Photon weight fused diffused light brain tissue blood oxygen concentration variable quantity imaging method and related product

Abstract

The invention discloses a photon weight fused diffused light brain tissue blood oxygen concentration variable quantity imaging method and related products, and relates to the technical field of biological tissue blood oxygen imaging. The method comprises the steps that experimental data obtained by irradiating a tested tissue through light sources of two wavelengths are obtained; for the experimental data corresponding to the light source of each wavelength, performing the following calculation: calculating an average photon transmission path obtained by the kth light probe combination in the ith voxel unit by using a formula; calculating the photon weight obtained by the kth light detection combination in the ith voxel unit by using a formula; calculating the tissue absorption coefficient variation of the ith voxel unit by using a formula; and finally, calculating the variation of the concentration of the oxyhemoglobin and the concentration of the deoxidized hemoglobin by utilizing calculation data obtained by the two wavelengths respectively. According to the method for fusing the photon weight, the accurate blood oxygen concentration variation of the brain tissue can be obtained by using a small number of S-D combined photon signals in a weight calculation mode.

Description

Technical Field

[0001] The present application relates to the technical field of biological tissue blood oxygen imaging, and in particular to a method for imaging changes in brain tissue blood oxygen concentration using diffuse light fused with photon weights and related products. Background Art

[0002] Blood oxygenation in biological tissues is an important physiological parameter, especially in brain tissue, where blood oxygen levels are closely related to neuronal activity and blood supply. For example, under external stimuli, or when the brain performs language or cognitive tasks, central neurons are activated, causing dilation of the capillary network in the cerebral cortex and accelerated blood circulation, resulting in a rich oxygen supply and an increase in brain tissue hemoglobin concentration and oxygen saturation. In pathological conditions such as stroke and Alzheimer's disease, central neurons or capillary networks in the brain cannot be effectively activated, resulting in symptoms such as decreased blood oxygen levels or even hypoxia. Therefore, changes in brain tissue blood oxygen concentration under external stimuli are closely related to physiological status and are a functional imaging technology for detecting various neurological diseases.

[0003] Near-infrared diffuse optical imaging (NIDIO) is a technique for measuring blood oxygen levels in biological tissue. It relies on placing multiple light sources and detectors on the surface of the tissue being measured, forming multiple light source-detector (SD) combinations. Different light sources sequentially emit a large number of photons into the tissue. After several scattering or absorption events within the tissue, a portion of the photons return to the tissue surface and are collected by the detector, thereby acquiring the photon signal. During signal processing, the change in the light intensity collected by the detector is first used to estimate the change in the tissue's absorption coefficient (Δμa). Since the primary absorbers in biological tissue are oxyhemoglobin (oxyhemoglobin), deoxyhemoglobin (deoxyhemoglobin), and water, the absorption coefficient changes at two or more wavelengths can be used to calculate the oxyhemoglobin concentration ([ΔHbO2]) and the deoxyhemoglobin concentration ([ΔHb]).

[0004] The process of reconstructing two-dimensional or three-dimensional images of tissue [ΔHbO2] and [ΔHb] using the light intensity data acquired by the above light source-detector (SD) combination is called blood oxygen imaging. Traditional blood oxygen imaging is divided into two methods: the modified Beer-Lambert (MBL) method and the finite element method (FEM). The MBL method maps the blood oxygen variation obtained at each SD position to the local area covered by that position. The blood oxygen variation of all local areas is then stitched together to obtain a global blood oxygenation image (or blood oxygenation map). This method is computationally simple and produces stable results. It requires only a small number of SD combinations (less than 50) to achieve imaging, and the equipment cost is low. However, MBL only produces a two-dimensional blood oxygen variation map and cannot reflect blood oxygen variation at different depths within the tissue.

[0005] FEM discretizes the tissue being measured into a large number of volumetric units and derives the discrete form of the differential equation for photon propagation within these units, forming a solution matrix. Furthermore, the matrix solution is used to determine the change in blood oxygen concentration ([ΔHbO2] and [ΔHb]) for each volumetric unit, thereby generating a three-dimensional image of the change in blood oxygen concentration. Although the FEM method can obtain information on blood oxygen variation at different tissue depths, the discrete form of the differential equation requires a large number of SD combinations (greater than 300) to produce a stable three-dimensional image, significantly increasing the hardware cost of the light source and detector. Using a small number of SD combinations (<50) to obtain photon information, FEM blood oxygen imaging is extremely unstable and subject to significant errors. Summary of the Invention

[0006] The purpose of this application is to provide an imaging method and related products for the change in blood oxygen concentration in brain tissue using diffuse light that integrates photon weights, which can obtain accurate changes in blood oxygen concentration in brain tissue using photon information obtained by a small number of SD combinations.

[0007] To achieve the above objectives, this application provides the following solutions:

[0008] In a first aspect, the present application provides a method for imaging changes in brain tissue blood oxygen concentration using diffuse light fused with photon weights, comprising:

[0009] Acquire experimental data obtained by irradiating the measured tissue with light sources of two wavelengths; the experimental data are all photon packets and corresponding photon packet information after Monte Carlo simulation of the measured tissue; the photon packet information includes the photon energy and transmission path of the photon packet; the photon packet is a combination of photons with the same path; the Monte Carlo simulation is performed using a plurality of optical probe combinations; each of the optical probe combinations can acquire the photon energy and transmission path of a plurality of photon packets; each of the optical probe combinations includes a light source and a plurality of detectors; the optical probe combination is arranged on the measured tissue; the measured tissue is evenly divided into a plurality of voxel units;

[0010] The following calculations are performed for the experimental data corresponding to each wavelength of the light source:

[0011] Using the formula Calculate the average photon transmission path acquired by the kth optical probe combination in the i-th voxel unit; where w (q,k) represents the total energy of the qth photon packet, s (i,q,k) is the transmission path of the qth photon packet in the i-th voxel unit, H k represents the total number of photon packets acquired by the k-th optical probe combination;

[0012] Using the formula Calculate the photon weight acquired by the kth light probe combination in the i-th voxel unit; where ss (i,k) represents the average photon transmission path acquired by the k-th optical probe combination in the i-th voxel unit;

[0013] Using the formula Calculate the change in tissue absorption coefficient of the i-th voxel unit; where M represents the total number of light sources, J represents the number of detectors in each light-detection combination, and ws (i,k) represents the photon weight acquired by the kth optical probe combination in the i-th voxel unit, Δμ a (k) represents the average change in tissue absorption coefficient of the area covered by the kth optical probe combination;

[0014] The changes in the concentrations of oxyhemoglobin and deoxyhemoglobin in the i-th voxel unit are calculated using the first tissue absorption coefficient change and the second tissue absorption coefficient change; the first tissue absorption coefficient change is the change in the tissue absorption coefficient of the i-th voxel unit calculated using the experimental data corresponding to the light source of the first wavelength; the second tissue absorption coefficient change is the change in the tissue absorption coefficient of the i-th voxel unit calculated using the experimental data corresponding to the light source of the second wavelength.

[0015] In a second aspect, the present application provides a computer device comprising: 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 any of the above-described methods for imaging changes in blood oxygen concentration in brain tissue using diffuse light fused with photon weights.

[0016] In a third aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the imaging method of the change in the blood oxygen concentration of brain tissue using diffuse light fused with photon weights as described above.

[0017] In a fourth aspect, the present application provides a computer program product, comprising a computer program, which, when executed by a processor, implements the imaging method of the change in blood oxygen concentration of brain tissue using diffuse light fused with photon weights as described above.

[0018] According to the specific embodiments provided in this application, this application discloses the following technical effects:

[0019] The present application provides an imaging method and related products for the change in blood oxygen concentration in brain tissue using diffuse light that integrates photon weights, the method comprising: obtaining experimental data obtained by irradiating the measured tissue with light sources of two wavelengths; the experimental data are all photon packets and corresponding photon packet information after Monte Carlo simulation of the measured tissue; the photon packet information includes the photon energy and transmission path of the photon packet; the photon packet is a combination of photons with the same path; the Monte Carlo simulation is performed using a number of optical probe combinations; each of the optical probe combinations can obtain the photon energy and transmission path of a number of photon packets; each of the optical probe combinations comprises a light source and a number of detectors; the optical probe combination is arranged on the measured tissue; the measured tissue is evenly divided into a number of voxel units; the experimental data corresponding to the light source of each wavelength are calculated as follows: using the formula Calculate the average photon transmission path acquired by the kth optical probe combination in the i-th voxel unit; where w (q,k) represents the total energy of the qth photon packet, s (i,q,k) is the transmission path of the qth photon packet in the i-th voxel unit, H k Represents the total number of photon packets acquired by the k-th optical probe combination; using the formula Calculate the photon weight acquired by the kth light probe combination in the i-th voxel unit; where ss (i,k) represents the average photon transmission path acquired by the kth optical probe combination in the i-th voxel unit, ss (i) Represents the total photon transmission path in the i-th voxel unit; using the formula Calculate the change in tissue absorption coefficient of the i-th voxel unit; where M represents the total number of light sources, J represents the number of detectors in each light-detection combination, and ws (i,k) represents the photon weight acquired by the kth optical probe combination in the i-th voxel unit, Δμ a (k) represents the average change in the tissue absorption coefficient of the area covered by the kth optical probe combination; the first tissue absorption coefficient change and the second tissue absorption coefficient change are used to calculate the change in the concentrations of oxyhemoglobin and deoxyhemoglobin in the i-th voxel unit; the first tissue absorption coefficient change is the change in the tissue absorption coefficient of the i-th voxel unit calculated using the experimental data corresponding to the first wavelength light source; the second tissue absorption coefficient change is the change in the tissue absorption coefficient of the i-th voxel unit calculated using the experimental data corresponding to the second wavelength light source. This application proposes a method for fusing photon weights, which can reflect the contribution weights of different photons to each voxel unit. By calculating through weights, accurate changes in brain tissue blood oxygen concentration can be obtained using a small number of SD combined photon signals. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0021] Figure 1 This is a diagram of the application environment of a method for imaging changes in blood oxygen concentration in brain tissue using diffuse light that integrates photon weights in one embodiment of the present application.

[0022] Figure 2 A flowchart of a method for imaging changes in blood oxygen concentration in brain tissue using diffuse light fused with photon weights provided in one embodiment of the present application.

[0023] Figure 3 A schematic diagram of a three-dimensional tissue model divided into voxel units provided in one embodiment of the present application.

[0024] Figure 4 A schematic diagram of the distribution of light sources and detectors on the surface of the tissue being measured provided in one embodiment of the present application.

[0025] FIG5 is a schematic diagram of changes in absorption coefficient of brain tissue at different depths during 830 nm light measurement provided by an embodiment of the present application.

[0026] FIG6 is a schematic diagram of changes in absorption coefficient of brain tissue at different depths during 690 nm light measurement according to an embodiment of the present application.

[0027] FIG7 is a schematic diagram of changes in brain tissue oxygenated hemoglobin concentration at different depths provided by an embodiment of the present application.

[0028] FIG8 is a schematic diagram of changes in deoxyhemoglobin concentration in brain tissue at different depths provided by an embodiment of the present application.

[0029] Figure 9 A schematic diagram of the overall process provided for one embodiment of the present application.

[0030] Figure 10 This is a schematic diagram of the implementation process of step B4 provided in one embodiment of the present application.

[0031] Figure 11 A schematic diagram of the structure of a computer device provided in one embodiment of the present application. DETAILED DESCRIPTION

[0032] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0033] In order to solve the problem that the existing technology cannot take into account the advantages of low cost, stable imaging, and reflecting information at different depths within the tissue, the present application proposes an imaging method for the change in blood oxygen concentration in brain tissue using diffused light fused with photon weight. The method can use a small number of SD combinations (less than 50) of photon signals to stably obtain a three-dimensional image of the change in blood oxygen concentration in brain tissue.

[0034] In order to make the above-mentioned purposes, features and advantages of the present application more obvious and easy to understand, the present application is further described in detail below with reference to the accompanying drawings and specific implementation methods.

[0035] The imaging method of the variation of blood oxygen concentration in brain tissue by diffuse light fusion photon weight provided in the embodiment of the present application can be applied to Figure 1In the application environment shown. Among them, the terminal 102 communicates with the server 104 through the network. The data storage system can store the data that the server 104 needs to process. The data storage system can be set up separately, or it can be integrated on the server 104, or it can be placed on the cloud or other servers. Among them, the terminal 102 can be, but is not limited to, various desktop computers, laptops, smart phones, tablets, Internet of Things devices and portable wearable devices. The Internet of Things devices can be smart speakers, smart TVs, smart air conditioners, smart car-mounted devices, etc. Portable wearable devices can be smart watches, smart bracelets, head-mounted devices, etc. The server 104 can be implemented as an independent server or a server cluster consisting of multiple servers, or it can be a cloud server.

[0036] In an exemplary embodiment, Figure 2 As shown, a method for imaging the change in blood oxygen concentration of brain tissue with diffuse light fused with photon weight is provided. The method is executed by a computer device, specifically a computer device such as a terminal or a server, or a terminal and a server. In the embodiment of the present application, the method is applied to Figure 1 The server 104 in the example is used as an example to illustrate the method, which includes the following steps S1 to S5.

[0037] S1. Acquire experimental data obtained by irradiating the measured tissue with light sources of two wavelengths; the experimental data are all photon packets and corresponding photon packet information after Monte Carlo simulation of the measured tissue; the photon packet information includes the photon energy and transmission path of the photon packet; the photon packet is a combination of photons with the same path; the Monte Carlo simulation is performed using several optical probe combinations (SD combinations); each of the optical probe combinations can acquire the photon energy and transmission path of several photon packets; each of the optical probe combinations includes a light source and several detectors; the optical probe combination is set on the measured tissue; the measured tissue is evenly divided into several voxel units.

[0038] In this embodiment, the measured tissue is the forehead of the subject, and the measured tissue is evenly divided into 1536 voxel units; the Monte Carlo simulation is performed using 8 optical probe combinations; each of the optical probe combinations includes 1 light source and 6 detectors.

[0039] Specifically, a total of M*J SD combinations (for the convenience of expression, the SD combination is also referred to as a light-detection combination in this application) are arranged on the surface of the tissue to be measured, which are divided into M groups, each group including 1 light source and J detectors surrounding the light source. During the data acquisition process, the M groups of light sources emit light in sequence, and the J detectors simultaneously collect the photons escaping from the tissue surface, thus completing the complete data acquisition of M*J SD positions. When M=8 and J=6, there are a total of 48 SD combinations to collect photon signals. This embodiment can stably reconstruct an image of the change in blood oxygen concentration of brain tissue in a three-dimensional voxel unit (for example, 16*16*6) from less measurement data (for example, 48=8*6).

[0040] The energy and path of the photon packet in this application can be obtained through photon Monte Carlo simulation; the process is to place a light source and a detector on the tissue surface, set the optical properties of the tissue, and use a computer to simulate the absorption, scattering and transmission of the photon packet in the tissue model, so as to obtain the energy and transmission path of the detected photon packet.

[0041] Monte Carlo simulation is a computer simulation. Because physical experiments can only obtain the detected light intensities I(t0,k) and I(t1,k), it is necessary to know the average photon transmission path MPL to obtain the tissue absorption change Δμ. a However, the MPL cannot be measured directly. Traditionally, it has been derived using analytical expressions for the diffusion equation of diffuse light. This embodiment uses the weighted summation of the photon packet's transmission path to obtain the MPL, which can only be obtained through Monte Carlo simulation. Monte Carlo simulation can describe the random process of photon transmission within tissue. By setting the optical properties (absorption, scattering, refraction, etc.), any Monte Carlo software (MCX, MCVM, etc.) can be used to determine the energy of the photon packet and its path within a voxel. Note that the energy of the photon packet here is obtained during the Monte Carlo simulation and has nothing to do with the experimentally detected light intensities I(t0, k) and I(t1, k). Computer simulation of photon transmission is a complex process and can only be performed using readily available Monte Carlo software (MCX, MCVM, etc.). This embodiment utilizes only the Monte Carlo simulation results (the energy of the photon packet and its path within a voxel) to calculate the average path and photon weight.

[0042] In this embodiment, the tissue to be measured (or phantom) is divided into n=1536 (16*16*6) units (i.e., voxel units). Figure 3 As shown, it is a schematic diagram of the three-dimensional tissue model divided into voxel units in this embodiment.

[0043] Arrange the light source (S) and detector (D) on the tissue surface. There are M*J SD combinations. Figure 4, which is a schematic diagram of the distribution of light sources and detectors on the surface of the tissue being measured (in this example, on the forehead of the human brain) when M = 8 and J = 6. Here, S1 and S8 represent the positions of the light sources, and D11-D16, D21-D26, ..., D81-D86 represent the positions of the detectors. Here, S1 and D11-16 form one SD combination, and so on, there are a total of eight SD combinations.

[0044] The following calculations are performed for the experimental data corresponding to each wavelength of the light source (the average transmission path MPL of the photon can be calculated by Monte Carlo simulation of the photon, and the average change of the tissue absorption coefficient Δμa of the area covered by all SD combinations is used to calculate the change of the tissue absorption coefficient of each voxel unit Δμ a (i)

[0045] S2. Using formula Calculate the average photon transmission path acquired by the kth optical probe combination in the i-th voxel unit; where w (q,k) represents the total energy of the qth photon packet, s (i,q,k) is the transmission path of the qth photon packet in the i-th voxel unit, H k Represents the total number of photon packets captured by the kth optical probe combination.

[0046] The above average photon transmission path is explained as follows: w(q,k) is multiplied by s(i,q,k) and for all H k The photon packets are summed (that is, ), get all H k The sum of the photon paths of the photon packets in the i-th voxel unit is divided by H k The total energy of the photon packet (that is, ), that is, the average photon transmission path of the i-th voxel unit is obtained.

[0047] S3. Using formula Calculate the photon weight acquired by the kth light probe combination in the i-th voxel unit; where ss (i,k) represents the average photon transmission path acquired by the k-th optical probe combination in the i-th voxel unit, represents the total photon transmission path in the i-th voxel unit in all optical probe combinations.

[0048] The above photon weight calculation process is explained as follows: sum all the average photon transmission paths (that is, ), and the sum of the average photon paths of all optical probe combinations is obtained. Divide the photon path of the kth optical probe combination by this sum (i.e. ), that is, the photon weight of the optical probe combination is obtained.

[0049] According to this formula, the photon weight of any SD combination in the i-th voxel unit can be determined.

[0050] S4. Use formula Calculate the change in tissue absorption coefficient of the i-th voxel unit; where M represents the total number of light sources, J represents the number of detectors in each light-detection combination, and ws (i,k) represents the photon weight acquired by the kth optical probe combination in the i-th voxel unit, Δμ a (k) represents the average change in tissue absorption coefficient in the area covered by the kth optical probe combination.

[0051] The calculation process of the tissue absorption coefficient change of the i-th voxel unit is explained as follows: ws(i,k) multiplied by Δμ a (k) and sum all SD combinations (i.e. ), the absorption coefficient changes of all SD combinations are obtained by the photon-weighted sum of the i-th voxel unit, which is divided by the sum of the photon weights (that is, ), that is, the change in tissue absorption coefficient of the i-th voxel unit is obtained.

[0052] Therefore, this embodiment realizes the calculation of the change in tissue absorption coefficient of each voxel unit fused with photon weights.

[0053] S5. Calculate the changes in the concentrations of oxyhemoglobin and deoxyhemoglobin in the i-th voxel unit using the first tissue absorption coefficient change and the second tissue absorption coefficient change; the first tissue absorption coefficient change is the change in the tissue absorption coefficient of the i-th voxel unit calculated using the experimental data corresponding to the light source of the first wavelength; the second tissue absorption coefficient change is the change in the tissue absorption coefficient of the i-th voxel unit calculated using the experimental data corresponding to the light source of the second wavelength.

[0054] This embodiment uses near-infrared light of two wavelengths (λ1 and λ2) to illuminate the tissue being measured, and according to the above formula, obtains the changes in the tissue absorption coefficient, namely Δμa(i,λ1) and Δμa(i,λ2). Based on the relationship between the absorption coefficient and the hemoglobin concentration, the changes in the oxyhemoglobin and deoxyhemoglobin concentrations of the i-th voxel unit can be obtained:

[0055]

[0056] Among them, ε HbO2 (λ1) and ε Hb (λ1) are the extinction coefficients of oxygenated hemoglobin and deoxygenated hemoglobin at wavelength λ1; ε HbO2 (λ2) and ε Hb(λ2) are the extinction coefficients of oxyhemoglobin and deoxyhemoglobin at wavelength λ2; Δ[HbO2](i) is the change in the concentration of oxyhemoglobin in the i-th voxel; Δμ a (i,λ2) is the change in tissue absorption coefficient at wavelength λ2, i.e., the change in the second tissue absorption coefficient; Δμ a (i,λ1) is the change in tissue absorption coefficient at wavelength λ1, that is, the first tissue absorption coefficient change, and Δ[Hb](i) is the change in deoxyhemoglobin concentration in the i-th voxel unit.

[0057] The calculation formula of the change in the concentration of oxyhemoglobin and deoxyhemoglobin is explained as follows: According to the principle of photon absorption of biological tissue, when the wavelength of incident light is λ, the tissue absorption coefficient μ a (i,λ) is equal to the sum of the coefficients of all light absorbers. In human tissue, the main light absorbers are oxyhemoglobin, deoxyhemoglobin and water, that is:

[0058] μ a (i,λ)=C [HbO2] (i,λ)+C [Hb] (i,λ)+C water (i,λ);

[0059] Among them, C [HbO2] (i,λ),C [Hb] (i,λ),C water (i, λ) are the absorption coefficients of oxyhemoglobin, deoxyhemoglobin, and water, respectively. On the other hand, the absorption coefficients of oxyhemoglobin and deoxyhemoglobin are their concentrations multiplied by their extinction coefficients, i.e.:

[0060] C [HbO2] (i,λ)=ε HbO2 (λ)[HbO2](i);C [Hb] (i,λ)=ε Hb (λ)[Hb](i);

[0061] Here ε HbO2 and ε Hb is the extinction coefficient of oxyhemoglobin and deoxyhemoglobin at a given wavelength λ, and its value can be obtained from the literature. [HbO2] and [Hb] are the concentrations of oxyhemoglobin and deoxyhemoglobin, respectively. Where [HbO2](i) is the concentration of oxyhemoglobin per voxel i, and [Hb](i) is the concentration of deoxyhemoglobin per voxel i.

[0062] Since the absorption coefficient of water is constant, μ a (i,λ) calculation formula and C[HbO2] (i,λ) calculation formula, the change of tissue absorption coefficient from time t0 to time t1 is:

[0063] Δμ a (i,λ)=ε HbO2 (λ)Δ[HbO2](i)+ε Hb (λ)Δ[Hb](i);

[0064] Here, the symbol Δ represents the change. That is, Δ[HbO2](i) is the change in the concentration of oxygenated hemoglobin in the i-th voxel unit; Δ[Hb](i) is the change in the concentration of deoxygenated hemoglobin in the i-th voxel unit.

[0065] Using two wavelengths (λ1 and λ2) of near-infrared light to illuminate the tissue under test, the above formula is obtained:

[0066] Δμ a (i,λ1)=ε HbO2 (λ1)Δ[HbO2](i)+ε Hb (λ1)Δ[Hb](i);

[0067] Δμ a (i,λ2)=ε HbO2 (λ2)Δ[HbO2](i)+ε Hb (λ2)Δ[Hb](i);

[0068] By solving the unknown variables Δ[HbO2](i) and Δ[Hb](i) of this set of two linear equations simultaneously, we can obtain the calculation formulas for the changes in the concentrations of oxyhemoglobin and deoxyhemoglobin mentioned above.

[0069] In addition, the average change in tissue absorption coefficient Δμ in the area covered by the kth optical probe combination is a The calculation method of (k) includes:

[0070] A1. Using the transmission path of the qth photon packet in each voxel unit, calculate the total transmission path of the qth photon packet. The calculation formula is:

[0071]

[0072] Where n represents the total number of voxel units.

[0073] A2. Calculate the average photon transmission path of the k-th optical probe combination using the total transmission path and total energy of each photon packet acquired by the k-th optical probe combination. The calculation formula is:

[0074]

[0075] Among them, L(q,k) represents the total transmission path of the qth photon packet.

[0076] A3. Calculate the change in photon density from time t0 to time t1 using the formula ΔOD(k) = ln(I(t0,k) / I(t1,k)). Here, the light intensities obtained from the kth SD combination at time t0 and time t1 are I(t0,k) and I(t1,k), respectively. ln(·) is the natural logarithm.

[0077] A4. Using the formula Δμ a (k) = ΔOD(k) / MPL(k) calculates the average change in tissue absorption coefficient in the area covered by the k-th optical probe combination; where ΔOD(k) represents the change in photon density from time t0 to time t1, and MPL(k) represents the average photon transmission path of the k-th optical probe combination.

[0078] The specific experimental process and information acquisition process include the following steps:

[0079] The imaging method of this embodiment was quantitatively verified in a verbal fluent task experiment on the human brain. The experiment included the following process:

[0080] (i) The subject sits on a chair; the researcher wipes the test area with medical alcohol cotton.

[0081] (ii) An optical probe was fixed to the subject's forehead using a medical bandage. The probe contained 8*6 SD combination sensors (i.e., 8 light source positions and 48 detector positions).

[0082] (iii) Pre-task measurements were performed while the subjects remained in a resting state. Each light source sequentially emitted photons of 830 nm and 690 nm wavelengths into the cerebral cortex, and eight detectors surrounding the light source simultaneously collected the photons. Each of the eight light sources emitted light sequentially, with the duration of each light source emitting and collecting photons being 0.2 seconds. After eight light source switching cycles, the pre-task optical measurement took a total of 1.6 seconds to complete.

[0083] (iv) The subjects completed a language fluency test under guidance, which specifically included: forming words using simple characters (e.g., sky, earth, cloud, wind, black, white, soil, etc.) for a total of 60 seconds.

[0084] (v) Immediately after the subject finishes the verbal fluency test, the optical measurement begins in the same manner as in step (iii); the total time for the post-task optical measurement is 1.6 seconds.

[0085] The light intensity signals (i.e., I(t0, k) and I(t1, k)) collected before and after the task (the experiment only obtained the light intensity signal; the photon path and photon energy of this embodiment are obtained by computer simulation of photon transmission (i.e., photon Monte Carlo simulation); photon Monte Carlo simulation is implemented by special software (e.g., MCX, MCVM, and the optical parameters used in the simulation can be obtained from the literature) are processed using the above-mentioned imaging method of this embodiment, that is, a three-dimensional imaging of the change in the absorption coefficient of the brain tissue is obtained (as shown in Figures 5 and 6, where Figure 5 (a) shows the absorption coefficient of the brain tissue at a depth of 5 mm in the 830 nm light measurement). Figure 5(b) shows the change in absorption coefficient of brain tissue at a depth of 10mm in 830nm light measurement; Figure 5(c) shows the change in absorption coefficient of brain tissue at a depth of 15mm in 830nm light measurement; Figure 5(d) shows the change in absorption coefficient of brain tissue at a depth of 20mm in 830nm light measurement; Figure 5(e) shows the change in absorption coefficient of brain tissue at a depth of 25mm in 830nm light measurement; Figure 5(f) shows the change in absorption coefficient of brain tissue at a depth of 30mm in 830nm light measurement. Figure 6(a) shows the change in absorption coefficient of brain tissue at a depth of 5mm in 690nm light measurement; Figure 6(b) shows the change in the absorption coefficient of brain tissue at a depth of 10 mm when measured with 690 nm light; Figure 6(c) shows the change in the absorption coefficient of brain tissue at a depth of 15 mm when measured with 690 nm light; Figure 6(d) shows the change in the absorption coefficient of brain tissue at a depth of 20 mm when measured with 690 nm light; Figure 6(e) shows the change in the absorption coefficient of brain tissue at a depth of 25 mm when measured with 690 nm light; and Figure 6(f) shows the change in the absorption coefficient of brain tissue at a depth of 30 mm when measured with 690 nm light; as well as three-dimensional imaging of the change in blood oxygen concentration (as shown in Figures 7 and 8, where Figure 7(a) shows the change in the absorption coefficient of brain tissue at a depth of 5 mm). Figure 7(b) shows the change in brain tissue oxygenated hemoglobin concentration ([ΔHbO2]) at a depth of 10 mm; Figure 7(c) shows the change in brain tissue oxygenated hemoglobin concentration ([ΔHbO2]) at a depth of 15 mm; Figure 7(d) shows the change in brain tissue oxygenated hemoglobin concentration ([ΔHbO2]) at a depth of 20 mm; Figure 7(e) shows the change in brain tissue oxygenated hemoglobin concentration ([ΔHbO2]) at a depth of 25 mm; and Figure 7(f) shows the change in brain tissue oxygenated hemoglobin concentration ([ΔHbO2]) at a depth of 30 mm.Figure 8(a) shows the change in deoxyhemoglobin concentration ([ΔHb]) of brain tissue at a depth of 5 mm; Figure 8(b) shows the change in deoxyhemoglobin concentration ([ΔHb]) of brain tissue at a depth of 10 mm; Figure 8(c) shows the change in deoxyhemoglobin concentration ([ΔHb]) of brain tissue at a depth of 15 mm; Figure 8(d) shows the change in deoxyhemoglobin concentration ([ΔHb]) of brain tissue at a depth of 20 mm; Figure 8(e) shows the change in deoxyhemoglobin concentration ([ΔHb]) of brain tissue at a depth of 25 mm; and Figure 8(f) shows the change in deoxyhemoglobin concentration ([ΔHb]) of brain tissue at a depth of 30 mm. Among them, the integers on the horizontal and vertical axes in the figure represent the serial numbers of the squares (unitless) (the horizontal and vertical coordinates can represent the serial numbers of pixels (dimensionless), for example, the range of the horizontal coordinate is 1 to 16, and the range of the vertical coordinate is 1 to 16, so this image has a total of 16*16=256 pixels).

[0086] The imaging method of this embodiment can be extended to a more general situation (i.e., collecting optical signals at multiple moments) according to actual needs, thereby obtaining continuous images of changes in brain tissue blood oxygen concentration.

[0087] Generally speaking, if Figure 9 As shown, this embodiment provides a method for imaging the change in blood oxygen concentration in brain tissue using diffuse light fused with photon weights, comprising the following steps: B1: Divide the tissue to be measured (or phantom) into n voxel units. B2: Arrange M*J SD combinations on the tissue surface and obtain the light intensity signals of all SD combinations at two different times. B3: Calculate the average change in tissue absorption coefficient of any SD combination. This step requires obtaining the average transmission path of the photons. Please refer to Figure 10 B4: Monte Carlo simulation of photons is used to calculate the average photon transmission path, and the change in tissue absorption coefficient for each voxel is calculated from the average change in tissue absorption coefficient across all SD combinations. B5: Two wavelengths of near-infrared light are used to illuminate the tissue under test, obtaining the respective changes in tissue absorption coefficient and further determining the changes in oxyhemoglobin and deoxyhemoglobin concentrations for all voxels. This embodiment can obtain cerebral blood oxygenation changes with depth information using photon information from a small number of SD combinations, providing enhanced anti-interference capabilities and more stable imaging results.

[0088] The method for imaging the change in blood oxygen concentration in brain tissue using diffuse light fused with photon weights described in this embodiment ("imaging" refers to the process of calculating the grayscale value of each two-dimensional pixel unit or three-dimensional voxel unit. These grayscale values ​​are projected on any display device (such as a computer or camera), resulting in a two-dimensional or three-dimensional image. That is, the change in blood oxygen concentration in each voxel unit is calculated and its value is represented by the grayscale of the image) has the following beneficial effects:

[0089] (1) Compared with the existing MBL method, the method described in this embodiment can reflect information at different tissue depths using the same SD combination and achieve three-dimensional imaging of changes in brain tissue blood oxygen concentration.

[0090] (2) The method described in this embodiment reflects the contribution weights of different photons to each tissue voxel unit (voxel element), and uses a linear iteration method to obtain an image of the change in blood oxygen concentration. Compared with the existing FEM method, a small amount of SD combined photon signals can be used to obtain a stable three-dimensional imaging of the change in blood oxygen concentration, which greatly reduces the equipment cost.

[0091] In an exemplary embodiment, a computer device is provided. The computer device may be a server or a terminal. The internal structure diagram thereof may be as follows: Figure 11 As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, abbreviated as I / O) and a communication interface. The processor, memory and input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a diffuse light imaging method of the change in brain tissue blood oxygen concentration that integrates photon weights is implemented.

[0092] Those skilled in the art will understand that Figure 11 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0093] In an exemplary embodiment, a computer device is further provided, including a memory and a processor. The memory stores a computer program, and the processor implements the steps in the above method embodiments when executing the computer program.

[0094] In an exemplary embodiment, a computer-readable storage medium is provided, storing a computer program. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments are implemented.

[0095] In an exemplary embodiment, a computer program product is provided, including a computer program. When the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0096] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0097] Those skilled in the art will understand that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, database or other media used in the embodiments provided in this application may include at least one of non-volatile and volatile memory. Non-volatile memory may include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory may include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM may be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0098] The databases involved in the various embodiments provided herein may include at least one of a relational database and a non-relational database. Non-relational databases may include, but are not limited to, distributed databases based on blockchains. The processors involved in the various embodiments provided herein may include, but are not limited to, general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic units, data processing logic units based on quantum computing, and the like.

[0099] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0100] This document uses specific examples to illustrate the principles and implementation methods of this application. The description of the above examples is only intended to help understand the method and core concept of this application. At the same time, for those skilled in the art, based on the concept of this application, there may be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting this application.

Claims

1. A method for imaging changes in brain tissue blood oxygen concentration using diffuse light fused with photon weights, characterized in that: include: Acquire experimental data obtained by irradiating the measured tissue with light sources of two wavelengths; the experimental data are all photon packets and corresponding photon packet information after Monte Carlo simulation of the measured tissue; the photon packet information includes the photon energy and transmission path of the photon packet; the photon packet is a combination of photons with the same path; the Monte Carlo simulation is performed using a plurality of optical probe combinations; each of the optical probe combinations can acquire the photon energy and transmission path of a plurality of photon packets; each of the optical probe combinations includes a light source and a plurality of detectors; the optical probe combination is arranged on the measured tissue; the measured tissue is evenly divided into a plurality of voxel units; The following calculations are performed for the experimental data corresponding to each wavelength of the light source: Using the formula Calculate the average photon transmission path acquired by the kth optical probe combination in the i-th voxel unit; where w (q,k) represents the total energy of the qth photon packet, s (i,q,k) is the transmission path of the qth photon packet in the i-th voxel unit, H k represents the total number of photon packets acquired by the k-th optical probe combination; Using the formula Calculate the photon weight acquired by the kth light probe combination in the i-th voxel unit; where ss (i,k) represents the average photon transmission path acquired by the k-th optical probe combination in the i-th voxel unit; Using the formula Calculate the change in tissue absorption coefficient of the i-th voxel unit; where M represents the total number of light sources, J represents the number of detectors in each light-detection combination, and ws (i,k) represents the photon weight acquired by the kth optical probe combination in the i-th voxel unit, Δμ a (k) represents the average change in tissue absorption coefficient of the area covered by the kth optical probe combination; The changes in the concentrations of oxyhemoglobin and deoxyhemoglobin in the i-th voxel unit are calculated using the first tissue absorption coefficient change and the second tissue absorption coefficient change; the first tissue absorption coefficient change is the change in the tissue absorption coefficient of the i-th voxel unit calculated using the experimental data corresponding to the light source of the first wavelength; the second tissue absorption coefficient change is the change in the tissue absorption coefficient of the i-th voxel unit calculated using the experimental data corresponding to the light source of the second wavelength.

2. The imaging method of brain tissue blood oxygen concentration variation by diffuse light fusion with photon weight according to claim 1, characterized in that: The calculation formula for calculating the changes in the concentrations of oxygenated hemoglobin and deoxygenated hemoglobin in the i-th voxel unit using the first tissue absorption coefficient change and the second tissue absorption coefficient change is: Among them, ε HbO2 (λ1) and ε Hb (λ1) are the extinction coefficients of oxygenated hemoglobin and deoxygenated hemoglobin at wavelength λ1; ε HbO2 (λ2) and ε Hb (λ2) are the extinction coefficients of oxyhemoglobin and deoxyhemoglobin at wavelength λ2; Δ[HbO2](i) is the change in the concentration of oxyhemoglobin in the i-th voxel; Δμ a (i,λ2) is the change in tissue absorption coefficient at wavelength λ2, i.e., the change in the second tissue absorption coefficient; Δμ a (i,λ1) is the change in tissue absorption coefficient at wavelength λ1, that is, the first tissue absorption coefficient change, and Δ[Hb](i) is the change in deoxyhemoglobin concentration in the i-th voxel unit.

3. The imaging method of brain tissue blood oxygen concentration variation by diffuse light fusion photon weight according to claim 1, characterized in that: The calculation method of the average change of the tissue absorption coefficient in the area covered by the kth optical probe combination includes: Using the transmission path of the qth photon packet in each voxel unit, calculate the total transmission path of the qth photon packet; Calculate the average photon transmission path of the k-th optical probe combination using the total transmission path and total energy of each photon packet acquired by the k-th optical probe combination; The change in photon density from time t0 to time t1 is calculated using the formula ΔOD(k) = ln(I(t0,k) / I(t1,k)). Here, I(t0,k) represents the light intensity captured by the k-th optical detector combination at time t0, and I(t1,k) represents the light intensity captured by the k-th optical detector combination at time t1. Using the formula Δμ a (k) = ΔOD(k) / MPL(k) calculates the average change in tissue absorption coefficient in the area covered by the k-th optical probe combination; where ΔOD(k) represents the change in photon density from time t0 to time t1, and MPL(k) represents the average photon transmission path of the k-th optical probe combination.

4. The imaging method of brain tissue blood oxygen concentration variation using diffuse light fused with photon weights according to claim 3, characterized in that: The formula for calculating the total transmission path of the qth photon packet using the transmission path of the qth photon packet in each voxel unit is: Where n represents the total number of voxel units.

5. The imaging method of brain tissue blood oxygen concentration variation by diffuse light fusion photon weight according to claim 3, characterized in that: The calculation formula for calculating the average photon transmission path of the kth optical probe combination using the total transmission path and total energy of each photon packet acquired by the kth optical probe combination is: Among them, L (q,k) represents the total transmission path of the qth photon packet.

6. The imaging method of brain tissue blood oxygen concentration variation by diffuse light fusion photon weight according to claim 1, characterized in that: The measured tissue is divided into 1536 voxel units; The Monte Carlo simulation is performed using 8 optical probe combinations; each optical probe combination includes 1 light source and 6 detectors.

7. The imaging method of brain tissue blood oxygen concentration variation by diffuse light fusion with photon weights according to claim 1, characterized in that: The tissue to be measured is the forehead of the subject.

8. A computer device comprising: 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 imaging method of the change in blood oxygen concentration of brain tissue using diffuse light fused with photon weights as described in any one of claims 1 to 7.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the imaging method of the change in blood oxygen concentration of brain tissue using diffuse light fused with photon weights according to any one of claims 1 to 7 is realized.

10. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the imaging method of the change in blood oxygen concentration of brain tissue using diffuse light fused with photon weights according to any one of claims 1 to 7 is realized.

Images