A method and device for determining material composition ratio

Abstract

The present disclosure relates to a method and device for determining a material component ratio, the method comprising: obtaining a photoacoustic spectrum at a position to be measured of a target object, the photoacoustic spectrum being obtained by measurement; determining a set of light flux spectra corresponding to the target object, the light flux spectra being a set pre-constructed to describe the distribution state of light flux spectra in the target object; determining each set of photoacoustic spectra under multiple assumed material component ratios based on the light flux spectra; determining the degree of matching between multiple sets of photoacoustic spectra and the photoacoustic spectrum; determining the material component ratio at the position to be measured based on the matching degree and the assumed material component ratio corresponding to each set of photoacoustic spectra. The disclosed embodiments can improve the accuracy of the detected material component ratio.

Description

Technical Field

[0001] The present disclosure relates to the field of detection technology, and in particular to a method and device for determining a material component ratio. Background Art

[0002] Photoacoustic imaging refers to the technology of imaging using the photoacoustic effect. Multispectral photoacoustic imaging uses the property that the photoacoustic signal generated by a substance is proportional to the light energy it absorbs. A multi-wavelength light source is used as the excitation source to stimulate the photoacoustic spectrum to obtain the absorption spectrum information of the substance, and then the absorption spectrum is used to unmix the proportion information of the substance components. For example, the relative proportion of oxygenated hemoglobin and deoxygenated hemoglobin in the blood can be unmixed to calculate the important physiological parameter of blood oxygen saturation.

[0003] In shallow media, the wavelength-dependent attenuation of light is weak, and the absorption spectrum can be approximately considered equal to the photoacoustic spectrum. The material composition ratio information can be obtained through traditional linear spectral unmixing. However, in deep scattering media, light has serious wavelength-dependent scattering and absorption, resulting in very complex flux spectra (flux spectrum: the value of the flux at a certain position at different wavelengths) at different positions in the imaging area. The photoacoustic spectrum is very different from the absorption spectrum. At this time, linear spectral unmixing will have a large error, resulting in the inability to accurately detect the material composition ratio. Summary of the invention

[0004] In view of this, the present disclosure proposes a technical solution for determining the ratio of material components.

[0005] According to one aspect of the present disclosure, a method for determining a material component ratio is provided, comprising:

[0006] Acquiring a photoacoustic spectrum at a position to be measured of the target object, wherein the photoacoustic spectrum is obtained by measurement;

[0007] Determine a luminous flux spectrum set corresponding to the target object, where the luminous flux spectrum set is a pre-constructed set for describing a distribution state of the luminous flux spectrum in the target object;

[0008] Based on the light flux spectrum set, determining each photoacoustic spectrum set under multiple assumed material component ratios;

[0009] determining a degree of matching between a plurality of the photoacoustic spectrum sets and the photoacoustic spectrum;

[0010] The material composition ratio at the position to be measured is determined according to the matching degree and the assumed material composition ratio corresponding to each set of photoacoustic spectra.

[0011] In a possible implementation, the light flux spectrum set is constructed in a manner including:

[0012] Using a simulated light source and a pre-built target object model, simulating the scattering and absorption of light by the target object to obtain a luminous flux spectrum in the target object model, wherein the target object model is pre-built according to optical parameters and physical shape of the target object;

[0013] The luminous flux spectrum set is constructed according to the luminous flux spectrum in the target object model.

[0014] In a possible implementation, the light flux spectrum set is characterized by a cone set, and the photoacoustic spectrum set is characterized by a cone set;

[0015] The determining of the light flux spectrum set corresponding to the target object includes:

[0016] Acquire a pre-constructed cone set for characterizing the light flux spectrum set;

[0017] The step of determining, based on the light flux spectrum set, each set of photoacoustic spectra under multiple assumed material component ratios comprises:

[0018] Based on the cone set characterizing the light flux spectrum set, constructing a cone set for characterizing each photoacoustic spectrum set under multiple assumed material component ratios;

[0019] The determining the matching degree between the plurality of photoacoustic spectrum sets and the photoacoustic spectrum comprises:

[0020] An angle between the photoacoustic spectrum and a set of cones characterizing each set of photoacoustic spectra is determined.

[0021] In a possible implementation, determining the material composition ratio at the position to be measured according to the matching degree and the assumed material composition ratio corresponding to each set of photoacoustic spectra includes:

[0022] The photoacoustic spectrum set with the smallest angle is taken as the target photoacoustic spectrum set matching the photoacoustic spectrum.

[0023] In a possible implementation, after determining the angle between the photoacoustic spectrum and the cone set characterizing each set of photoacoustic spectra, the method further includes:

[0024] According to the angle and a preset Gaussian white noise model, determining the posterior probability that the material composition ratio at the position to be measured is the material composition ratio of each hypothesis;

[0025] Based on the posterior probability, the material composition ratio at the position to be measured is determined.

[0026] In a possible implementation manner, determining the material composition ratio at the position to be measured based on the posterior probability includes:

[0027] Multiply the material composition ratio of each hypothesis by the corresponding posterior probability and sum them up;

[0028] Divide the sum result by the total number of groups of the assumed material component ratio to obtain the target ratio of the material component;

[0029] Based on the target ratio of the material components, the material component ratio at the position to be measured is determined.

[0030] In a possible implementation, determining the angle between the photoacoustic spectrum and a cone set characterizing each set of photoacoustic spectra includes:

[0031] For a single photoacoustic spectrum set, the minimum value of the angle between each element in the set and the photoacoustic spectrum is determined as the angle between the single photoacoustic spectrum set and the photoacoustic spectrum.

[0032] In a possible implementation, determining, based on the light flux spectrum set, each set of photoacoustic spectra under multiple assumed material component ratios includes:

[0033] Determining the absorption spectrum of each assumed material component ratio based on the absorption coefficient of light of each assumed material component ratio;

[0034] The photoacoustic spectrum and the light flux spectrum set are used to obtain photoacoustic spectrum sets of multiple assumed material component ratios.

[0035] According to another aspect of the present disclosure, there is provided a device for determining a material component ratio, comprising:

[0036] An acquisition module, used for acquiring a photoacoustic spectrum at a position to be measured of a target object, wherein the photoacoustic spectrum is obtained by measurement;

[0037] A first determination module, used to determine a luminous flux spectrum set corresponding to the target object, wherein the luminous flux spectrum set is a pre-constructed set used to describe a distribution state of the luminous flux spectrum in the target object;

[0038] A second determination module is used to determine, based on the light flux spectrum set, each set of photoacoustic spectra under multiple assumed material component ratios;

[0039] A third determination module is used to determine the matching degree between the plurality of photoacoustic spectrum sets and the photoacoustic spectrum;

[0040] The fourth determination module is used to determine the material composition ratio at the position to be measured according to the matching degree and the assumed material composition ratio corresponding to each set of photoacoustic spectra.

[0041] In a possible implementation, the light flux spectrum set is constructed in a manner including:

[0042] Using a simulated light source and a pre-built target object model, simulating the scattering and absorption of light by the target object to obtain a luminous flux spectrum in the target object model, wherein the target object model is pre-built according to optical parameters and physical shape of the target object;

[0043] The luminous flux spectrum set is constructed according to the luminous flux spectrum in the target object model.

[0044] In a possible implementation, the light flux spectrum set is characterized by a cone set, and the photoacoustic spectrum set is characterized by a cone set;

[0045] The first determination module is used to obtain a pre-built cone set for characterizing the light flux spectrum set;

[0046] The second determination module is used to construct a cone set for characterizing each photoacoustic spectrum set under multiple assumed material component ratios based on the cone set characterizing the light flux spectrum set;

[0047] The third determination module is used to determine the angle between the photoacoustic spectrum and the cone set characterizing each set of photoacoustic spectra.

[0048] In a possible implementation manner, the fourth determination module is configured to use a photoacoustic spectrum set with a smallest angle as a target photoacoustic spectrum set that matches the photoacoustic spectrum.

[0049] In a possible implementation, after determining the angle between the photoacoustic spectrum and the cone set characterizing each set of photoacoustic spectra, the device further includes:

[0050] The fifth determination module is used to determine the posterior probability that the material composition ratio at the position to be measured is each assumed material composition ratio according to the angle and a preset Gaussian white noise model; based on the posterior probability, determine the material composition ratio at the position to be measured.

[0051] In one possible implementation, the fifth determination module is used to multiply each hypothesized material composition ratio by the corresponding posterior probability and sum the results; divide the sum by the total number of groups of hypothesized material composition ratios to obtain a target ratio of the material composition; and determine the material composition ratio at the position to be measured based on the target ratio of the material composition.

[0052] In a possible implementation, the third determination module is used to determine, for a single photoacoustic spectrum set, a minimum value of angles between each element in the set and the photoacoustic spectrum as the angle between the single photoacoustic spectrum set and the photoacoustic spectrum.

[0053] In a possible implementation, the second determination module is used to determine the absorption spectrum of each assumed material component ratio based on the absorption coefficient of light of each assumed material component ratio; and to obtain each set of photoacoustic spectra of multiple assumed material component ratios by using the photoacoustic spectrum and the light flux spectrum set.

[0054] According to another aspect of the present disclosure, a device for determining a material component ratio is provided, comprising: a processor; and a memory for storing instructions executable by the processor; wherein the processor is configured to implement the above method when executing the instructions stored in the memory.

[0055] According to another aspect of the present disclosure, a non-volatile computer-readable storage medium is provided, on which computer program instructions are stored, wherein the computer program instructions implement the above method when executed by a processor.

[0056] According to another aspect of the present disclosure, a computer program product is provided, including a computer-readable code, or a non-volatile computer-readable storage medium carrying the computer-readable code. When the computer-readable code runs in a processor of an electronic device, the processor in the electronic device executes the above method.

[0057] In the embodiment of the present disclosure, after obtaining the measured photoacoustic spectrum at the position to be measured of the target object, a pre-constructed set of light flux spectrums for describing the distribution state of the light flux spectrum in the target object is determined, and based on the light flux spectrum set, each set of photoacoustic spectrums under multiple assumed material component ratios is determined; the degree of matching between multiple sets of photoacoustic spectrums and the photoacoustic spectrum is determined; and the material component ratio at the position to be measured is determined according to the matching degree and the assumed material component ratio corresponding to each set of photoacoustic spectrum. Thus, by pre-constructing a set of light flux spectrums for describing the light flux spectrum in the medium, and then assuming multiple material component ratios, a set of photoacoustic spectrums under multiple assumed material component ratios is determined based on the light flux spectrum set to characterize the photoacoustic spectra that may be generated by multiple assumed material component ratios, so that the degree of matching between multiple sets of photoacoustic spectrums and the measured photoacoustic spectrum can be determined; and the material component ratio at the position to be measured is determined according to the matching degree and the assumed material component ratio corresponding to each set of photoacoustic spectrum, thereby improving the accuracy of the detected material component ratio.

[0058] Further features and aspects of the present disclosure will become apparent from the following detailed description of exemplary embodiments with reference to the attached drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] The accompanying drawings, which are incorporated in and constitute a part of the specification, illustrate exemplary embodiments, features, and aspects of the disclosure and, together with the description, serve to explain the principles of the disclosure.

[0060] Figure 1 A flow chart showing a method for determining a material composition ratio according to an embodiment of the present disclosure.

[0061] Figure 2 A schematic diagram of an experimental result provided by an embodiment of the present disclosure is shown.

[0062] Figure 3 Another schematic diagram of experimental results provided by an embodiment of the present disclosure is shown.

[0063] Figure 4 A block diagram of a device for determining a material composition ratio according to an embodiment of the present disclosure is shown.

[0064] Figure 5 A block diagram of an electronic device according to an embodiment of the present disclosure is shown.

[0065] Figure 6 A block diagram of an electronic device according to an embodiment of the present disclosure is shown. DETAILED DESCRIPTION

[0066] Various exemplary embodiments, features and aspects of the present disclosure will be described in detail below with reference to the accompanying drawings. The same reference numerals in the accompanying drawings represent elements with the same or similar functions. Although various aspects of the embodiments are shown in the accompanying drawings, the drawings are not necessarily drawn to scale unless otherwise specified.

[0067] The word “exemplary” is used exclusively herein to mean “serving as an example, example, or illustration.” Any embodiment described herein as “exemplary” is not necessarily to be construed as preferred or advantageous over other embodiments.

[0068] In addition, in order to better illustrate the present disclosure, numerous specific details are given in the following specific embodiments. It should be understood by those skilled in the art that the present disclosure can also be implemented without certain specific details. In some examples, methods, means, components and circuits well known to those skilled in the art are not described in detail in order to highlight the subject matter of the present disclosure.

[0069] In deep scattering media, light is subjected to severe wavelength-dependent scattering and absorption, resulting in very complex luminous flux spectra (luminous flux spectrum: the value of the luminous flux at a certain position at different wavelengths) at different positions in the photoacoustic imaging area. The photoacoustic spectrum is very different from the absorption spectrum, and linear spectral unmixing will have large errors at this time.

[0070] For the photoacoustic imaging area position r, the simple mathematical expression of this problem is formula (1):

[0071]

[0072] in is the photoacoustic spectrum actually collected at this position, λ is the wavelength, The absorption spectrum that characterizes the material composition information a, is the light flux spectrum. If the absorption and scattering of biological tissues at different wavelengths do not vary with wavelength, is a constant, but in practice this is obviously impossible. It is closely related to the imaging point position, the global scattering absorption coefficient distribution of biological tissues, and the light source distribution, and is very complex. The existence of the flux spectrum causes a difference between the photoacoustic spectrum and the absorption spectrum, resulting in low accuracy of the linear spectrum unmixing result and inability to accurately detect the proportion of material components.

[0073] In addition, in the related art, when determining the proportion of material components, it is necessary to use the relative relationship between the photoacoustic spectra at different points in the photoacoustic image. Therefore, the requirements for the quality of photoacoustic image reconstruction are very high and the robustness is low.

[0074] In the embodiment of the present disclosure, after obtaining the measured photoacoustic spectrum at the position to be measured of the target object, a pre-constructed set of light flux spectrums for describing the distribution state of the light flux spectrum in the target object is determined, and based on the light flux spectrum set, each set of photoacoustic spectrums under multiple assumed material component ratios is determined; the degree of matching between multiple sets of photoacoustic spectrums and the photoacoustic spectrum is determined; and the material component ratio at the position to be measured is determined according to the matching degree and the assumed material component ratio corresponding to each set of photoacoustic spectrum. Thus, by pre-constructing a set of light flux spectrums for describing the light flux spectrum in the medium, and then assuming multiple material component ratios, a set of photoacoustic spectrums under multiple assumed material component ratios is determined based on the light flux spectrum set to characterize the photoacoustic spectra that may be generated by multiple assumed material component ratios, so that the degree of matching between multiple sets of photoacoustic spectrums and the measured photoacoustic spectrum can be determined; and the material component ratio at the position to be measured is determined according to the matching degree and the assumed material component ratio corresponding to each set of photoacoustic spectrum, thereby improving the accuracy of the detected material component ratio.

[0075] Figure 1 FIG. 1 is a flow chart showing a method for determining a material composition ratio according to an embodiment of the present disclosure. Figure 1 As shown, the method includes:

[0076] In step S11, a photoacoustic spectrum at a position to be measured of the target object is obtained.

[0077] The photoacoustic spectrum is measured by a photoacoustic imaging device. The photoacoustic spectrum can be a photoacoustic signal measured at different wavelengths. For example, photoacoustic signals at multiple wavelengths can be obtained by a photoacoustic imaging device. Specifically, the wavelength of a commonly used spectrum is 700nm-900nm. The photoacoustic signal can be measured once at an interval of 10nm to obtain a photoacoustic spectrum with a wavelength interval of 10nm.

[0078] In step S12, a luminous flux spectrum set corresponding to the target object is determined, where the luminous flux spectrum set is a pre-constructed set for describing a distribution state of the luminous flux spectrum in the target object;

[0079] An element in the luminous flux spectrum set is a luminous flux spectrum, which includes luminous flux values ​​at multiple wavelengths, and the luminous flux spectrum set contains multiple luminous flux spectra.

[0080] In the embodiment of the present disclosure, the luminous flux spectrum in the luminous flux spectrum set can be used to describe the distribution state of the luminous flux spectrum in the target object, and its specific theoretical basis is as follows:

[0081] In the Monte Carlo photon diffusion model, the light flux value at a certain position R is determined by the contribution of all photon paths passing through the position. According to this principle, when we use a multi-spectral light source to excite, the light flux spectrum φ(R,λ) at a certain position R in the material can be expressed by the spectrum P of each photon path. i (R,λ) is described by the weighted sum. That is, φ(R,λ)=∑ i W i ·P i (R,λ), where P i (R,λ) is determined by the scattering and absorption coefficients on the photon path i, W i is the weight value.

[0082] Then the possible luminous flux spectrum at any position in the material should be contained in the convex cone ({P i (R,λ)}), where convexcone(A)={∑ i ω i s i |s i ∈A,ω i >0},ω i is the weight value, A is the value containing P i The set of (R,λ), s i is an element in the set A.

[0083] We further discovered that we can use convexcone({P i (R,λ)}) RS (λ)} to replace {Pi (R,λ)}, where The basis vectors that will be used to form a convex cone are taken from the set of all possible photon path flux spectra {P i (R,λ)} is replaced by convexcone({P i The luminous flux spectrum set {F RS (λ)}.

[0084] Flux spectrum collection {F RS There are many ways to construct {F (λ)}. For example, the target object or a similar material with a composition close to the target object can be simulated to obtain the luminous flux spectrum distribution in the simulated target object, and then the luminous flux spectrum at different positions in the distribution can be randomly extracted to obtain {F RS (λ)}. At the same time, we found that we can directly use cone({F RS (λ)}) to describe the light flux in the tissue, where cone(A) = {ω i s i |s i ∈A,ω i >0}.

[0085] It should be noted that the luminous flux spectrum set may be pre-constructed, and in step S12, the constructed luminous flux spectrum set may be directly acquired.

[0086] In addition, since there may be many types of target objects, to construct a light flux spectrum set, it is necessary to know the absorbing substances in the target objects and their absorption and scattering properties. Therefore, multiple light flux spectrum sets can be pre-constructed according to the types of target objects. For example, light flux spectrum sets are constructed for agar, saline solution, blood, fat emulsion, etc., and then the corresponding light flux spectrum set is determined according to the type of target object in S11 to improve the accuracy of the detected material component ratio.

[0087] In step S13, based on the light flux spectrum set, photoacoustic spectrum sets under multiple assumed material component ratios are determined;

[0088] In the disclosed embodiment, multiple material component ratios can be pre-assumed. When the material component ratio is determined, the absorption spectrum of the material is determined. Then, based on the light flux spectrum set determined in step S12, a photoacoustic spectrum set under the assumed material component ratio can be determined. For each assumed material component ratio, a photoacoustic spectrum set can be obtained. The photoacoustic spectrum set is a set of photoacoustic spectra obtained by simulation calculation and used to represent the photoacoustic spectra stimulated by the assumed material component ratio.

[0089] The specific process of determining each set of photoacoustic spectra can be referred to the possible implementation methods provided in the present disclosure, which will not be described in detail here.

[0090] In step S14, determining the matching degree between the plurality of photoacoustic spectrum sets and the photoacoustic spectrum;

[0091] The matching degree between the photoacoustic spectrum set and the photoacoustic spectrum can be determined according to the angle between the photoacoustic spectrum set and the photoacoustic spectrum, and the smaller the angle, the higher the matching degree. Alternatively, it can be determined according to the distance between the photoacoustic spectrum and the photoacoustic spectrum set, and the smaller the distance, the higher the matching degree.

[0092] For details, please refer to the possible implementation methods provided in the present disclosure, which will not be described in detail here.

[0093] In step S15, the assumed material composition ratio corresponding to the target light flux spectrum is used as the material composition ratio at the position to be measured.

[0094] Since the light flux spectrum set is a pre-constructed set for describing the light flux spectrum distribution state in the target object, the photoacoustic spectrum set can be used to describe the photoacoustic spectrum generated by the hypothetical material component ratio. Then, the matching degree between the photoacoustic spectrum set determined in step S14 and the photoacoustic spectrum can be used to characterize the photoacoustic spectrum measured in step S11, which may be generated by the hypothetical material component ratio corresponding to the photoacoustic spectrum set with a high matching degree. Therefore, the material component ratio at the position to be measured can be determined according to the matching degree and the hypothetical material component ratio corresponding to each photoacoustic spectrum set.

[0095] There may be many specific implementations of step S15. In one example, the assumed material composition ratio corresponding to the photoacoustic spectrum set with the highest matching degree may be used as the material composition ratio at the position to be measured. In another example, when the matching degree is a probability, the material composition ratio at the position to be measured may be determined based on the probability. For details, please refer to the possible implementations provided in the present disclosure, which will not be elaborated here.

[0096] In the embodiment of the present disclosure, after obtaining the measured photoacoustic spectrum at the position to be measured of the target object, a pre-constructed set of light flux spectrums for describing the distribution state of the light flux spectrum in the target object is determined, and based on the light flux spectrum set, each set of photoacoustic spectrums under multiple assumed material component ratios is determined; the degree of matching between multiple sets of photoacoustic spectrums and the photoacoustic spectrum is determined; and the material component ratio at the position to be measured is determined according to the matching degree and the assumed material component ratio corresponding to each set of photoacoustic spectrum. Thus, by pre-constructing a set of light flux spectrums for describing the light flux spectrum in the medium, and then assuming multiple material component ratios, a set of photoacoustic spectrums under multiple assumed material component ratios is determined based on the light flux spectrum set to characterize the photoacoustic spectra that may be generated by multiple assumed material component ratios, so that the degree of matching between multiple sets of photoacoustic spectrums and the measured photoacoustic spectrum can be determined; and the material component ratio at the position to be measured is determined according to the matching degree and the assumed material component ratio corresponding to each set of photoacoustic spectrum, thereby improving the accuracy of the detected material component ratio.

[0097] When determining the proportion of material components at a certain position, the embodiment of the present disclosure can simply use the photoacoustic spectrum at that position without relying on the relative relationship between the photoacoustic spectra at different points in the photoacoustic image. Therefore, the requirements for the quality of photoacoustic image reconstruction are very low and the robustness is high.

[0098] There may be multiple ways to implement the material composition ratio determination method provided in the embodiments of the present disclosure. In one possible implementation, the method for constructing the luminous flux spectrum set includes: using a simulated light source and a pre-constructed target object model to simulate the scattering and absorption of light by the target object to obtain the luminous flux spectrum in the target object model, wherein the target object model is pre-constructed according to the optical parameters and physical shape of the target object; and constructing the luminous flux spectrum set according to the luminous flux spectrum in the target object model.

[0099] The target object model is used to simulate the scattering and absorption of light by the target object. It can be constructed by setting the shape, size and absorption scattering coefficient of the target object model. For example, when the target object is biological tissue, the components of common biological tissues with strong light absorption in the near-infrared band are similar, such as blood, fat, skin tissue, etc., and these material components have a certain content range, which limits the absorption scattering coefficient of the biological tissue to a certain range. Therefore, the absorption scattering coefficient can be set within this range, and the shape and size of the biological tissue model can be set to be consistent with or close to the shape and size of the actual target object to be measured, so as to construct the target object model.

[0100] By using a simulated light source to illuminate the target object model, the distribution of the luminous flux spectrum in the target object model can be obtained, and then the luminous flux spectrum obtained by simulation is extracted to construct a luminous flux spectrum set.

[0101] In the embodiment of the present disclosure, by using a simulated light source and a pre-built target object model, the scattering and absorption of light by the target object is simulated to obtain the luminous flux spectrum in the target object model; and according to the luminous flux spectrum in the target object model, the luminous flux spectrum set is constructed. Thus, the luminous flux spectrum set of the target object can be accurately obtained by simulation.

[0102] In a possible implementation, the light flux spectrum set is characterized by a convex set; determining the light flux spectrum set corresponding to the target object includes: obtaining a pre-constructed cone set for characterizing the light flux spectrum set; determining each photoacoustic spectrum set under multiple assumed material component ratios based on the light flux spectrum set includes: based on the cone set characterizing the light flux spectrum set, constructing a cone set for characterizing each photoacoustic spectrum set under multiple assumed material component ratios; determining the degree of matching between multiple photoacoustic spectrum sets and the photoacoustic spectrum includes: determining the angle between the photoacoustic spectrum and the cone set characterizing each photoacoustic spectrum set.

[0103] The cone set S is a set with this property: if an element s∈S, then for any positive number w, there is ws∈S. Then, the possible luminous flux spectrum at any position R in the material should be contained in the cone cone ({P i (R,λ)}), therefore, cone({F RS (λ)}) to describe the light flux in the tissue.

[0104] When the light flux spectrum set is characterized by a cone set, the cones representing the light flux in the tissue can be directly obtained ({F RS (λ)}).

[0105] After determining the cone characterizing the light flux in the tissue, a cone set for characterizing each set of photoacoustic spectra under multiple assumed material component ratios can be constructed based on the cone set characterizing the light flux spectrum set.

[0106] In a possible implementation, based on the light flux spectrum set, each set of photoacoustic spectra under multiple assumed material component ratios is determined, including: based on the absorption coefficient of each assumed material component ratio to light, determining the absorption spectrum of each assumed material component ratio; using the photoacoustic spectrum and the light flux spectrum set to obtain each set of photoacoustic spectra for multiple assumed material component ratios.

[0107] The assumed material composition ratio here has a certain composition, so the absorption coefficient of the material composition ratio is also certain. Based on the absorption coefficient, the absorption spectrum of the assumed material composition ratio can be determined, that is, the change of energy absorbed by the material with wavelength.

[0108] Assume that the relative proportion of the material components at a certain position in the biological tissue is [a1, a2...a n ] i , where n is the number of substances in a set of material components. For the measurement of blood oxygen saturation, n is 2, which are oxygenated hemoglobin and deoxygenated hemoglobin respectively; i is the number of groups obtained by traversing all possible proportions of material components. For example, for the strategy of blood oxygen saturation, the blood oxygen saturation (oxygenated hemoglobin) can be adjusted from 0% to 100% with an interval of 0.5%, and 201 groups of material components can be obtained. Then, the corresponding absorption spectrum at this position is [a1, a2...a n ] i ·[ε1(λ),ε1(λ)...ε n (λ)], where, [ε1(λ),ε2(λ)...ε n (λ)] is the absorption spectrum of different substances.

[0109] From the above, it can be easily concluded that the photoacoustic spectrum corresponding to a set of material components will also be located in a cone. i It can be represented by expression (2).

[0110] PAcone i =cone(([a1,a2…a n ] i ·[ε1(λ),ε1(λ),…ε n (λ)])⊙{F RS (λ)}) (2)

[0111] Here, a⊙B is defined as the product of element a and every element in set B.

[0112] Obtained PAcone i That is, it is the photoacoustic spectrum set of the i-th group of assumed material component ratios. Since multiple groups of material component ratios can be assumed in advance, the photoacoustic spectrum sets of the multiple groups of assumed material component ratios can be obtained.

[0113] In the disclosed embodiment, the absorption spectrum of each assumed material component ratio is determined based on the absorption coefficient of light of each assumed material component ratio; and the photoacoustic spectrum and the light flux spectrum set are used to obtain the photoacoustic spectrum sets of multiple assumed material component ratios. Thus, the photoacoustic spectrum sets of the assumed material component ratio can be accurately determined, thereby improving the accuracy of the detected material component ratio.

[0114] After the photoacoustic spectrum sets are determined, the angle between the photoacoustic spectrum measured in step S11 and the cone set characterizing each photoacoustic spectrum set may be determined.

[0115] The recording form of the luminous flux spectrum in the computer can be vector form, and the recording form of the photoacoustic spectrum set in the computer can also be vector form. Therefore, the cone set used to characterize each photoacoustic spectrum set under a variety of assumed material component ratios is composed of vector elements. Then, when determining the angle between the measured photoacoustic spectrum and the cone set characterizing each photoacoustic spectrum set, the angle between the vector and the vector can be calculated to obtain the angle between the measured photoacoustic spectrum and the cone set.

[0116] In addition, the distance between a point and a convex cone can be determined by a modified collision detection algorithm (GJK), and the angle between the photoacoustic spectrum (vector) and the cone set can be determined by a certain coordinate transformation.

[0117] In the embodiment of the present disclosure, the light flux spectrum set is characterized by a cone set, so a pre-constructed cone set for characterizing the light flux spectrum set can be obtained, and then based on the cone set characterizing the light flux spectrum set, a cone set for characterizing each photoacoustic spectrum set under multiple assumed material component ratios is constructed to determine the angle between the photoacoustic spectrum and the cone set characterizing each photoacoustic spectrum set. Thus, the conceptual model of a convex cone is innovatively used to describe the light flux spectrum set and the photoacoustic spectrum set of light at a certain position in a turbid medium (biological tissue is a typical turbid medium), and the angle between the photoacoustic spectrum and the cone set characterizing each photoacoustic spectrum set is used to determine the degree of matching between multiple photoacoustic spectrum sets and the photoacoustic spectrum, which can improve the accuracy of the determined matching degree, and then can significantly improve the efficiency and accuracy of detecting the material component ratio, and has high robustness to noise.

[0118] In a possible implementation, determining the material composition ratio at the position to be measured based on the matching degree and the assumed material composition ratio corresponding to each photoacoustic spectrum set includes: taking the photoacoustic spectrum set with the smallest angle as the target photoacoustic spectrum set that matches the photoacoustic spectrum.

[0119] The photoacoustic spectrum set with the smallest angle can be regarded as the photoacoustic spectrum set that best matches the measured photoacoustic spectrum. Thus, the target photoacoustic spectrum set that matches the photoacoustic spectrum can be accurately determined, thereby improving the accuracy of the detected material component ratio.

[0120] In a possible implementation, determining the angle between the photoacoustic spectrum and a cone set characterizing each set of photoacoustic spectra includes: for a single set of photoacoustic spectra, determining a minimum value of the angles between each element in the set and the photoacoustic spectrum as the angle between the single set of photoacoustic spectra and the photoacoustic spectrum.

[0121] In this implementation, for the angle between the photoacoustic spectrum and a single cone set characterizing each set of photoacoustic spectra, the minimum angle between the photoacoustic spectrum and all elements in the single cone set can be measured. Then, for the measured photoacoustic spectrum, the minimum angle between the photoacoustic spectrum (in vector form) and each vector in the cone set of the single set of photoacoustic spectra can be determined as the angle between the photoacoustic spectrum and the cone set.

[0122] For a photoacoustic spectrum PA(λ) measured in tissue (in practical applications, the wavelength can only be discretely taken at finite points, in this case, we use the vector The measured photoacoustic spectrum is represented by (3). PAcone with different photoacoustic spectra i The angle θ between i .

[0123]

[0124] The method for calculating this angle is still the previous modified GJK method.

[0125] For PAcone i The closest one in the set The element (with the smallest angle) can be expressed by expression (4).

[0126]

[0127] In the embodiment of the present disclosure, for a single photoacoustic spectrum set, the minimum value of the angle between each element in the set and the photoacoustic spectrum is determined as the angle between the single photoacoustic spectrum set and the photoacoustic spectrum. Thus, for the angle between the single photoacoustic spectrum set and the measured photoacoustic spectrum, the minimum angle between all elements of the single photoacoustic spectrum set and the measured photoacoustic spectrum can be determined as the angle between the single photoacoustic spectrum set and the photoacoustic spectrum, so as to accurately describe the angle between the measured photoacoustic spectrum and the single photoacoustic spectrum set.

[0128] In a possible implementation, after determining the angle between the photoacoustic spectrum and the cone set characterizing each set of photoacoustic spectra, the method further includes: determining, based on the angle and a preset Gaussian white noise model, the posterior probability that the material composition ratio at the position to be measured is each assumed material composition ratio; and determining the material composition ratio at the position to be measured based on the posterior probability.

[0129] The angle here is proportional to the posterior probability.

[0130] In actual measurement, noise is inevitable. Assuming that the noise introduced in the actual measurement is Gaussian white noise with a mean of 0, the standard deviation of the noise at different wavelengths is calculated through multiple measurements. and each photoacoustic spectrum collection PAcone i The elements corresponding to different wavelengths are divided by the corresponding standard deviations, thus simplifying the noise to Gaussian white noise with a mean of 0 and a standard deviation of 1. After this operation, we can obtain the posterior probability of the proportion of material components in different groups based on the above angle and the standard Gaussian white noise model, and then determine the estimated value of the material composition ratio.

[0131] The posterior probability that the material composition ratio at the position to be measured is the i-th group of material composition ratios of each hypothesis can be expressed by formula (5).

[0132]

[0133] After determining the posterior probability, the material composition ratio at the position to be measured can be determined based on the posterior probability. In one example, a group of material composition ratios with the highest posterior probability can be directly used as the material composition ratio at the position to be measured, or the posterior probabilities can be averaged. For details, please refer to the possible implementation methods provided in the present disclosure, which will not be elaborated here.

[0134] In the disclosed embodiment, the material composition ratio at the position to be measured is determined to be the posterior probability of each assumed material composition ratio according to the angle and the preset Gaussian white noise model; based on the posterior probability, the material composition ratio at the position to be measured is determined. Thus, by considering the posterior probability of noise to determine the material composition ratio at the position to be measured, it is more consistent with the actual situation and can improve the accuracy of the measured material composition ratio.

[0135] In one possible implementation, determining the material composition ratio at the position to be measured based on the posterior probability includes: multiplying each assumed material composition ratio by the corresponding posterior probability and summing the results; dividing the sum by the total number of groups of assumed material composition ratios to obtain a target ratio of material composition; and determining the material composition ratio at the position to be measured based on the target ratio of material composition.

[0136] For example, assuming that the blood oxygen saturation (oxygenated hemoglobin) ranges from 0% to 100% with an interval of 0.5%, 201 groups of hypothetical material components are obtained. Through the method provided by the present disclosure, it is possible to determine the posterior probability that the material component ratio at the position to be measured is the material component ratio of each hypothesis. The posterior probability is also 201, and each group of hypothetical material components corresponds to a posterior probability. Multiply each group of blood oxygen saturation by the corresponding posterior probability and sum them, and divide the sum by 201 (the total number of groups) to get a percentage, which can be directly used as the blood oxygen saturation at the position to be measured.

[0137] In the disclosed embodiment, the target ratio of material components is obtained by multiplying each assumed material component ratio by the corresponding posterior probability and summing the results, and then dividing the sum by the total number of groups of assumed material component ratios; based on the target ratio of material components, the material component ratio at the position to be measured is determined, thereby improving the accuracy of the determined material component ratio at the position to be detected.

[0138] The material component ratio determination method provided in the embodiment of the present disclosure can be applied to determine the material component ratio of a turbid medium. Since light in a deep turbid medium has serious wavelength-related scattering and absorption, the luminous flux spectrum (luminous flux spectrum: the value of the luminous flux at a certain position at different wavelengths) at different positions in the imaging area is very complex, and the photoacoustic spectrum and the absorption spectrum are very different. At this time, there will be a large error in linear spectrum unmixing, resulting in a low accuracy of the obtained material component ratio. The material component ratio determination method provided in the present disclosure can obtain the luminous flux spectrum in the turbid medium, and then obtain the material component ratio at the position to be measured, which can improve the accuracy of the obtained material component ratio.

[0139] Exemplarily, the turbid medium here may be, for example, agar, saline solution, blood, fat emulsion, etc. The embodiments of the present disclosure may be used to measure the content of components such as hemoglobin, melanin, collagen, and fat at a certain location of the human body.

[0140] An application scenario of an embodiment of the present disclosure is described below. In this application scenario, the application scenario is to measure blood oxygen saturation, the target object is blood, and the process of determining the material component ratio in this application scenario is as follows.

[0141] In step S21 , a multispectral photoacoustic image measured by a photoacoustic imaging device is acquired.

[0142] In step S22, the photoacoustic spectrum of the target position in the multispectral photoacoustic image is obtained.

[0143] In step S23, a pre-constructed convex cone ({F RS(λ)}).

[0144] In step S24, different blood oxygen saturations are assumed from 0% to 100% (according to a gradient of 0.5%) to obtain absorption spectra of oxygenated blood and deoxygenated blood at different blood oxygen saturations. The 201 sets of absorption spectra are multiplied by the convex cone cone ({F RS (λ)}), and obtain the photoacoustic spectral cone PCone under 201 sets of assumed blood oxygen saturation.

[0145] In step S25, the collision detection algorithm GJK is used to obtain 201 sets of luminous flux spectra, photoacoustic spectra cones PAcone and photoacoustic spectra under assumed blood oxygen saturation. angle.

[0146] In step S26, based on the angle and the Gaussian white noise model, 201 groups of posterior probabilities corresponding to the hypothesized blood oxygen saturation are obtained.

[0147] In step S27, the 201 groups of assumed blood oxygen saturation values ​​are multiplied by their respective posterior probabilities and summed, and then divided by 201 to obtain a percentage as the estimated blood oxygen saturation value.

[0148] Compared with the linear unmixing method, the error of the estimated blood oxygen saturation by the material component ratio determination method provided by the present disclosure is greatly reduced, and it has a relatively strong ability to resist noise. Figure 2 A schematic diagram of experimental results provided for an embodiment of the present disclosure, specifically the solution errors of the method of the embodiment of the present disclosure and the linear unmixing method under different signal-to-noise ratios, wherein 27dB is the case where the system signal-to-noise ratio is low, demonstrating the robustness of the method of the embodiment of the present disclosure to noise.

[0149] In addition, we used substances such as agar, saline solution, blood, and fat emulsion to simulate biological tissues and estimate the blood oxygen saturation in the phantom. Figure 3 Another schematic diagram of experimental results provided by the embodiment of the present disclosure, the solid points are the estimated results of linear unmixing, the solid triangles are the estimated results of the embodiment of the present disclosure, and the hollow triangles are the true values. Figure 3 It can be seen that the estimation result of the method in the embodiment of the present disclosure is very close to the true value.

[0150] It should be noted that although the above method for determining the material component ratio is introduced by taking blood oxygen saturation measurement as an example, those skilled in the art will appreciate that the present disclosure should not be limited thereto. In fact, the user can flexibly set the specific measurement target object according to personal preferences and / or actual application scenarios.

[0151] In addition, the present disclosure also provides an image processing device, an electronic device, a computer-readable storage medium, and a program, all of which can be used to implement any method for determining the material component ratio provided by the present disclosure. The corresponding technical solutions and descriptions can be found in the corresponding records in the method section and will not be repeated here.

[0152] Figure 4 A block diagram of a device for determining a material composition ratio according to an embodiment of the present disclosure is shown. Figure 4 As shown, the material composition ratio determining device 40 includes:

[0153] An acquisition module 401 is used to acquire a photoacoustic spectrum at a position to be measured of a target object, wherein the photoacoustic spectrum is obtained by measurement;

[0154] A first determining module 402 is used to determine a luminous flux spectrum set corresponding to the target object, where the luminous flux spectrum set is a pre-constructed set used to describe the distribution state of the luminous flux spectrum in the target object;

[0155] A second determination module 403 is used to determine, based on the light flux spectrum set, each set of photoacoustic spectra under multiple assumed material component ratios;

[0156] A third determination module 404 is used to determine the matching degree between the plurality of photoacoustic spectrum sets and the photoacoustic spectrum;

[0157] The fourth determination module 405 is used to determine the material composition ratio at the position to be measured according to the matching degree and the assumed material composition ratio corresponding to each set of photoacoustic spectra.

[0158] In a possible implementation, the light flux spectrum set is constructed in a manner including:

[0159] Using a simulated light source and a pre-built target object model, simulating the scattering and absorption of light by the target object to obtain a luminous flux spectrum in the target object model, wherein the target object model is pre-built according to optical parameters and physical shape of the target object;

[0160] The luminous flux spectrum set is constructed according to the luminous flux spectrum in the target object model.

[0161] In a possible implementation, the light flux spectrum set is characterized by a cone set, and the photoacoustic spectrum set is characterized by a cone set;

[0162] The first determination module is used to obtain a pre-built cone set for characterizing the light flux spectrum set;

[0163] The second determination module is used to construct a cone set for characterizing each photoacoustic spectrum set under multiple assumed material component ratios based on the cone set characterizing the light flux spectrum set;

[0164] The third determination module is used to determine the angle between the photoacoustic spectrum and the cone set characterizing each set of photoacoustic spectra.

[0165] In a possible implementation manner, the fourth determination module is configured to use a photoacoustic spectrum set with a smallest angle as a target photoacoustic spectrum set that matches the photoacoustic spectrum.

[0166] In a possible implementation, after determining the angle between the photoacoustic spectrum and the cone set characterizing each set of photoacoustic spectra, the device further includes:

[0167] The fifth determination module is used to determine the posterior probability that the material composition ratio at the position to be measured is each assumed material composition ratio according to the angle and a preset Gaussian white noise model; based on the posterior probability, determine the material composition ratio at the position to be measured.

[0168] In one possible implementation, the fifth determination module is used to multiply each hypothesized material composition ratio by the corresponding posterior probability and sum the results; divide the sum by the total number of groups of hypothesized material composition ratios to obtain a target ratio of the material composition; and determine the material composition ratio at the position to be measured based on the target ratio of the material composition.

[0169] In a possible implementation, the third determination module is used to determine, for a single photoacoustic spectrum set, a minimum value of angles between each element in the set and the photoacoustic spectrum as the angle between the single photoacoustic spectrum set and the photoacoustic spectrum.

[0170] In a possible implementation, the second determination module is used to determine the absorption spectrum of each assumed material component ratio based on the absorption coefficient of light of each assumed material component ratio; and to obtain each set of photoacoustic spectra of multiple assumed material component ratios by using the photoacoustic spectrum and the light flux spectrum set.

[0171] In some embodiments, the functions or modules included in the device provided by the embodiments of the present disclosure can be used to execute the method described in the above method embodiments. The specific implementation can refer to the description of the above method embodiments, and for the sake of brevity, it will not be repeated here.

[0172] The embodiment of the present disclosure also provides a computer-readable storage medium on which computer program instructions are stored, and the computer program instructions implement the above method when executed by a processor. The computer-readable storage medium can be a volatile or non-volatile computer-readable storage medium.

[0173] An embodiment of the present disclosure further proposes an electronic device, comprising: a processor; and a memory for storing instructions executable by the processor; wherein the processor is configured to implement the above method when executing the instructions stored in the memory.

[0174] The embodiments of the present disclosure also provide a computer program product, including a computer-readable code, or a non-volatile computer-readable storage medium carrying the computer-readable code. When the computer-readable code runs in a processor of an electronic device, the processor in the electronic device executes the above method.

[0175] Figure 5 8 is a block diagram of an apparatus 800 for determining a material component ratio according to an exemplary embodiment. For example, the apparatus 800 may be a mobile phone, a computer, a digital broadcast terminal, a messaging device, a game console, a tablet device, a medical device, a fitness device, a personal digital assistant, etc.

[0176] Reference Figure 5 , the device 800 may include one or more of the following components: a processing component 802 , a memory 804 , a power component 806 , a multimedia component 808 , an audio component 810 , an input / output (I / O) interface 812 , a sensor component 814 , and a communication component 816 .

[0177] The processing component 802 generally controls the overall operation of the device 800, such as operations associated with display, phone calls, data communications, camera operations, and recording operations. The processing component 802 may include one or more processors 820 to execute instructions to complete all or part of the steps of the above-mentioned method. In addition, the processing component 802 may include one or more modules to facilitate the interaction between the processing component 802 and other components. For example, the processing component 802 may include a multimedia module to facilitate the interaction between the multimedia component 808 and the processing component 802.

[0178] The memory 804 is configured to store various types of data to support operations on the device 800. Examples of such data include instructions for any application or method operating on the device 800, contact data, phone book data, messages, pictures, videos, etc. The memory 804 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk.

[0179] The power supply component 806 provides power to the various components of the device 800. The power supply component 806 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power for the device 800.

[0180] The multimedia component 808 includes a screen that provides an output interface between the device 800 and the user. In some embodiments, the screen may include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes a touch panel, the screen may be implemented as a touch screen to receive input signals from the user. The touch panel includes one or more touch sensors to sense touch, slide, and gestures on the touch panel. The touch sensor may not only sense the boundaries of the touch or slide action, but also detect the duration and pressure associated with the touch or slide operation. In some embodiments, the multimedia component 808 includes a front camera and / or a rear camera. When the device 800 is in an operating mode, such as a shooting mode or a video mode, the front camera and / or the rear camera may receive external multimedia data. Each front camera and rear camera may be a fixed optical lens system or have a focal length and optical zoom capability.

[0181] The audio component 810 is configured to output and / or input audio signals. For example, the audio component 810 includes a microphone (MIC), and when the device 800 is in an operating mode, such as a call mode, a recording mode, and a speech recognition mode, the microphone is configured to receive an external audio signal. The received audio signal can be further stored in the memory 804 or sent via the communication component 816. In some embodiments, the audio component 810 also includes a speaker for outputting audio signals.

[0182] I / O interface 812 provides an interface between processing component 802 and peripheral interface modules, such as keyboards, click wheels, buttons, etc. These buttons may include but are not limited to: home button, volume button, start button, and lock button.

[0183] The sensor assembly 814 includes one or more sensors for providing various aspects of the status assessment of the device 800. For example, the sensor assembly 814 can detect the open / closed state of the device 800, the relative positioning of components, such as the display and keypad of the device 800, and the sensor assembly 814 can also detect the position change of the device 800 or a component of the device 800, the presence or absence of user contact with the device 800, the orientation or acceleration / deceleration of the device 800, and the temperature change of the device 800. The sensor assembly 814 may include a proximity sensor configured to detect the presence of a nearby object without any physical contact. The sensor assembly 814 may also include an optical sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, the sensor assembly 814 may also include an accelerometer, a gyroscope sensor, a magnetic sensor, a pressure sensor, or a temperature sensor.

[0184] The communication component 816 is configured to facilitate wired or wireless communication between the device 800 and other devices. The device 800 can access a wireless network based on a communication standard, such as WiFi, 2G or 3G, or a combination thereof. In an exemplary embodiment, the communication component 816 receives a broadcast signal or broadcast-related information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communication component 816 also includes a near field communication (NFC) module to facilitate short-range communication. For example, the NFC module can be implemented based on radio frequency identification (RFID) technology, infrared data association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology and other technologies.

[0185] In an exemplary embodiment, the apparatus 800 may be implemented by one or more application specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors or other electronic components to perform the above method.

[0186] In an exemplary embodiment, a non-volatile computer-readable storage medium is also provided, such as a memory 804 including computer program instructions, which can be executed by the processor 820 of the device 800 to perform the above method.

[0187] Figure 6 1 is a block diagram of an apparatus 1900 for determining a material component ratio according to an exemplary embodiment. For example, the apparatus 1900 may be provided as a server or a terminal device. Figure 6, the apparatus 1900 includes a processing component 1922, which further includes one or more processors, and a memory resource represented by a memory 1932 for storing instructions, such as an application, that can be executed by the processing component 1922. The application stored in the memory 1932 may include one or more modules, each corresponding to a set of instructions. In addition, the processing component 1922 is configured to execute instructions to perform the above method.

[0188] The device 1900 may also include a power supply component 1926 configured to perform power management of the device 1900, a wired or wireless network interface 1950 configured to connect the device 1900 to a network, and an input / output (I / O) interface 1958. The device 1900 may operate based on an operating system stored in the memory 1932, such as Windows Server™, MacOS X™, Unix™, Linux™, FreeBSD™, or the like.

[0189] In an exemplary embodiment, a non-volatile computer-readable storage medium is also provided, such as a memory 1932 including computer program instructions, which can be executed by the processing component 1922 of the device 1900 to perform the above method.

[0190] The present disclosure may be a system, a method and / or a computer program product. The computer program product may include a computer-readable storage medium carrying computer-readable program instructions for causing a processor to implement various aspects of the present disclosure.

[0191] A computer-readable storage medium may be a tangible device that can hold and store instructions used by an instruction execution device. A computer-readable storage medium may be, for example, but not limited to, an electrical storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing. More specific examples of computer-readable storage media (a non-exhaustive list) include: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a static random access memory (SRAM), a portable compact disk read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a mechanical encoding device, such as a punch card or a raised structure in a groove on which instructions are stored, and any suitable combination of the foregoing. As used herein, a computer-readable storage medium is not to be interpreted as a transient signal per se, such as a radio wave or other freely propagating electromagnetic wave, an electromagnetic wave propagating through a waveguide or other transmission medium (e.g., a light pulse through a fiber optic cable), or an electrical signal transmitted through a wire.

[0192] The computer-readable program instructions described herein can be downloaded from a computer-readable storage medium to each computing / processing device, or downloaded to an external computer or external storage device via a network, such as the Internet, a local area network, a wide area network, and / or a wireless network. The network can include copper transmission cables, optical fiber transmissions, wireless transmissions, routers, firewalls, switches, gateway computers, and / or edge servers. The network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in the computer-readable storage medium in each computing / processing device.

[0193] The computer program instructions for performing the operation of the present disclosure may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-related instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages, such as Smalltalk, C++, etc., and conventional procedural programming languages, such as "C" language or similar programming languages. Computer-readable program instructions may be executed completely on a user's computer, partially on a user's computer, as an independent software package, partially on a user's computer, partially on a remote computer, or completely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., using an Internet service provider to connect via the Internet). In some embodiments, an electronic circuit, such as a programmable logic circuit, a field programmable gate array (FPGA), or a programmable logic array (PLA), may be customized by utilizing the state information of the computer-readable program instructions, and the electronic circuit may execute the computer-readable program instructions, thereby realizing various aspects of the present disclosure.

[0194] Various aspects of the present disclosure are described herein with reference to the flowcharts and / or block diagrams of the methods, devices (systems) and computer program products according to the embodiments of the present disclosure. It should be understood that each box in the flowchart and / or block diagram and the combination of each box in the flowchart and / or block diagram can be implemented by computer-readable program instructions.

[0195] These computer-readable program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, thereby producing a machine, so that when these instructions are executed by the processor of the computer or other programmable data processing device, a device that implements the functions / actions specified in one or more boxes in the flowchart and / or block diagram is generated. These computer-readable program instructions can also be stored in a computer-readable storage medium, and these instructions cause the computer, programmable data processing device, and / or other equipment to work in a specific manner, so that the computer-readable medium storing the instructions includes a manufactured product, which includes instructions for implementing various aspects of the functions / actions specified in one or more boxes in the flowchart and / or block diagram.

[0196] Computer-readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device so that a series of operating steps are performed on the computer, other programmable data processing apparatus, or other device to produce a computer-implemented process, thereby causing the instructions executed on the computer, other programmable data processing apparatus, or other device to implement the functions / actions specified in one or more boxes in the flowchart and / or block diagram.

[0197] The flow chart and block diagram in the accompanying drawings show the possible architecture, function and operation of the system, method and computer program product according to multiple embodiments of the present disclosure. In this regard, each square box in the flow chart or block diagram can represent a part of a module, program segment or instruction, and a part of the module, program segment or instruction includes one or more executable instructions for realizing the specified logical function. In some alternative implementations, the function marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two continuous square boxes can actually be executed substantially in parallel, and they can sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs the specified function or action, or can be implemented with a combination of special hardware and computer instructions.

[0198] The embodiments of the present disclosure have been described above, and the above description is exemplary, not exhaustive, and is not limited to the disclosed embodiments. Many modifications and changes will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The selection of terms used herein is intended to best explain the principles of the embodiments, practical applications, or technical improvements in the market, or to enable other persons of ordinary skill in the art to understand the embodiments disclosed herein.

Claims

1. A method for determining a material composition ratio, characterized in that: include: Acquiring a photoacoustic spectrum at a position to be measured of the target object, wherein the photoacoustic spectrum is obtained by measurement; Determine a luminous flux spectrum set corresponding to the target object, wherein the luminous flux spectrum set is a pre-constructed set for describing the distribution state of the luminous flux spectrum in the target object, and the luminous flux spectrum is the value of the luminous flux at a certain position under different wavelengths; Based on the light flux spectrum set, determining each photoacoustic spectrum set under multiple assumed material component ratios; determining a degree of matching between a plurality of the photoacoustic spectrum sets and the photoacoustic spectrum; Determining the material composition ratio at the position to be measured according to the matching degree and the assumed material composition ratio corresponding to each set of photoacoustic spectra; The method of constructing the light flux spectrum set includes: Using a simulated light source and a pre-built target object model, simulating the scattering and absorption of light by the target object to obtain a luminous flux spectrum in the target object model, wherein the target object model is pre-built according to optical parameters and physical shape of the target object; Constructing the luminous flux spectrum set according to the luminous flux spectrum in the target object model; The light flux spectrum set is characterized by a cone set, and the photoacoustic spectrum set is characterized by a cone set; The determining of the light flux spectrum set corresponding to the target object includes: Acquire a pre-constructed cone set for characterizing the light flux spectrum set; The step of determining, based on the light flux spectrum set, each set of photoacoustic spectra under multiple assumed material component ratios comprises: Based on the cone set characterizing the light flux spectrum set, a cone set for characterizing each photoacoustic spectrum set under multiple assumed material component ratios is constructed.

2. The method according to claim 1, characterized in that: The determining the matching degree between the plurality of photoacoustic spectrum sets and the photoacoustic spectrum comprises: An angle between the photoacoustic spectrum and a set of cones characterizing each set of photoacoustic spectra is determined.

3. The method according to claim 2, characterized in that: Determining the material composition ratio at the position to be measured according to the matching degree and the assumed material composition ratio corresponding to each set of photoacoustic spectra includes: The photoacoustic spectrum set with the smallest angle is taken as the target photoacoustic spectrum set matching the photoacoustic spectrum.

4. The method according to claim 2, characterized in that: After determining the angle between the photoacoustic spectrum and the cone set characterizing each set of photoacoustic spectra, the method further comprises: According to the angle and a preset Gaussian white noise model, determining the posterior probability that the material composition ratio at the position to be measured is the material composition ratio of each hypothesis; Based on the posterior probability, the material composition ratio at the position to be measured is determined.

5. The method according to claim 4, characterized in that: The determining, based on the posterior probability, the material composition ratio at the position to be measured includes: Multiply the material composition ratio of each hypothesis by the corresponding posterior probability and sum them up; Divide the sum result by the total number of groups of the assumed material component ratio to obtain the target ratio of the material component; Based on the target ratio of the material components, the material component ratio at the position to be measured is determined.

6. The method according to claim 2, characterized in that: Determining the angle between the photoacoustic spectrum and a cone set characterizing each set of photoacoustic spectra includes: For a single photoacoustic spectrum set, the minimum value of the angle between each element in the set and the photoacoustic spectrum is determined as the angle between the single photoacoustic spectrum set and the photoacoustic spectrum.

7. The method according to claim 1, characterized in that: The step of determining, based on the light flux spectrum set, each set of photoacoustic spectra under multiple assumed material component ratios comprises: Determining the absorption spectrum of each assumed material component ratio based on the absorption coefficient of light of each assumed material component ratio; The photoacoustic spectrum and the light flux spectrum set are used to obtain photoacoustic spectrum sets of multiple assumed material component ratios.

8. A device for determining a material composition ratio, characterized in that: include: An acquisition module, used to acquire a photoacoustic spectrum at a position to be measured of a target object, wherein the photoacoustic spectrum is obtained by measurement; A first determination module is used to determine a luminous flux spectrum set corresponding to the target object, wherein the luminous flux spectrum set is a pre-constructed set for describing the distribution state of the luminous flux spectrum in the target object, and the luminous flux spectrum is the value of the luminous flux at a certain position under different wavelengths; A second determination module is used to determine, based on the light flux spectrum set, each set of photoacoustic spectra under multiple assumed material component ratios; A third determination module is used to determine the matching degree between the plurality of photoacoustic spectrum sets and the photoacoustic spectrum; A fourth determination module, configured to determine the material composition ratio at the position to be measured according to the matching degree and the assumed material composition ratio corresponding to each set of photoacoustic spectra; The method of constructing the light flux spectrum set includes: Using a simulated light source and a pre-built target object model, simulating the scattering and absorption of light by the target object to obtain a luminous flux spectrum in the target object model, wherein the target object model is pre-built according to optical parameters and physical shape of the target object; Constructing the luminous flux spectrum set according to the luminous flux spectrum in the target object model; The light flux spectrum set is characterized by a cone set, and the photoacoustic spectrum set is characterized by a cone set; The first determination module is used to obtain a pre-built cone set for characterizing the light flux spectrum set; The second determination module is used to construct a cone set for characterizing each photoacoustic spectrum set under multiple assumed material component ratios based on the cone set characterizing the light flux spectrum set.

9. A device for determining a material composition ratio, characterized in that: include: processor; a memory for storing processor-executable instructions; The processor is configured to implement the method described in any one of claims 1 to 7 when executing the instructions stored in the memory.

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