A four-dimensional dynamic organ structure imaging method and system based on biomagnetic signals

Abstract

The application provides a four-dimensional dynamic organ structure imaging method and system based on biomagnetic signals, and relates to the fields of biomedical engineering and imaging technology.The method comprises the following steps: measuring time-series magnetic field signals generated by bio-organ electric activity by using a magnetic field sensor array; obtaining dynamic electric activity source distribution of the bio-organ at a preset time sequence based on time-series magnetic field signals; for each time point in the preset time sequence, adaptive transformation is performed on a preset template organ model so that the template organ model is matched with the electric activity source distribution at the time point in morphology and position, and a personalized three-dimensional organ structure capable of representing the electric activity source distribution at the time point is generated; and the personalized three-dimensional organ structures are combined in time sequence to construct a personalized four-dimensional dynamic structure model of the bio-organ.The application can obtain a personalized four-dimensional dynamic structure model of an organ which is completely synchronized with functional information in space and time from functional magnetic field measurement of bioelectric activity.

Description

Technical Field

[0001] This invention relates to the fields of biomedical engineering and imaging technology, and in particular to a four-dimensional dynamic organ structure imaging method and system based on biomagnetic signals. Background Technology

[0002] Currently, traditional methods for obtaining biological organ structures primarily involve scanning the human body using medical imaging techniques (MRI, CT, etc.) to obtain two-dimensional tomographic images, which are then reconstructed into three-dimensional images. However, some biological organs are constantly undergoing mechanical movement, such as the beating of the heart and gastrointestinal peristalsis. These medical imaging techniques suffer from a conflict between temporal and spatial resolution, making it difficult to achieve ideal results when imaging moving organs. Furthermore, in applications involving magnetic field measurements for imaging bioelectrical activity sources, it is impossible to simultaneously perform medical imaging techniques to acquire structural images, further reducing the accuracy of obtaining structural images through medical imaging. Summary of the Invention

[0003] This invention provides a four-dimensional dynamic organ structure imaging method and system based on biomagnetic signals, which solves the problems of difficulty in dynamic organ imaging and the asynchrony between functional and structural information in the prior art, and realizes accurate and rapid four-dimensional dynamic organ imaging.

[0004] This invention provides a four-dimensional dynamic organ structure imaging method based on biomagnetic signals, comprising the following steps: Using a magnetic field sensor array to measure the time-series magnetic field signals generated by the electrical activity of biological organs; Based on the time-series magnetic field signal, the dynamic electrical activity source distribution of the biological organ in a preset time series is obtained by inversion. For each time point in the preset time series, an adaptive transformation is performed on a preset template organ model to match its morphology and location with the distribution of electrical activity sources at that time point, thereby generating a personalized three-dimensional organ structure that can characterize the distribution of electrical activity sources at that time point. The personalized three-dimensional organ structures are combined in chronological order to construct a personalized four-dimensional dynamic structural model of the biological organ.

[0005] According to the four-dimensional dynamic organ structure imaging method based on biomagnetic signals provided by the present invention, before using a magnetic field sensor array to measure the time-series magnetic field signal generated by the electrical activity of biological organs, the method further includes: Obtain the body surface contour of the organism containing the biological organ; and, The coordinate space of the magnetic field sensor array is registered with the coordinate space of the body surface contour.

[0006] According to the four-dimensional dynamic organ structure imaging method based on biomagnetic signals provided by the present invention, the step of acquiring the body surface contour of the organism containing the biological organ includes: Obtain the body surface data of the organism containing the biological organ; The body surface data is registered with a preset torso structure template to generate the body surface contour.

[0007] According to the four-dimensional dynamic organ structure imaging method based on biomagnetic signals provided by the present invention, the step of registering the body surface data with a preset trunk structure template includes: The body surface data and the trunk structure template were coarsely registered using principal component analysis. The coarsely registered body surface data is finely registered with the trunk structure template using an iterative nearest-point algorithm.

[0008] The four-dimensional dynamic organ structure imaging method based on biomagnetic signals provided by the present invention, after performing fine registration of the coarsely registered body surface data and the trunk structure template using an iterative nearest-point algorithm, further includes: Using a non-rigid registration algorithm, the finely registered body surface data is non-rigidly registered with the torso structure template; and, The surface of the non-rigidly registered torso structure template is reconstructed to generate a uniform triangular mesh as the body surface contour.

[0009] According to the four-dimensional dynamic organ structure imaging method based on biomagnetic signals provided by the present invention, the step of registering the coordinate space of the magnetic field sensor array with the coordinate space of the body surface contour includes: In two independent scans, a first point cloud and a second point cloud containing common marker blocks are acquired, wherein the first point cloud is associated with the magnetic field sensor array and the second point cloud contains data of the body surface contour; by registering the common marker blocks in the first and second point clouds, the spatial positional relationship between the magnetic field sensor array and the body surface contour is established.

[0010] According to the four-dimensional dynamic organ structure imaging method based on biomagnetic signals provided by the present invention, the step of inverting the distribution of dynamic electrical activity sources of the biological organ in a preset time series based on the time-series magnetic field signal includes: Using the body surface contour of the organism containing the biological organ as the boundary condition, an electromagnetic field physics model connecting the magnetic field and the distribution of the electrical activity source is constructed. Based on the time-series magnetic field signal, a source-tracing imaging algorithm is used to invert the electromagnetic field physics model to obtain the distribution of the dynamic electroactive sources.

[0011] According to the four-dimensional dynamic organ structure imaging method based on biomagnetic signals provided by the present invention, the step of adaptively transforming a preset template organ model includes: The template organ model is subjected to a rigid transformation to achieve a rough alignment with the distribution of the electrical activity source; The template organ model, which has undergone rigid transformation, is subjected to non-rigid deformation to further refine its morphology, thereby generating the personalized three-dimensional organ structure.

[0012] According to the four-dimensional dynamic organ structure imaging method based on biomagnetic signals provided by the present invention, the template organ model is created by segmenting, registering and averaging organ images of a group of healthy subjects.

[0013] This invention also provides a four-dimensional dynamic organ structure imaging system based on biomagnetic signals, comprising the following modules: A magnetic field signal measurement module is used to measure the time-series magnetic field signals generated by the electrical activity of biological organs using a magnetic field sensor array. The inversion module is used to invert the distribution of dynamic electrical activity sources of the biological organ in a preset time series based on the time-series magnetic field signal. The three-dimensional organ structure generation module is used to generate a personalized three-dimensional organ structure that can characterize the distribution of electrical activity sources at each time point in the preset time series by adaptively transforming a preset template organ model to match its morphology and position with the distribution of electrical activity sources at that time point. The four-dimensional model construction module is used to combine the personalized three-dimensional organ structures in chronological order to construct a personalized four-dimensional dynamic structural model of the biological organ.

[0014] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the four-dimensional dynamic organ structure imaging method based on biomagnetic signals as described above.

[0015] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the four-dimensional dynamic organ structure imaging method based on biomagnetic signals as described above.

[0016] The present invention also provides a computer program product, including a computer program that, when executed by a processor, implements the four-dimensional dynamic organ structure imaging method based on biomagnetic signals as described above.

[0017] This invention provides a four-dimensional dynamic organ structure imaging method and system based on biomagnetic signals. By using the distribution of dynamic electroactive sources derived from biomagnetic signals as a spatiotemporal constraint, a general template organ model is adaptively matched and transformed. Thus, without the need for synchronous traditional structural imaging, a personalized four-dimensional dynamic structural model that is perfectly synchronized with functional information in time and space and can accurately characterize the organ movement process is directly obtained. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0019] Figure 1 This is one of the flowcharts of the four-dimensional dynamic organ structure imaging method based on biomagnetic signals provided by the present invention.

[0020] Figure 2 This is the second schematic diagram of the four-dimensional dynamic organ structure imaging method based on biomagnetic signals provided by the present invention.

[0021] Figure 3 This is the third flowchart of the four-dimensional dynamic organ structure imaging method based on biomagnetic signals provided by the present invention.

[0022] Figure 4 This is a schematic diagram of the homogenized triangular mesh torso surface model provided by the present invention.

[0023] Figure 5 This is a schematic diagram of the personalized heart model provided by the present invention.

[0024] Figure 6 This is a schematic diagram of the structure of the four-dimensional dynamic organ structure imaging system based on biomagnetic signals provided by the present invention.

[0025] Figure 7 This is a schematic diagram of the structure of the electronic device provided by the present invention. Detailed Implementation

[0026] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0027] The present invention will now be described in detail with reference to the accompanying drawings. The specific operation methods in the method embodiments can also be applied to the device embodiments or system embodiments. In the description of the present invention, unless otherwise stated, "at least one" includes one or more. "Multiple" refers to two or more. For example, at least one of A, B, and C includes: A existing alone, B existing alone, A and B existing simultaneously, A and C existing simultaneously, B and C existing simultaneously, and A, B, and C existing simultaneously. In the present invention, " / " means "or". For example, A / B can mean A or B. "And / or" in this document is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone.

[0028] The present invention will now be described in detail with reference to specific embodiments.

[0029] In some specific embodiments of the present invention, such as Figure 1 As shown, this scheme provides a four-dimensional dynamic organ structure imaging method based on biomagnetic signals, including: Step S100: Measure the time-series magnetic field signal generated by the electrical activity of biological organs using a magnetic field sensor array; Step S200: Based on the time-series magnetic field signal, the dynamic electrical activity source distribution of the biological organ in a preset time series is obtained by inversion; Step S300: For each time point in the preset time series, an adaptive transformation is performed on a preset template organ model to match its morphology and location with the distribution of electrical activity sources at that time point, thereby generating a personalized three-dimensional organ structure that can characterize the distribution of electrical activity sources at that time point. Step S400: Combine the personalized three-dimensional organ structures in chronological order to construct a personalized four-dimensional dynamic structural model of the biological organ.

[0030] It should be noted that existing dynamic organ imaging protocols typically require long scan times to obtain clear images with high spatial resolution. During this time, organ movement can cause image blurring or motion artifacts, making it difficult to accurately capture changes in morphology and position during dynamic processes. Furthermore, functional magnetic field signal measurements cannot be performed synchronously with structural MRI / CT scans. Researchers can only use static organ structural models acquired at different time points for source tracing calculations. This spatiotemporal mismatch between functional and structural information means that the structural models used for calculations cannot reflect the organ's true position, orientation, and morphology during magnetic field measurements, thus significantly reducing the accuracy and reliability of electrical activity source tracing imaging.

[0031] Therefore, this invention generates a four-dimensional model that includes a time dimension, accurately reproducing the entire process of mechanical motion such as heartbeat, thus achieving four-dimensional imaging of dynamic organs. Furthermore, the dynamic structural model of the organ is directly derived from functional magnetic field measurement data; since both sources are identical, perfect alignment in time and space is ensured, greatly improving the accuracy of bioelectrical activity tracing imaging.

[0032] It is worth noting that two independent template models are used in the embodiments of the present invention: one is a trunk structure template, which is used to register with the body surface data to generate the body surface contour or a personalized trunk model in order to realize the calibration of the sensor coordinate space; the other is a template organ model, which is used to match the distribution of dynamic electrical activity sources and generate personalized organ structures through adaptive transformation.

[0033] Furthermore, the method disclosed in this invention is essentially a universal imaging platform technology applicable to any bioelectrically active organ capable of generating an externally measurable magnetic field. These biological organs include, but are not limited to: the heart (whose electrical activity generates magnetocardiogram (MCG) signals), the gastrointestinal tract (whose smooth muscle electrical activity generates gastrointestinal magnetocardiogram (MGG) signals), the brain (whose neuronal electrical activity generates magnetoencephalogram (MEG) signals), and other muscle tissues.

[0034] In some possible embodiments of the present invention, if the biological organ is the heart, the personalized four-dimensional dynamic structural model is used to characterize the beating process of the heart during at least one cardiac cycle.

[0035] If the biological organ is the gastrointestinal tract, a personalized four-dimensional dynamic structural model is used to characterize the rhythmic contraction and relaxation of the gastrointestinal wall spatial morphology, as well as the physical deformation process of the lumen volume and contour during at least one peristaltic cycle.

[0036] If the biological organ is the brain, it is used to characterize a spontaneous, globally synchronized fluctuation throughout the entire cortex of the brain tissue.

[0037] Preferably, the template organ model is created by segmenting, registering, and averaging organ images of a group of healthy subjects.

[0038] To clearly illustrate the core technical steps of this invention, a preferred, but not limiting, specific embodiment of four-dimensional dynamic imaging of the human heart will be described in detail below. Those skilled in the art should understand that applying the principles and steps of this embodiment to other biological organs, such as reconstructing a four-dimensional dynamic model of gastric peristalsis by measuring gastrointestinal magnetotransmission signals, falls within the scope of protection claimed by this invention.

[0039] The following is in conjunction with the appendix Figure 2 -Appendix Figure 5Taking the inversion of the four-dimensional dynamic structure of the human heart by measuring the magnetic field of its electrical activity as an example, the method of the present invention will be described in detail. Other biological organs can be inverted using the same method.

[0040] In one specific embodiment of the present invention, in response to the deficiencies or improvement needs of the prior art, the present invention provides a method for retrieving the position and shape of biological organs by measuring the magnetic field of their electrical activity, such as... Figure 2 As shown, the specific steps are as follows: Step 1: Magnetic field sensors are arranged in an array around the target organ to measure the magnetic field generated by the biological organ; Step 2: Obtain the surface contour of the organism. The methods for obtaining this contour include 3D scanning reconstruction, multi-view 2D image 3D reconstruction, CT, MRI, etc. Step 3: Match the sensor coordinate space to the coordinate space of the organism's surface contour to establish the spatial positional relationship between the sensor and the organism's surface contour. Step 4: Construct an electromagnetic field physics model of the magnetic field and current density source based on Maxwell's equations under low-frequency electromagnetic fields; Step 5: Based on the established electromagnetic field physics model, solve the inverse problem (including MNE, LCMV, LORETA, Champagne, etc.) to obtain the source distribution of the time series source imaging. Match the source distribution of the source imaging with the template organ model and perform adaptive transformations on the template organ model, such as translation, rotation, and scaling, to obtain the four-dimensional dynamic structure of the personalized organ.

[0041] In another specific embodiment of the present invention, such as Figure 3 As shown, the four-dimensional dynamic organ structure imaging method based on biomagnetic signals provided by this invention specifically includes the following steps: Step S310, Work Preparation and Data Acquisition: In this embodiment, a magnetic field sensor array is required to measure the temporal magnetic field signal generated by the electrical activity of biological organs.

[0042] Specifically, an initial torso structure template is first generated based on the subject's height, weight, gender, and other information.

[0043] Next, the subject's body surface data is acquired. Specifically, the subject lies flat on the bed, and point clouds of both the sensor panel marker blocks and the bed marker blocks are simultaneously scanned using an optical scanning device. The panel marker blocks and the bed marker block point clouds are located in the same coordinate space. Subsequently, the sensor panel is removed, and the subject's body surface scan point cloud and the bed marker block point cloud are simultaneously scanned, with both located in the same coordinate space.

[0044] Meanwhile, the spatial positional relationship between the magnetic field sensor array and a panel marker block is known and fixed. Point clouds of the panel marker block and the bed marker block are acquired through a single, independent scan.

[0045] Step S320: Obtaining and registering the body surface contour: The purpose of this step is to create an accurate, personalized body surface profile, i.e., a personalized torso model, and to register the sensor coordinate system to the coordinate system of this model.

[0046] In some possible embodiments of the present invention, before using a magnetic field sensor array to measure the time-series magnetic field signal generated by the electrical activity of biological organs, the method further includes: Obtain the body surface contour of the organism containing the biological organ; and The coordinate space of the magnetic field sensor array is registered with the coordinate space of the body surface contour.

[0047] Specifically, the personalized body surface contour is first obtained. The point cloud of the subject's anterior chest surface scan obtained in step S310 is then registered with a preset torso structure template.

[0048] In some possible embodiments of the present invention, the step of obtaining the body surface contour of the organism containing the biological organ includes: Obtain the body surface data of the organism containing the biological organ; The body surface data is registered with a preset torso structure template to generate the body surface contour.

[0049] In possible embodiments, the body surface data of the organism containing the biological organ is obtained by at least one of three-dimensional scanning, three-dimensional reconstruction of multi-view two-dimensional images, computed tomography, or magnetic resonance imaging.

[0050] In some possible embodiments of the present invention, the step of registering the body surface data with a preset torso structure template includes: The body surface data and the trunk structure template were coarsely registered using principal component analysis. The coarsely registered body surface data is finely registered with the trunk structure template using an iterative nearest-point algorithm.

[0051] Furthermore, after performing fine registration between the coarsely registered body surface data and the trunk structure template using the iterative nearest-neighbor algorithm, the process further includes: A non-rigid registration algorithm is used to perform non-rigid registration between the finely registered body surface data and the torso structure template; and, The surface of the non-rigidly registered torso structure template is reconstructed to generate a uniform triangular mesh as the body surface contour.

[0052] Preferably, the registration process can be implemented using non-rigid registration algorithms such as principal component analysis (PCA), iterative nearest point (ICP), coherent point drift (CPD), non-rigid iterative nearest point (N-ICP) algorithm, or thin plate spline robust point matching (TPS-RPM) algorithm.

[0053] Specifically, a personalized torso is obtained by matching the torso structure template with the torso scan point cloud. The matching process includes rigid registration and non-rigid registration. Rigid registration is achieved by coarsely registering the scanned point cloud with the torso template model using principal component analysis (PCA) to obtain the coarse registration transformation matrix T1. Then, fine registration is achieved using the iterative nearest neighbor method (ICP) to obtain the fine registration transformation matrix T2. The transformation matrix T is then set to T1. T2 is applied to the torso template model to achieve its matching with the scanned point cloud.

[0054] The non-rigid registration module improves the matching degree between the anterior surface point cloud of the torso template model and the anterior chest scan point cloud of the subject by using non-rigid registration algorithms (such as Coherent Point Drift (CPD), Non-Rigid Iterative Closest Point (N-ICP), Thin Plate Spline Robust Point Matching (TPS-RPM), etc.) and point cloud fusion. Finally, by reconstructing the registered torso template model, a homogenized triangular mesh torso surface model is obtained, such as... Figure 4 As shown.

[0055] Then, coordinate registration is performed between the sensor and the body surface contour.

[0056] In some possible embodiments of the present invention, the step of registering the coordinate space of the magnetic field sensor array with the coordinate space of the body surface contour includes: A first point cloud and a second point cloud containing common marker blocks are acquired in two independent scans, wherein the first point cloud is associated with the magnetic field sensor array and the second point cloud contains data of the body surface contour. By registering the common marker blocks in the first point cloud and the second point cloud, the spatial positional relationship between the magnetic field sensor array and the body surface contour is established.

[0057] Specifically, the point cloud of the bed marker block obtained by two independent scans is registered using the iterative nearest neighbor method (ICP) to obtain the transformation matrix T3. The spatial relationship between the magnetic field sensor array and the panel marker block is known and fixed. The transformation matrix T3 is applied to the magnetic field sensor array to calibrate the spatial coordinates of the sensor array and the spatial coordinates of the uniform triangular mesh torso surface model, thereby matching the sensor coordinate space to the coordinate space of the personalized torso.

[0058] Step S330, Physical Modeling and Inverse Problem Solving: In some possible embodiments of the present invention, the step of inverting the distribution of dynamic electrical activity sources of the biological organ over a preset time series based on the time-series magnetic field signal includes: Using the body surface contour of the organism containing the biological organ as the boundary condition, an electromagnetic field physics model connecting the magnetic field and the distribution of the electrical activity source is constructed. Based on the time-series magnetic field signal, a source-tracing imaging algorithm is used to invert the electromagnetic field physics model to obtain the distribution of the dynamic electroactive sources.

[0059] In possible embodiments, the source-tracing imaging algorithm includes algorithms such as minimum norm estimation, linearly constrained minimum variance beamforming, low-resolution electromagnetic tomography, or Champagne.

[0060] In a possible embodiment, the electromagnetic field physics model can be constructed using the body surface contour as a boundary condition, employing the boundary element method.

[0061] Specifically, firstly, based on Maxwell's equations under low-frequency electromagnetic fields: (1); (2); (3); (4), in, It is a vector differential operator; Indicates divergence; Indicates curl; Represents the electric displacement vector; Indicates charge density; Indicates electric field strength; Indicates magnetic flux density; Indicates magnetic field strength. Indicates a current density source; Indicates electrical conductivity; Volume current density is represented by a current density source. The electric field established in the conductive tissue drives the generated conduction current.

[0062] Using the personalized surface contour generated in step S320 as boundary conditions, an electromagnetic field physics model between the magnetic field and the current density source is constructed using the boundary element method (BEM). The calculation formula is as follows: (5); (6), in, Representation space The magnetic field strength at a point is measured using a magnetic field sensor. Indicates the first Space on a boundary surface Electric potential at a point; The position vector of the observation point represents the three-dimensional coordinates of any spatial observation point; The variable represents the integral variable, which is located inside the organism (integral volume V or boundary surface). The three-dimensional coordinates of any point in space; Permeability of free space; An integral volume refers to a conductive area of ​​a living organism, such as the volume of the entire torso. for A point current density source; It is a volume infinitesimal element; The number of boundary surfaces represents the total number of boundary surfaces between tissues with different electrical conductivity in a living organism, such as heart-lung, lung-trunk, etc. For the first A boundary surface; , They represent the first The electrical conductivity of the tissues on both the inner and outer sides of the boundary surface. Pick ; for Any boundary surface within; Indicates the first The electric potential at any point in space on the boundary surface; Representing an area infinitesimal element is a representation of the boundary. A tiny unit for integration.

[0063] Formula (5) characterizes the volume source current The magnetic field generated by the secondary current source (characterized by the difference in potential and conductivity). Formula (6) characterizes the potential at the boundaries of different tissues.

[0064] By approximating the complex integral formula above using numerical methods (such as discretizing the volume and surface into a large number of small elements or meshes), a concise linear matrix equation can be obtained.

[0065] Specifically, by performing boundary element discretization, a linear model of the magnetic field and current density source can be established: (7), in, For the lead field matrix, It is a current density source.

[0066] Next, based on this physical model, source-tracing imaging calculations are performed on the magnetocardiogram signal at fixed time intervals to obtain the dynamic source-tracing results for the entire cycle, i.e., the inversion solution. This inverse problem can be solved using minimum norm estimation (MNE), linearly constrained minimum variance beamforming (LCMV), low-resolution electromagnetic tomography (LORETA), or the Champagne algorithm. By calculating the signal throughout the entire cardiac cycle, the dynamic source tracing result for the entire cycle, i.e., the dynamic distribution of electrical activity sources, can be obtained.

[0067] Step S340, Construction of the four-dimensional dynamic model: The dynamic electrical activity source distribution obtained in step S330 is matched with a preset cardiac template model.

[0068] In this embodiment, the personalized four-dimensional dynamic structural model can be constructed based on the distribution of electrical activity sources in the heart during the QRS and T bands.

[0069] The source distribution of the upcoming source-tracing imaging is matched with the cardiac template to obtain a personalized cardiac model, and a four-dimensional dynamic cardiac structure model is obtained based on the source distribution of the source-tracing results of the QRS band and T band.

[0070] This step takes the distribution of electrical activity sources at each time point in the cardiac cycle, such as multiple time points within the QRS and T segments, as a spatial constraint.

[0071] In some possible embodiments of the present invention, the step of adaptively transforming a preset template organ model includes: The template organ model is subjected to at least one or a combination of translation, rotation, scaling, or non-rigid deformation.

[0072] Specifically, the template organ model is first subjected to a rigid transformation to achieve a rough alignment with the distribution of the electrical activity source; then, the template organ model after the rigid transformation is subjected to a non-rigid deformation to further refine the morphology of the template organ model, thereby generating the personalized three-dimensional organ structure.

[0073] Taking the heart as an example, adaptive transformations are performed on the heart template model, including translation, rotation, scaling, and possible non-rigid deformations, so that the position and shape of the transformed heart model can optimally accommodate or explain the current distribution of electrical activity sources, such as... Figure 5 As shown, the source distribution at each time point corresponds to the generation of a personalized three-dimensional heart structure.

[0074] Finally, by combining this series of three-dimensional structural models arranged in chronological order to represent the heart's morphology at different times, a personalized four-dimensional dynamic structural model that can characterize the complete beating process of the heart within a cardiac cycle is constructed.

[0075] In summary, this embodiment demonstrates in detail how the method of the present invention can be used to successfully deduce the four-dimensional dynamic structure of the heart from the magnetic field signal. Similarly, those skilled in the art can refer to the content disclosed in this embodiment to apply this method to the dynamic imaging of other biological organs. For example, by replacing the heart template with a stomach template and the magnetic field signal with a gastric magnetic signal, four-dimensional dynamic imaging of gastric peristalsis can be achieved. These applications all fall within the protection scope of the present invention.

[0076] The four-dimensional dynamic organ structure imaging method based on biomagnetic signals provided by this invention has the following advantages compared with the prior art: Achieving four-dimensional imaging of dynamic organs: It can generate four-dimensional models that include the time dimension, dynamically representing the complex mechanical movement processes of biological organs such as heartbeat and stomach peristalsis. It can also capture the dynamic processes of functional structures such as changes in the activity areas of the cerebral cortex, providing structural models containing rich spatiotemporal dynamic information that far exceed static three-dimensional images.

[0077] Ensuring synchronization between functional and structural information: Since the dynamic structural model of an organ is directly derived from functional magnetic field data, the two achieve inherent synchronization and intrinsic registration in time and space. This fundamentally eliminates the problem of temporal and spatial mismatch between functional and structural information in traditional methods, thereby greatly improving the accuracy of bioelectrical activity tracing imaging.

[0078] Achieving high-precision personalized modeling: By combining a general template organ model with the measured functional magnetic field data of an individual subject, a personalized organ model specific to that individual is generated, which has important data reference significance for further precision medicine and personalized diagnosis.

[0079] Simplified procedures and improved safety: This invention avoids reliance on simultaneous, expensive MRI or CT scans during functional imaging. Core dynamic structural information is derived entirely from non-invasive, radiation-free magnetic field measurements, which not only reduces costs and procedural complexity but also enhances safety for subjects.

[0080] The above description is merely a preferred embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

[0081] In some specific embodiments of the present invention, such as Figure 6 As shown, this solution provides a four-dimensional dynamic organ structure imaging system based on biomagnetic signals, including: Magnetic field signal measurement module 10 is used to measure the temporal magnetic field signal generated by the electrical activity of biological organs using a magnetic field sensor array; Inversion module 20 is used to invert the distribution of dynamic electrical activity sources of the biological organ in a preset time series based on the time-series magnetic field signal; The three-dimensional organ structure generation module 30 is used to generate a personalized three-dimensional organ structure that can characterize the distribution of electrical activity sources at each time point in the preset time series by adaptively transforming a preset template organ model so that its shape and position match the distribution of electrical activity sources at that time point. The four-dimensional model construction module 40 combines the personalized three-dimensional organ structures in chronological order to construct a personalized four-dimensional dynamic structural model of the biological organ.

[0082] In some possible embodiments of the present invention, the magnetic field signal measurement module 10 includes an array of magnetic field sensors arranged in an array for non-invasively measuring the weak temporal magnetic field signals generated around the body surface by the electrical activity of biological organs such as the heart.

[0083] In some possible embodiments of the present invention, the magnetic field signal measurement module 10 includes a body surface contour acquisition unit, which can acquire body surface data of the subject organism through a three-dimensional optical scanning device, a multi-view camera system, CT or MRI equipment. The magnetic field signal measurement module 10 also includes a coordinate registration unit, which is used to unify the coordinate space of the magnetic field sensor array, the coordinate space of the body surface contour, and the coordinate space of the template organ model used subsequently, establishing a precise spatial relationship between them. This unit can be implemented using non-rigid registration algorithms such as principal component analysis, iterative nearest point algorithm, and coherence point drift.

[0084] In some possible embodiments of the present invention, the inversion module 20, based on the measured time-series magnetic field signal and the established physical model, calculates the distribution of dynamic electrical activity sources within the organ over time by solving the electromagnetic inverse problem. This module may employ algorithms such as Minimum Norm Estimation (MNE), Linear Constrained Minimum Variance Beamforming (LCMV), Low Resolution Electromagnetic Tomography (LORETA), or Champagne.

[0085] In some possible embodiments of the present invention, the four-dimensional model construction module 40 receives the dynamic distribution of electrical activity sources and performs spatiotemporal matching with a preset template organ model. By performing adaptive transformations such as translation, rotation, scaling, and non-rigid deformation on the template model, a series of personalized three-dimensional organ structures that best match the distribution of electrical activity sources and are arranged in chronological order are generated, and finally combined into a complete personalized four-dimensional dynamic structure model.

[0086] Figure 7 An example is a schematic diagram of the physical structure of an electronic device, such as... Figure 7 As shown, the electronic device may include a processor 710, a communications interface 720, a memory 730, and a communication bus 740, wherein the processor 710, communications interface 720, and memory 730 communicate with each other via the communication bus 740. The processor 710 can call logical instructions in the memory 730 to execute a four-dimensional dynamic organ structure imaging method based on biomagnetic signals. This method includes: measuring the temporal magnetic field signal generated by the electrical activity of a biological organ using a magnetic field sensor array; obtaining the dynamic electrical activity source distribution of the biological organ in a preset time series based on the temporal magnetic field signal; for each time point in the preset time series, adaptively transforming a preset template organ model to match its morphology and position with the electrical activity source distribution at that time point, thereby generating a personalized three-dimensional organ structure that can characterize the electrical activity source distribution at that time point; and combining the personalized three-dimensional organ structures in chronological order to construct a personalized four-dimensional dynamic structural model of the biological organ.

[0087] Furthermore, the logical instructions in the aforementioned memory 730 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, essentially, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0088] On the other hand, the present invention also provides a computer program product, which includes a computer program that can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the four-dimensional dynamic organ structure imaging method based on biomagnetic signals provided by the above methods. The method includes: measuring the temporal magnetic field signal generated by the electrical activity of the biological organ using a magnetic field sensor array; obtaining the dynamic electrical activity source distribution of the biological organ in a preset time series based on the temporal magnetic field signal; for each time point in the preset time series, adaptively transforming a preset template organ model to match its morphology and position with the electrical activity source distribution at that time point, thereby generating a personalized three-dimensional organ structure that can characterize the electrical activity source distribution at that time point; and combining the personalized three-dimensional organ structures in chronological order to construct a personalized four-dimensional dynamic structural model of the biological organ.

[0089] In another aspect, the present invention also provides a non-transitory computer-readable storage medium storing a computer program thereon. When executed by a processor, the computer program implements the four-dimensional dynamic organ structure imaging method based on biomagnetic signals provided by the methods described above. The method includes: measuring the temporal magnetic field signal generated by the electrical activity of a biological organ using a magnetic field sensor array; obtaining the dynamic electrical activity source distribution of the biological organ in a preset time series based on the temporal magnetic field signal; for each time point in the preset time series, adaptively transforming a preset template organ model to match its morphology and position with the electrical activity source distribution at that time point, thereby generating a personalized three-dimensional organ structure that can characterize the electrical activity source distribution at that time point; and combining the personalized three-dimensional organ structures in chronological order to construct a personalized four-dimensional dynamic structural model of the biological organ.

[0090] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0091] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0092] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for four-dimensional dynamic organ structure imaging based on biomagnetic signals, characterized by, include: Using a magnetic field sensor array to measure the time-series magnetic field signals generated by the electrical activity of biological organs; Based on the time-series magnetic field signal, the dynamic electrical activity source distribution of the biological organ in a preset time series is obtained by inversion. For each time point in the preset time series, an adaptive transformation is performed on a preset template organ model to match its morphology and location with the distribution of electrical activity sources at that time point, thereby generating a personalized three-dimensional organ structure that can characterize the distribution of electrical activity sources at that time point. The step of adaptively transforming a preset template organ model includes: performing a rigid transformation on the template organ model to achieve a rough alignment with the distribution of the electrical activity source; and performing a non-rigid deformation on the rigidly transformed template organ model to further refine the morphology of the template organ model, thereby generating the personalized three-dimensional organ structure. The personalized three-dimensional organ structures are combined in chronological order to construct a personalized four-dimensional dynamic structural model of the biological organ.

2. The method of claim 1, wherein the method is a method of four- dimensional dynamic organ structure imaging based on biomagnetic signals. Prior to using a magnetic field sensor array to measure the time-series magnetic field signal generated by the electrical activity of biological organs, the method further includes: Obtain the body surface contour of the organism containing the biological organ; and, The coordinate space of the magnetic field sensor array is registered with the coordinate space of the body surface contour.

3. The bio-magnetic signal based four-dimensional dynamic organ structure imaging method according to claim 2, characterized in that, The step of obtaining the body surface contour of the organism containing the biological organ includes: Obtain the body surface data of the organism containing the biological organ; The body surface data is registered with a preset torso structure template to generate the body surface contour.

4. The four-dimensional dynamic organ structure imaging method based on biomagnetic signals according to claim 3, characterized in that, The step of registering the body surface data with a preset torso structure template includes: The body surface data and the trunk structure template were coarsely registered using principal component analysis. The coarsely registered body surface data is finely registered with the trunk structure template using an iterative nearest-point algorithm.

5. The four-dimensional dynamic organ structure imaging method based on biomagnetic signals according to claim 4, characterized in that, After finely registering the coarsely registered body surface data with the trunk structure template using the iterative nearest-point algorithm, the process further includes: A non-rigid registration algorithm is used to perform non-rigid registration between the finely registered body surface data and the torso structure template; and, The surface of the non-rigidly registered torso structure template is reconstructed to generate a uniform triangular mesh as the body surface contour.

6. The four-dimensional dynamic organ structure imaging method based on biomagnetic signals according to claim 2, characterized in that, The step of registering the coordinate space of the magnetic field sensor array with the coordinate space of the body surface contour includes: In two independent scans, a first point cloud and a second point cloud containing common marker blocks are acquired, wherein the first point cloud is associated with the magnetic field sensor array and the second point cloud contains data of the body surface contour; by registering the common marker blocks in the first and second point clouds, the spatial positional relationship between the magnetic field sensor array and the body surface contour is established.

7. The four-dimensional dynamic organ structure imaging method based on biomagnetic signals according to claim 2, characterized in that, The step of inverting the distribution of dynamic electrical activity sources of the biological organ over a preset time series based on the time-series magnetic field signal includes: Using the body surface contour of the organism containing the biological organ as the boundary condition, an electromagnetic field physics model connecting the magnetic field and the distribution of the electrical activity source is constructed. Based on the time-series magnetic field signal, a source-tracing imaging algorithm is used to invert the electromagnetic field physics model to obtain the distribution of the dynamic electroactive sources.

8. The four-dimensional dynamic organ structure imaging method based on biomagnetic signals according to claim 1, characterized in that, The template organ model was created by segmenting, registering, and averaging organ images from a group of healthy subjects.

9. A four-dimensional dynamic organ structure imaging system based on biomagnetic signals, characterized in that, include: A magnetic field signal measurement module is used to measure the time-series magnetic field signals generated by the electrical activity of biological organs using a magnetic field sensor array. The inversion module is used to invert the distribution of dynamic electrical activity sources of the biological organ in a preset time series based on the time-series magnetic field signal. A three-dimensional organ structure generation module is used to generate a personalized three-dimensional organ structure that characterizes the distribution of electrical activity sources at each time point in the preset time series by adaptively transforming a preset template organ model to match its morphology and position with the distribution of electrical activity sources at that time point. The adaptive transformation of the preset template organ model includes: performing a rigid transformation on the template organ model to achieve a rough alignment with the distribution of electrical activity sources; and performing a non-rigid deformation on the rigidly transformed template organ model to further refine its morphology, thereby generating the personalized three-dimensional organ structure. The four-dimensional model construction module is used to combine the personalized three-dimensional organ structures in chronological order to construct a personalized four-dimensional dynamic structural model of the biological organ.

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