Dynamic diffusion optical tomography method, device and equipment based on ultrasonic position prior and medium

Abstract

The invention discloses a dynamic diffusion optical tomography method and device based on ultrasonic position prior, equipment and a medium, and relates to the technical field of image processing, and the method comprises the steps: obtaining a to-be-reconstructed breast image and an ultrasonic image which are collected and preprocessed when a to-be-detected breast is under preset pressure; calculating a weight matrix of a mathematical model constructed based on the to-be-reconstructed breast image according to the breast morphology parameters in the ultrasonic image, and solving a detector data matrix of the mathematical model by using the to-be-reconstructed breast image; and based on a detector data matrix solving result and a weight matrix calculation result of the mathematical model, solving an optical absorption coefficient matrix in the mammary tissue in the mathematical model by using focus space position information representing a mammary tissue focus area in the ultrasonic image to obtain optical characteristic information in the mammary tissue. And obtaining a reconstructed breast image based on a post-processing result of the optical characteristic information. According to the invention, the accuracy and resolution of optical imaging are improved.

Description

Technical Field

[0001] The present invention relates to the field of image processing technology, and in particular to a method, device, equipment and medium for dynamic diffusion optical tomography based on ultrasound position prior. Background Art

[0002] Currently, in breast examinations, non-invasive examinations are performed using diffuse optical tomography (DOT) technology, which uses diffuse light absorbed and scattered by tissues to reconstruct images. It can quantitatively measure components such as oxyhemoglobin, deoxyhemoglobin, blood oxygen, and water, and perform functional imaging of tissues to determine whether there is cancerous tissue in the breast. It has a high sensitivity for breast cancer detection.

[0003] However, the solution of the inverse problem of DOT is nonlinear, ill-posed, and ill-posed, so DOT imaging has the problems of insufficient spatial resolution and poor imaging accuracy.

[0004] In summary, how to accurately solve the inverse problem of the DOT imaging process and obtain a reconstructed image with high resolution and accurate reconstruction results is a technical problem to be solved in this field. Summary of the invention

[0005] In view of this, the purpose of the present invention is to provide a method, device, equipment and medium for dynamic diffusion optical tomography based on ultrasound position prior, which can accurately solve the inverse problem of the DOT imaging process and obtain a reconstructed image with high resolution and accurate reconstruction results. The specific scheme is as follows:

[0006] In a first aspect, the present application discloses a dynamic diffusion optical tomography method based on ultrasound position prior, comprising:

[0007] Obtaining a breast image to be reconstructed and a corresponding ultrasound image collected and preprocessed at a preset pressure of the breast to be tested; wherein the breast image to be reconstructed includes breast contour information and detector data information within the breast contour;

[0008] Calculating a weight matrix of a mathematical model constructed based on the breast image to be reconstructed according to breast morphology parameters in the ultrasound image, and solving a detector data matrix of the mathematical model using the breast image to be reconstructed; wherein the mathematical model is used to describe the mathematical relationship between the propagation of an optical signal in the breast tissue of the breast to be tested and the reception of the propagated optical signal by the detector;

[0009] Based on the detector data matrix solution results and weight matrix calculation results of the mathematical model and using the lesion spatial position information representing the breast tissue lesion area in the ultrasound image, the optical absorption coefficient matrix inside the breast tissue in the mathematical model is solved to obtain the corresponding optical characteristic information inside the breast tissue, and based on the post-processing results of the optical characteristic information, the corresponding reconstructed breast image is obtained.

[0010] Optionally, the step of obtaining the breast image to be reconstructed and the corresponding ultrasound image collected and preprocessed at a preset pressure of the breast to be tested includes:

[0011] Acquire multiple initial DOT images and ultrasound images of the breast to be tested at a preset pressure, and acquire an ambient dark frame of the breast to be tested during a process in which the pressure is gradually increased to reach the preset pressure;

[0012] Using the ambient dark frame to perform image preprocessing on each of the initial DOT images to obtain a plurality of preprocessed DOT images;

[0013] Fusing all the pre-processed DOT images to obtain a fused DOT image, performing gradient descent processing on the fused DOT image, determining points with the largest gradient descent in each image region, and connecting the points with arcs to obtain a breast contour image;

[0014] The data points in the breast contour image are subjected to difference processing to obtain a breast image to be reconstructed.

[0015] Optionally, performing difference processing on the data points in the breast contour image to obtain the breast image to be reconstructed includes:

[0016] The first frame of DOT image corresponding to each light source when the pressure gradually increases to reach the preset pressure is used as a reference image;

[0017] Performing difference calculation between data points at various positions within the range surrounded by the arc in the breast contour image and data points at corresponding positions in the reference image to obtain corresponding difference data;

[0018] A breast image to be reconstructed is generated according to the difference data and the breast contour image.

[0019] Optionally, before calculating the weight matrix of the mathematical model constructed based on the breast image to be reconstructed according to the breast morphology parameters in the ultrasound image, and solving the detector data matrix of the mathematical model using the breast image to be reconstructed, the method further includes:

[0020] Performing segmentation processing on the tissue body representing the breast tissue in the breast image to be reconstructed to obtain corresponding internal points of the tissue;

[0021] Discretizing the continuous light flux disturbance equation according to the internal points of the tissue to obtain a light diffusion equation representing the relationship between the light flux disturbance between different light sources and detectors;

[0022] Selecting a target light diffusion equation from the light diffusion equations according to the light source position condition and the detector position condition;

[0023] The target light diffusion equation is rearranged to obtain a mathematical model in matrix form.

[0024] Optionally, the step of arranging the target light diffusion equation to obtain a mathematical model in a matrix form includes:

[0025] The Green's function values ​​from the internal points of the tissue to the detector in the target light diffusion equation are used to construct a weight matrix of the mathematical model in the form of matrix elements;

[0026] Constructing the detector data matrix of the mathematical model in the form of matrix elements by using the uniform medium light flux part of the light source at the internal point of the tissue in each target light diffusion equation;

[0027] Constructing the optical absorption coefficient matrix of the mathematical model in the form of matrix elements using the perturbed absorption coefficient of each tissue internal point in the target light diffusion equation;

[0028] The mathematical model is constructed according to the weight matrix, the detector data matrix and the optical absorption coefficient matrix.

[0029] Optionally, the detector data matrix solution result and the weight matrix calculation result based on the mathematical model are used to solve the optical absorption coefficient matrix inside the breast tissue in the mathematical model by using the lesion spatial position information representing the breast tissue lesion area in the ultrasound image to obtain the corresponding optical characteristic information inside the breast tissue, including:

[0030] Based on the detector data matrix solution results and weight matrix calculation results of the mathematical model and using the lesion spatial position information representing the breast tissue lesion area in the ultrasound image, the regularization term of the objective function to be solved of the mathematical model is calculated; wherein the objective function to be solved is an objective function constructed with the minimum optical absorption coefficient matrix of the mathematical model as the goal;

[0031] The objective function to be solved is calculated by using least squares to obtain the optical absorption coefficient value inside the breast tissue in the mathematical model as the optical characteristic information inside the breast tissue.

[0032] Optionally, before calculating the regularization term of the objective function to be solved of the mathematical model based on the detector data matrix solution result and the weight matrix calculation result of the mathematical model and using the lesion spatial position information characterizing the breast tissue lesion area in the ultrasound image, the method further includes:

[0033] A regularization term is added to the objective function to be solved of the mathematical model; the regularization term includes a spatial regularization matrix and a regularization coefficient.

[0034] In a second aspect, the present application discloses a dynamic diffusion optical tomography device based on ultrasound position prior, comprising:

[0035] An image acquisition module, used to acquire a breast image to be reconstructed and a corresponding ultrasound image collected and preprocessed at a preset pressure of the breast to be tested; wherein the breast image to be reconstructed includes breast contour information and detector data information within the breast contour;

[0036] A matrix solving module, used to calculate the weight matrix of the mathematical model constructed based on the breast image to be reconstructed according to the breast morphology parameters in the ultrasound image, and solve the detector data matrix of the mathematical model using the breast image to be reconstructed; wherein the mathematical model is used to describe the mathematical relationship between the propagation of the light signal in the breast tissue of the breast to be tested and the detector receiving the propagated light signal;

[0037] An image reconstruction module is used to solve the optical absorption coefficient matrix inside the breast tissue in the mathematical model based on the detector data matrix solution results and weight matrix calculation results of the mathematical model and using the lesion spatial position information representing the breast tissue lesion area in the ultrasound image to obtain the corresponding optical characteristic information inside the breast tissue, and based on the post-processing results of the optical characteristic information, obtain the corresponding reconstructed breast image.

[0038] In a third aspect, the present application discloses an electronic device, comprising:

[0039] Memory, used to store computer programs;

[0040] A processor is used to execute the computer program to implement the steps of the aforementioned disclosed dynamic diffusion optical tomography method based on ultrasound position prior.

[0041] In a fourth aspect, the present application discloses a computer-readable storage medium for storing a computer program; wherein, when the computer program is executed by a processor, the steps of the aforementioned dynamic diffusion optical tomography method based on ultrasound position prior are implemented.

[0042] It can be seen that the present application discloses a dynamic diffusion optical tomography method based on ultrasound position prior, comprising: obtaining a breast image to be reconstructed and preprocessed at a preset pressure and a corresponding ultrasound image of a breast to be tested; wherein the breast image to be reconstructed includes breast contour information and detector data information within the breast contour; calculating a weight matrix of a mathematical model constructed based on the breast image to be reconstructed according to breast morphology parameters in the ultrasound image, and solving the detector data matrix of the mathematical model using the breast image to be reconstructed; wherein the mathematical model is used to describe the mathematical relationship between the propagation of an optical signal in the breast tissue of the breast to be tested and the detector receiving the propagated optical signal; based on the solution result of the detector data matrix of the mathematical model and the calculation result of the weight matrix and using the spatial position information of the lesion characterizing the breast tissue lesion area in the ultrasound image, solving the optical absorption coefficient matrix inside the breast tissue in the mathematical model to obtain the corresponding optical characteristic information inside the breast tissue, and based on the post-processing result of the optical characteristic information, obtaining the corresponding reconstructed breast image. It can be seen that by obtaining the pre-processed breast image to be reconstructed, the influence of system noise and environmental noise can be effectively reduced, the signal generated by the light source passing through the breast tissue can be highlighted, the signal-to-noise ratio and resolution of the image can be improved, and the image quality can be enhanced; the breast morphology parameter information of the ultrasound image is used to calculate the weight matrix information of the mathematical model used to describe the propagation of light signals in breast tissue and the reception of light signals by the detector, and the spatial position information of the lesion in the ultrasound image is used to solve the optical absorption coefficient matrix inside the breast tissue in the mathematical model, which reduces the pathological nature of the inverse problem solution and obtains the reconstructed image. By combining the two technologies of ultrasound imaging and optical imaging, ultrasound images provide high-resolution breast morphology parameters and lesion spatial position information, which provide important prior knowledge for the construction of mathematical models and the solution of inverse problems of optical imaging, and improve the accuracy and resolution of optical imaging. At the same time, optical imaging can reflect the optical properties of tissues and provide more physiological information for the diagnosis of breast cancer. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying creative work.

[0044] Figure 1 A flow chart of a dynamic diffusion optical tomography method based on ultrasound position prior disclosed in the present application;

[0045] Figure 2A flow chart of a breast image to be reconstructed and a corresponding ultrasound image acquisition method disclosed in the present application;

[0046] Figure 3 This is a schematic structural diagram of a dynamic diffusion optical tomography device based on ultrasound position prior disclosed in the present application;

[0047] Figure 4 This is a structural diagram of an electronic device disclosed in this application. DETAILED DESCRIPTION

[0048] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0049] Currently, in breast examinations, diffuse optical tomography (DOT) technology is used for non-invasive examinations. It uses diffuse light absorbed and scattered by tissues to reconstruct images, and can quantitatively measure components such as oxyhemoglobin, deoxyhemoglobin, blood oxygen, and water. It performs functional imaging of tissues to determine whether there is cancerous tissue in the breast, and it has a high sensitivity for breast cancer detection.

[0050] However, the solution of the inverse problem of DOT is nonlinear, ill-posed, and ill-posed, so DOT imaging has the problems of insufficient spatial resolution and poor imaging accuracy.

[0051] To this end, the present invention provides a dynamic diffusion optical tomography scheme based on ultrasound position prior, which can accurately solve the inverse problem of the DOT imaging process and obtain a reconstructed image with high resolution and accurate reconstruction results.

[0052] Reference Figure 1 As shown, the embodiment of the present invention discloses a dynamic diffusion optical tomography method based on ultrasound position prior, comprising:

[0053] Step S11: obtaining a breast image to be reconstructed and a corresponding ultrasound image collected and preprocessed at a preset pressure of the breast to be tested; wherein the breast image to be reconstructed includes breast contour information and detector data information within the breast contour.

[0054] In this embodiment, a preset pressure is applied to the breast to be tested. Generally, the pressure is applied to the breast to be tested from low to high according to the preset pressure by the acquisition device, and then the optical image and ultrasonic image of the breast in the process of applying pressure to the preset pressure are acquired. It should be noted that the acquired breast optical image needs to be preprocessed to obtain the reconstructed breast image with noise removed. This preset pressure is to simulate a specific physiological state or to better obtain the imaging data of breast tissue under different conditions. Ultrasonic images of the breast are acquired using an ultrasonic device. These ultrasonic images can provide the morphological parameters of the mammary gland of the breast to be tested and the spatial location information of potential lesions. Optical imaging equipment (including multiple light sources and detectors) is used to acquire multi-angle breast optical image data, which will be used for subsequent diffuse optical tomography analysis.

[0055] Step S12: Calculate the weight matrix of the mathematical model constructed based on the breast image to be reconstructed according to the breast morphology parameters in the ultrasound image, and use the breast image to be reconstructed to solve the detector data matrix of the mathematical model; wherein the mathematical model is used to describe the mathematical relationship between the propagation of the light signal in the breast tissue of the breast to be tested and the detector receiving the propagated light signal.

[0056] In this embodiment, before calculating the weight matrix of the mathematical model constructed based on the breast image to be reconstructed according to the breast morphology parameters in the ultrasound image and solving the detector data matrix of the mathematical model using the breast image to be reconstructed, the method also includes: segmenting the tissue body representing the breast tissue in the breast image to be reconstructed to obtain corresponding internal points of the tissue; discretizing the continuous light flux disturbance equation according to the internal points of the tissue to obtain a light diffusion equation representing the relationship between the light flux disturbance between different light sources and detectors; selecting a target light diffusion equation from the light diffusion equations according to the light source position conditions and the detector position conditions; and sorting the target light diffusion equation to obtain a mathematical model in matrix form. Specifically, the Green's function values ​​from the internal points of the tissue to the detector in each target light diffusion equation are used in the form of matrix elements to construct the weight matrix of the mathematical model; the uniform medium luminous flux part of the light source at the internal points of the tissue in each target light diffusion equation is used in the form of matrix elements to construct the detector data matrix of the mathematical model; the perturbation absorption coefficient of the internal points of the tissue in each target light diffusion equation is used in the form of matrix elements to construct the optical absorption coefficient matrix of the mathematical model; the mathematical model is constructed based on the weight matrix, the detector data matrix and the optical absorption coefficient matrix. It can be understood that according to the radiation propagation theory, the diffusion process of the light source after entering the tissue body conforms to the following formula:

[0057] ;

[0058] ;

[0059] ;

[0060] in, The speed of light propagation in the tissue. represents the light flux through the tissue. represents the tissue absorption coefficient, represents the tissue scattering coefficient, D is the diffusion coefficient, represents the reduced scattering coefficient, Indicates the intensity of the light source, represents the anisotropy factor, Represents the position vector within the tissue body.

[0061] Since optical imaging devices use continuous waves, that is, ,but:

[0062] ;

[0063] Based on the perturbation theory, the breast tissue can be approximated as a homogeneous medium and spatially perturbed heterogeneous tissue under macroscopic conditions, and its absorption coefficient can be approximated as:

[0064] ;

[0065] in, represents the background absorption coefficient of the homogeneous medium, represents the spatial disturbance absorption coefficient, then Substituting into the diffusion equation of light propagation, we obtain:

[0066] ;

[0067] ;

[0068] According to the Rytov approximation solution, we can know that:

[0069] ;

[0070] in, for The luminous flux at is the homogeneous medium portion of the luminous flux, The light source is The luminous flux disturbance at is the position vector in the tissue volume, is the position vector of the light source.

[0071] Based on the zero boundary condition, the tissue is surrounded by an ideal fully absorbing material, so when the photon crosses the boundary, it is immediately absorbed, causing the light density of the outer layer of the tissue boundary to drop sharply to zero. Assuming that the detector to the surface of the breast tissue is a vacuum condition and will not affect the light, then:

[0072] ;

[0073] ;

[0074] in, represents the position vector of a point inside the tissue, represents the position vector at the detector, Indicates that the light source is in the detector The luminous flux disturbance at represents the volume of the tissue, represents the absorption disturbance inside the tissue, Represented as a light source at a point inside the tissue The luminous flux in the uniform medium, Indicates that the light source is at a point inside the tissue The luminous flux disturbance at yes The differential at represents the Green's function from the integration point inside the tissue to the detector, is the attenuation coefficient, Represents the distance from the integration point inside the tissue to the detector.

[0075] Since the luminous flux of the homogeneous medium is much greater than the perturbation caused by the inhomogeneous medium, that is:

[0076] ;

[0077] ;

[0078] To the tissue After the dissection, N internal points of the tissue are obtained. The above formula is discretized, and the light diffusion equations of different light sources and detectors can be expressed by the following formula:

[0079] ;

[0080] in, Indicates light source , in the detector The flux disturbance at , N is the number of subdivided voxels, yes The Green's function value is It is a light source , in the detector The uniform medium luminous flux portion at yes The disturbance absorption coefficient at represents the voxel volume, is the position vector of voxel j, represents the position vector of detector i, A vector representing the position of the light source.

[0081] Since the total number of light sources used in the optical imaging device is M, and the number of detectors is K, the light propagation equation between the mth light source position and the Kth detector positions is integrated into a matrix form, that is, the formula of the mathematical model is as follows:

[0082] ;

[0083] ;

[0084] The detector data matrix consisting of M light sources and K detector data is expressed as follows:

[0085] ;

[0086] The weight matrix representation of the mathematical model is as follows:

[0087] ;

[0088] The optical absorption coefficient matrix inside the tissue to be solved is expressed as follows:

[0089] ;

[0090] The mathematical model can be expressed as follows:

[0091] .

[0092] Therefore, after obtaining the mathematical model, the breast tissue is segmented according to the breast morphology parameters obtained from the ultrasound image, and the weight matrix of the mathematical model can be calculated. , and the detector data matrix can be obtained by solving the breast image to be reconstructed .

[0093] Step S13: Based on the detector data matrix solution results and weight matrix calculation results of the mathematical model and using the lesion spatial position information representing the breast tissue lesion area in the ultrasound image, the optical absorption coefficient matrix inside the breast tissue in the mathematical model is solved to obtain the corresponding optical characteristic information inside the breast tissue, and based on the post-processing results of the optical characteristic information, a corresponding reconstructed breast image is obtained.

[0094] In this embodiment, the regularization term of the objective function to be solved of the mathematical model is calculated based on the solution results of the detector data matrix and the calculation results of the weight matrix of the mathematical model and using the spatial position information of the lesion characterizing the breast tissue lesion area in the ultrasound image; wherein the objective function to be solved is an objective function constructed with the goal of minimizing the optical absorption coefficient matrix of the mathematical model; the objective function to be solved is calculated using least squares to obtain the optical absorption coefficient value inside the breast tissue in the mathematical model as the optical characteristic information inside the breast tissue. It can be understood that in order to solve the optical absorption coefficient matrix , we need to solve the inverse problem, that is, to solve the objective function. Therefore, the mathematical model becomes . The initial objective function is: ,in. Represents the Euclidean norm. At the same time, before calculating the regularization term of the objective function to be solved of the mathematical model based on the detector data matrix solution result and the weight matrix calculation result of the mathematical model and using the lesion spatial position information representing the breast tissue lesion area in the ultrasound image, it also includes: adding a regularization term to the objective function to be solved of the mathematical model; the regularization term includes a spatial regularization matrix and a regularization coefficient. That is, in order to reduce the morbidity of the inverse problem solution, a regularization term can be added to the initial objective function of the specific mathematical model to obtain the objective function to be solved:

[0095] ;

[0096] Where L is the spatial regularization matrix and λ is the regularization coefficient.

[0097] The high-resolution spatial location information of the lesion is obtained through ultrasound images, and the breast tissue is divided into two areas, the lesion area and the non-lesion area. This information is added to the regularization term in a soft prior way. The specific form is:

[0098] ;

[0099] Among them, P is the number of voxel points that make up the lesion area.

[0100] Using the least squares method, we can solve for the value of X, which is the optical property information inside the breast tissue. The post-processing process may include further data analysis and adjustment of image contrast, brightness and other parameters to highlight specific tissue features. Specifically, a specific algorithm is used to convert the tissue coefficient map into a pseudo-color image for film reading, which is the reconstructed breast image. Pseudo-color images can more intuitively show the differences in optical properties of different tissue areas, making it easier for doctors to diagnose breast cancer.

[0101] It can be seen that the present application discloses a dynamic diffusion optical tomography method based on ultrasound position prior, comprising: obtaining a breast image to be reconstructed and preprocessed at a preset pressure and a corresponding ultrasound image of a breast to be tested; wherein the breast image to be reconstructed includes breast contour information and detector data information within the breast contour; calculating a weight matrix of a mathematical model constructed based on the breast image to be reconstructed according to breast morphology parameters in the ultrasound image, and solving the detector data matrix of the mathematical model using the breast image to be reconstructed; wherein the mathematical model is used to describe the mathematical relationship between the propagation of an optical signal in the breast tissue of the breast to be tested and the detector receiving the propagated optical signal; based on the solution result of the detector data matrix of the mathematical model and the calculation result of the weight matrix and using the spatial position information of the lesion characterizing the breast tissue lesion area in the ultrasound image, solving the optical absorption coefficient matrix inside the breast tissue in the mathematical model to obtain the corresponding optical characteristic information inside the breast tissue, and based on the post-processing result of the optical characteristic information, obtaining the corresponding reconstructed breast image. It can be seen that by obtaining the pre-processed breast image to be reconstructed, the influence of system noise and environmental noise can be effectively reduced, the signal generated by the light source passing through the breast tissue can be highlighted, the signal-to-noise ratio and resolution of the image can be improved, and the image quality can be enhanced; the breast morphology parameter information of the ultrasound image is used to calculate the weight matrix information of the mathematical model used to describe the propagation of light signals in breast tissue and the reception of light signals by the detector, and the spatial position information of the lesion in the ultrasound image is used to solve the optical absorption coefficient matrix inside the breast tissue in the mathematical model, which reduces the pathological nature of the inverse problem solution and obtains the reconstructed image. By combining the two technologies of ultrasound imaging and optical imaging, ultrasound images provide high-resolution breast morphology parameters and lesion spatial position information, which provide important prior knowledge for the construction of mathematical models and the solution of inverse problems of optical imaging, and improve the accuracy and resolution of optical imaging. At the same time, optical imaging can reflect the optical properties of tissues and provide more physiological information for the diagnosis of breast cancer.

[0102] Reference Figure 2 As shown, the embodiment of the present invention discloses a specific breast image to be reconstructed and a corresponding ultrasound image acquisition method. Compared with the previous embodiment, this embodiment further illustrates and optimizes the technical solution. Specifically:

[0103] Step S21: acquiring a plurality of initial DOT images and ultrasound images of the breast to be tested at a preset pressure, and acquiring an ambient dark frame of the process in which the pressure of the breast to be tested is gradually increased to reach the preset pressure.

[0104] In this embodiment, based on the theory of tumor capillary angiogenesis (i.e., there are new capillaries around the tumor tissue to provide nutrients for it), and the process of applying pressure to the breast tissue, the new capillaries of the tumor are collapsed, and the concentration of deoxyhemoglobin in the malignant tumor increases over time. DOT+ultrasound is designed to detect this dynamic physiological change, that is, the dynamic process of malignant lesion characteristics. Therefore, firstly, the breast tissue data of the breast to be tested is obtained, and the DOT detection data is collected by the acquisition device. Specifically, pressure is applied to a single breast to be tested, and the pressure is gradually increased from A mmHg to B mmHg, and then slowly released to A mmHg. In the process of applying pressure, K light sources are received by the detector end after passing through the breast tissue of the breast to be tested. During the acquisition, one light source is lit each time to obtain multi-angle optical image data of different light sources scattered and absorbed by the breast, and a total of M frames of images are collected, of which the number of B mmHg image frames is N frames. Before and after the acquisition of M frames of images, the light source is not lit, and the dark frame of the environment is collected. It should be noted that the acquisition of environmental dark frames before and after the acquisition of M frames covers the entire pressure change range from the pressure A mmHg gradually increasing to B mmHg and then releasing. The acquisition of environmental dark frames before and after this process can provide a unified environmental noise reference for the entire acquisition process. Then, when the breast tissue of the breast to be tested is under pressure of B mmHg, the transmitter of the ultrasound probe emits high-frequency sound waves and uses a mechanical rotation structure to perform a degree step. Through the process of emitting sound waves and receiving echoes multiple times, the ultrasound imaging system can obtain echo signals of breast tissue in different directions and positions to generate ultrasound images.

[0105] Step S22: performing image preprocessing on each of the initial DOT images using the ambient dark frame to obtain a plurality of preprocessed DOT images.

[0106] In this embodiment, in order to reduce the interference of acquisition equipment noise, environmental noise, etc., N frames of images corresponding to B mmHg are selected for preprocessing. The preprocessing mainly includes: performing operations such as darkening, normalization, smoothing, noise reduction, and spatial smoothing on the initial DOT image to obtain multiple preprocessed DOT images.

[0107] Step S23: Fuse all the preprocessed DOT images to obtain a fused DOT image, perform gradient descent processing on the fused DOT image, determine the point with the largest gradient descent in each image area, and connect the points with arcs to obtain a breast contour image.

[0108] In this embodiment, after obtaining multiple pre-processed DOT images, since these pre-processed DOT images are obtained from multiple angles or at different times, they contain information about breast tissue. The pre-processed DOT images are fused. This process may involve processing each pixel point, such as combining the brightness values ​​of corresponding pixels in N frames of images according to a certain algorithm (such as weighted average method, etc.), so as to obtain a complete static fused breast image. This fused DOT image can integrate the information of multiple frames of images, reduce noise interference, and more clearly present the overall characteristics of breast tissue. A gradient calculation algorithm is used for the fused DOT image. Common gradient algorithms include Sobel operator, Prewitt operator, etc. These operators can calculate the brightness change rate of the image in the horizontal and vertical directions. Through the selected gradient algorithm, the gradient value of each pixel point in the fused DOT image is calculated. The gradient value reflects the intensity of the brightness change of the fused DOT image at this point. Among all the calculated gradient values, find the point with the largest gradient drop. These points are usually located at the junction of breast tissue and the surrounding background, because the brightness change is most drastic here. The points with the largest gradient drop are connected along arcs. This connection process may need to consider the distribution pattern of the points, such as connecting them in a certain order (from left to right, from top to bottom, etc.) or according to the distance and angle relationship between adjacent points to form a closed curve, that is, to obtain the breast contour image.

[0109] Step S24: performing difference processing on the data points in the breast contour image to obtain a breast image to be reconstructed.

[0110] In this embodiment, the first frame of DOT image corresponding to each light source in the process of gradually increasing the pressure to reach the preset pressure is used as a reference image; the data points at each position within the range surrounded by the arc in the breast contour image are differenced with the data points at the corresponding position of the reference image to obtain corresponding difference data; and the breast image to be reconstructed is generated based on the difference data and the breast contour image. It can be understood that the specific implementation steps of the difference processing are as follows:

[0111] 1. Determine the reference image: In a specific imaging environment, multiple lamps (multiple light sources) are used to illuminate the breast tissue, and images are collected at multiple angles and multiple times. For each lamp, there is a series of corresponding image frames. Therefore, each lamp will produce a series of images during the data acquisition process. Among these images, the first frame image of each lamp is selected as the reference image. This is because the first frame image usually represents the initial optical state under specific experimental conditions (such as the initial pressure state, etc.).

[0112] 2. Data collection and contour determination: During the data collection process, by applying pressure to the breast tissue, multiple light sources and detectors are used to collect multi-angle optical image data. At the same time, N frames of images collected under a specific pressure (such as B mmHg) are fused and processed to obtain a complete static fused breast image StaticImg. The static fused breast image is gradient-solved, and the points with the largest gradient descent are connected along arcs to obtain a breast contour map. In this way, the area that needs to be processed by difference is determined, that is, the data within the breast contour.

[0113] 3. Difference processing: For the image sequence corresponding to each light, take its first frame image as a reference, and perform difference calculation between the data located in the breast contour in the subsequent image and the data at the corresponding position in the reference frame. Specifically, for each pixel or voxel point in the contour, calculate the difference between its optical data value in the subsequent frame and the data value at the corresponding position in the reference frame. That is: difference data = subsequent image pixel value - reference image pixel value. In this way, a series of difference data can be obtained. These difference data reflect the changes in light after passing through breast tissue at different time points or under different pressure conditions. They contain information on changes in light flux caused by changes in the internal structure of breast tissue (such as changes in the optical properties of tissue caused by lesions such as tumors) and external pressure. Through the above steps, detection data for subsequent optical imaging can be obtained. These detection data provide a basis for further image reconstruction and analysis.

[0114] It can be seen that the acquisition of multiple initial DOT images and ultrasound images of the breast to be tested at the preset pressure at the same time provides a rich source of information for subsequent fusion analysis. The combination of the two can more comprehensively describe the state of breast tissue. Obtaining the ambient dark frame of the breast to be tested when the pressure gradually increases to the preset pressure helps to eliminate the interference of factors such as ambient light on the DOT image and improve the image quality. The fused DOT image is obtained by fusing all pre-processed DOT images. This step can integrate image information from multiple angles or at different times to reduce information redundancy and uncertainty. The fused image is subjected to gradient descent processing and the maximum gradient descent point is determined. These points are then connected with arcs to obtain the breast contour image, which enables subsequent analysis to focus on the key areas of breast tissue and improves the accuracy and efficiency of the analysis. Difference processing can highlight the information of optical property changes caused by factors such as pressure changes or internal lesions of breast tissue, making these changes more obvious in the image and providing more valuable information for subsequent image reconstruction and lesion detection.

[0115] Reference Figure 3 As shown, the present invention accordingly discloses a dynamic diffusion optical tomography device based on ultrasound position prior, comprising:

[0116] An image acquisition module 11 is used to acquire a breast image to be reconstructed and a corresponding ultrasound image collected and preprocessed at a preset pressure of the breast to be tested; wherein the breast image to be reconstructed includes breast contour information and detector data information within the breast contour;

[0117] A matrix solving module 12 is used to calculate a weight matrix of a mathematical model constructed based on the breast image to be reconstructed according to breast morphology parameters in the ultrasound image, and to solve a detector data matrix of the mathematical model using the breast image to be reconstructed; wherein the mathematical model is used to describe the mathematical relationship between the propagation of an optical signal in the breast tissue of the breast to be tested and the reception of the propagated optical signal by the detector;

[0118] The image reconstruction module 13 is used to solve the optical absorption coefficient matrix inside the breast tissue in the mathematical model based on the detector data matrix solution results and weight matrix calculation results of the mathematical model and using the lesion spatial position information representing the breast tissue lesion area in the ultrasound image to obtain the corresponding optical characteristic information inside the breast tissue, and based on the post-processing results of the optical characteristic information, obtain the corresponding reconstructed breast image.

[0119] It can be seen that the present application discloses a method of obtaining a breast image to be reconstructed and preprocessed at a preset pressure of a breast to be tested and a corresponding ultrasound image; wherein the breast image to be reconstructed includes breast contour information and detector data information within the breast contour; a weight matrix of a mathematical model constructed based on the breast image to be reconstructed is calculated according to breast morphology parameters in the ultrasound image, and the detector data matrix of the mathematical model is solved using the breast image to be reconstructed; wherein the mathematical model is used to describe the mathematical relationship between the propagation of an optical signal in the breast tissue of the breast to be tested and the reception of the propagated optical signal by the detector; based on the solution result of the detector data matrix of the mathematical model and the calculation result of the weight matrix and using the spatial position information of the lesion characterizing the lesion area of ​​the breast tissue in the ultrasound image, the optical absorption coefficient matrix inside the breast tissue in the mathematical model is solved to obtain the corresponding optical characteristic information inside the breast tissue, and based on the post-processing result of the optical characteristic information, the corresponding reconstructed breast image is obtained. It can be seen that by obtaining the pre-processed breast image to be reconstructed, the influence of system noise and environmental noise can be effectively reduced, the signal generated by the light source passing through the breast tissue can be highlighted, the signal-to-noise ratio and resolution of the image can be improved, and the image quality can be enhanced; the breast morphology parameter information of the ultrasound image is used to calculate the weight matrix information of the mathematical model used to describe the propagation of light signals in breast tissue and the reception of light signals by the detector, and the spatial position information of the lesion in the ultrasound image is used to solve the optical absorption coefficient matrix inside the breast tissue in the mathematical model, which reduces the pathological nature of the inverse problem solution and obtains the reconstructed image. By combining the two technologies of ultrasound imaging and optical imaging, ultrasound images provide high-resolution breast morphology parameters and lesion spatial position information, which provide important prior knowledge for the construction of mathematical models and the solution of inverse problems of optical imaging, and improve the accuracy and resolution of optical imaging. At the same time, optical imaging can reflect the optical properties of tissues and provide more physiological information for the diagnosis of breast cancer.

[0120] Furthermore, the present application also discloses an electronic device. Figure 4 This is a structural diagram of an electronic device 20 according to an exemplary embodiment. The content in the diagram cannot be regarded as any limitation on the scope of use of the present application.

[0121] Figure 4A schematic diagram of the structure of an electronic device 20 provided in an embodiment of the present application. The electronic device 20 may specifically include: at least one processor 21, at least one memory 22, a power supply 23, a communication interface 24, an input / output interface 25, and a communication bus 26. The memory 22 is used to store a computer program, which is loaded and executed by the processor 21 to implement the relevant steps in the dynamic diffusion optical tomography method based on ultrasound position prior disclosed in any of the aforementioned embodiments. In addition, the electronic device 20 in this embodiment may specifically be an electronic computer.

[0122] In this embodiment, the power supply 23 is used to provide working voltage for each hardware device on the electronic device 20; the communication interface 24 can create a data transmission channel between the electronic device 20 and the external device, and the communication protocol it follows is any communication protocol that can be applied to the technical solution of the present application, and is not specifically limited here; the input and output interface 25 is used to obtain external input data or output data to the outside world, and its specific interface type can be selected according to specific application needs and is not specifically limited here.

[0123] Among them, the processor 21 may include one or more processing cores, such as a 4-core processor, an 8-core processor, etc. The processor 21 can be implemented in at least one hardware form of DSP (Digital Signal Processing), FPGA (Field-Programmable Gate Array), and PLA (Programmable Logic Array). The processor 21 may also include a main processor and a coprocessor. The main processor is a processor for processing data in the awake state, also known as a CPU (Central Processing Unit); the coprocessor is a low-power processor for processing data in the standby state. In some embodiments, the processor 21 may be integrated with a GPU (Graphics Processing Unit), which is responsible for rendering and drawing the content to be displayed on the display screen. In some embodiments, the processor 21 may also include an AI (Artificial Intelligence) processor, which is used to process computing operations related to machine learning.

[0124] In addition, the memory 22, as a carrier for storing resources, can be a read-only memory, a random access memory, a disk or an optical disk, etc. The resources stored thereon can include an operating system 221, a computer program 222, etc., and the storage method can be temporary storage or permanent storage.

[0125] Among them, the operating system 221 is used to manage and control the hardware devices and computer programs 222 on the electronic device 20, so as to realize the operation and processing of the massive data 223 in the memory 22 by the processor 21, which can be Windows Server, Netware, Unix, Linux, etc. In addition to including a computer program that can be used to complete the dynamic diffusion optical tomography method based on ultrasonic position prior performed by the electronic device 20 disclosed in any of the aforementioned embodiments, the computer program 222 can further include a computer program that can be used to complete other specific tasks. In addition to data transmitted from an external device received by the electronic device, the data 223 can also include data collected by its own input and output interface 25, etc.

[0126] Furthermore, the present application also discloses a computer-readable storage medium for storing a computer program; wherein, when the computer program is executed by a processor, the aforementioned disclosed dynamic diffusion optical tomography method based on ultrasound position prior is implemented. The specific steps of the method can refer to the corresponding contents disclosed in the aforementioned embodiments, and will not be repeated here.

[0127] In this specification, each embodiment is described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the embodiments can be referred to each other. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part.

[0128] Professionals may further appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented with 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 may 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 this application. The steps of the method or algorithm described in conjunction with the embodiments disclosed herein can be implemented directly with hardware, a software module executed by a processor, or a combination of the two. The software module can be placed in a random access memory RAM (Random Access Memory), memory, read-only memory ROM (Read Only Memory), electrically programmable EPROM (Electrically Programmable Read Only Memory), electrically erasable programmable EEPROM (ElectricErasable Programmable Read Only Memory), register, hard disk, removable disk, CD-ROM (CompactDisc-Read Only Memory), or any other form of storage medium known in the technical field.

[0129] Finally, it should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the presence of other identical elements in the process, method, article or device including the elements.

[0130] The scheme provided by the present invention is introduced in detail above. Specific examples are used in this article to illustrate the principle and implementation mode of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea. At the same time, for those skilled in the art, according to the idea of ​​the present invention, there will be changes in the specific implementation mode and application scope. In summary, the content of this specification should not be understood as limiting the present invention.

Claims

1. A dynamic diffusion optical tomography method based on ultrasound position prior, characterized in that: include: Obtaining a breast image to be reconstructed and a corresponding ultrasound image collected and preprocessed at a preset pressure of the breast to be tested; wherein the breast image to be reconstructed includes breast contour information and detector data information within the breast contour; Calculating a weight matrix of a mathematical model constructed based on the breast image to be reconstructed according to breast morphology parameters in the ultrasound image, and solving a detector data matrix of the mathematical model using the breast image to be reconstructed; wherein the mathematical model is used to describe the mathematical relationship between the propagation of an optical signal in the breast tissue of the breast to be tested and the reception of the propagated optical signal by the detector; Based on the detector data matrix solution results and weight matrix calculation results of the mathematical model and using the lesion spatial position information representing the breast tissue lesion area in the ultrasound image, the optical absorption coefficient matrix inside the breast tissue in the mathematical model is solved to obtain the corresponding optical characteristic information inside the breast tissue, and based on the post-processing results of the optical characteristic information, the corresponding reconstructed breast image is obtained.

2. The method for dynamic diffusion optical tomography based on ultrasound position prior according to claim 1, characterized in that: The step of obtaining a breast image to be reconstructed and a corresponding ultrasound image collected and preprocessed at a preset pressure of the breast to be tested comprises: Acquire multiple initial DOT images and ultrasound images of the breast to be tested at a preset pressure, and acquire an ambient dark frame of the breast to be tested during a process in which the pressure is gradually increased to reach the preset pressure; Using the ambient dark frame to perform image preprocessing on each of the initial DOT images to obtain a plurality of preprocessed DOT images; Fusing all the pre-processed DOT images to obtain a fused DOT image, performing gradient descent processing on the fused DOT image, determining points with the largest gradient descent in each image region, and connecting the points with arcs to obtain a breast contour image; The data points in the breast contour image are subjected to difference processing to obtain a breast image to be reconstructed.

3. The method for dynamic diffusion optical tomography based on ultrasound position prior according to claim 2, characterized in that: The step of performing difference processing on the data points in the breast contour image to obtain the breast image to be reconstructed includes: The first frame of DOT image corresponding to each light source when the pressure gradually increases to reach the preset pressure is used as a reference image; Performing difference calculation between data points at various positions within the range surrounded by the arc in the breast contour image and data points at corresponding positions in the reference image to obtain corresponding difference data; A breast image to be reconstructed is generated according to the difference data and the breast contour image.

4. The method for dynamic diffusion optical tomography based on ultrasound position prior according to claim 1, characterized in that: Before calculating the weight matrix of the mathematical model constructed based on the breast image to be reconstructed according to the breast morphology parameters in the ultrasound image, and solving the detector data matrix of the mathematical model using the breast image to be reconstructed, the method further includes: Performing segmentation processing on the tissue body representing the breast tissue in the breast image to be reconstructed to obtain corresponding internal points of the tissue; Discretizing the continuous light flux disturbance equation according to the internal points of the tissue to obtain a light diffusion equation representing the relationship between the light flux disturbance between different light sources and detectors; Selecting a target light diffusion equation from the light diffusion equations according to the light source position condition and the detector position condition; The target light diffusion equation is rearranged to obtain a mathematical model in matrix form.

5. The method for dynamic diffusion optical tomography based on ultrasound position prior according to claim 4, characterized in that: The target light diffusion equation is arranged to obtain a mathematical model in a matrix form, including: The Green's function values ​​from the internal points of the tissue to the detector in the target light diffusion equation are used to construct a weight matrix of the mathematical model in the form of matrix elements; Constructing the detector data matrix of the mathematical model in the form of matrix elements by using the uniform medium light flux part of the light source at the internal point of the tissue in each target light diffusion equation; Constructing the optical absorption coefficient matrix of the mathematical model in the form of matrix elements using the perturbed absorption coefficient of each tissue internal point in the target light diffusion equation; The mathematical model is constructed according to the weight matrix, the detector data matrix and the optical absorption coefficient matrix.

6. The method for dynamic diffusion optical tomography based on ultrasound position prior according to claim 5, characterized in that: The detector data matrix solution result and the weight matrix calculation result based on the mathematical model are used to solve the optical absorption coefficient matrix inside the breast tissue in the mathematical model by using the lesion spatial position information representing the breast tissue lesion area in the ultrasound image to obtain the corresponding optical characteristic information inside the breast tissue, including: Based on the detector data matrix solution results and weight matrix calculation results of the mathematical model and using the lesion spatial position information representing the breast tissue lesion area in the ultrasound image, the regularization term of the objective function to be solved of the mathematical model is calculated; wherein the objective function to be solved is an objective function constructed with the minimum optical absorption coefficient matrix of the mathematical model as the goal; The objective function to be solved is calculated by using least squares to obtain the optical absorption coefficient value inside the breast tissue in the mathematical model as the optical characteristic information inside the breast tissue.

7. The method for dynamic diffusion optical tomography based on ultrasound position prior according to claim 6, characterized in that: Before calculating the regularization term of the objective function to be solved of the mathematical model based on the detector data matrix solution result and the weight matrix calculation result of the mathematical model and using the lesion spatial position information representing the breast tissue lesion area in the ultrasound image, the method further includes: A regularization term is added to the objective function to be solved of the mathematical model; the regularization term includes a spatial regularization matrix and a regularization coefficient.

8. A dynamic diffusion optical tomography device based on ultrasound position prior, characterized in that: include: An image acquisition module, used to acquire a breast image to be reconstructed and a corresponding ultrasound image collected and preprocessed at a preset pressure of the breast to be tested; wherein the breast image to be reconstructed includes breast contour information and detector data information within the breast contour; A matrix solving module, used to calculate the weight matrix of the mathematical model constructed based on the breast image to be reconstructed according to the breast morphology parameters in the ultrasound image, and solve the detector data matrix of the mathematical model using the breast image to be reconstructed; wherein the mathematical model is used to describe the mathematical relationship between the propagation of the light signal in the breast tissue of the breast to be tested and the detector receiving the propagated light signal; An image reconstruction module is used to solve the optical absorption coefficient matrix inside the breast tissue in the mathematical model based on the detector data matrix solution results and weight matrix calculation results of the mathematical model and using the lesion spatial position information representing the breast tissue lesion area in the ultrasound image to obtain the corresponding optical characteristic information inside the breast tissue, and based on the post-processing results of the optical characteristic information, obtain the corresponding reconstructed breast image.

9. An electronic device, characterized in that: include: Memory, used to store computer programs; A processor is used to execute the computer program to implement the steps of the dynamic diffusion optical tomography method based on ultrasound position prior according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: Used to store computer programs; wherein, when the computer program is executed by a processor, the steps of the dynamic diffusion optical tomography method based on ultrasound position prior as described in any one of claims 1 to 7 are implemented.

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