 7 is implemented.

10. 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, so that the electronic device executes the epileptic lesion localization method according to any one of claims 1 to 7.

Images