Dynamic sound velocity self-adaptive ultrasonic opto-acoustic bimodal imaging method and dynamic sound velocity self-adaptive ultrasonic opto-acoustic bimodal imaging system

Abstract

The invention relates to the field of sound velocity, opto-acoustic and ultrasonic imaging, in particular to a dynamic sound velocity self-adaptive ultrasonic opto-acoustic bimodal imaging method and a dynamic sound velocity self-adaptive ultrasonic opto-acoustic bimodal imaging system. The method comprises the following steps: acquiring an ultrasonic signal and a photoacoustic signal; reconstructing a sound velocity distribution diagram according to the ultrasonic signal; based on the sound velocity distribution diagram, reconstructing a related time delay diagram; and reconstructing an ultrasonic image and a photoacoustic image based on the related time delay graph. The problems that a traditional sound velocity correction method is limited in application range, inconvenient to operate, high in cost, low in resolution and the like are solved; the adopted sound velocity correction algorithm is high in resolution, is suitable for various transducers of linear arrays, convex arrays, ring arrays, spherical arrays and the like, and is widely applied to most parts of a human body; cancerous tissues, normal tissues, muscles, fat and the like can be accurately distinguished; the ultrasonic and photoacoustic dual-mode imaging system is simple in structure, is not influenced by illumination, is high in sound velocity resolution and signal-to-noise ratio, supports seamless correction and registration of ultrasonic and photoacoustic dual-mode imaging, and promotes clinical application and development of ultrasonic and photoacoustic dual-mode imaging.

Description

Technical Field

[0001] The invention relates to the fields of sound velocity, photoacoustic and ultrasonic imaging, and in particular to a dynamic sound velocity adaptive ultrasonic photoacoustic dual-modality imaging method and system. Background Art

[0002] Photoacoustic imaging (PA) has gained increasing attention in the field of medical imaging due to its significant advantages such as high molecular and functional contrast and high resolution. At the same time, ultrasound imaging (US) occupies an important position in clinical diagnosis due to its rich anatomical information, low cost, portability, high biosafety and strong penetration. At present, by seamlessly combining photoacoustic imaging with ultrasound imaging and using a shared ultrasound transducer and data acquisition system, co-registered images with complementary contrast can be obtained, providing more accurate information for tumor diagnosis and staging, intraoperative navigation, etc. However, due to the complex structure of the human body and the significant differences in sound speed between different tissues and different parts of the same tissue, traditional photoacoustic and ultrasound imaging technologies are mostly based on constant sound speed for image reconstruction, resulting in distortion of the reconstructed image and affecting the clinical application effect.

[0003] In order to solve the above problems, a variety of sound velocity correction algorithms have been developed. For example, the sound velocity correction method of transmission ultrasound tomography based on annular ultrasonic transducers can reconstruct the sound velocity distribution for correction, but the iterative calculation is time-consuming and the resolution of the dual-velocity method is low. It is only applicable to acoustically transparent tissues, such as breasts, and is inconvenient to operate and has high hardware costs. Although the compressed sensing method can compensate for the sound velocity of cortical bone ultrasound imaging, it is only applicable to regular medium models with large differences in multi-layer sound velocities, with low lateral resolution and limited scope of application. The frequency domain analysis method compensates for the sound velocity of photoacoustic images, but is easily affected by uneven illumination and low signal-to-noise ratio. The method of reconstructing the sound velocity distribution based on prior information (such as CT or MRI) is theoretically feasible, but the reconstructed sound velocity map has large deviations, is difficult to align, and is costly, which is not conducive to clinical transformation.

[0004] In view of the limitations of the prior art, the present invention aims to provide a dynamic sound velocity adaptive ultrasound-photoacoustic dual-modality imaging method, which can be widely applied to various tissues, has low cost and high sound velocity resolution. Through innovative technical means, the present invention can obtain and correct the sound velocity distribution inside the tissue in real time, thereby significantly improving the resolution and signal-to-noise ratio of ultrasound-photoacoustic dual-modality imaging, and correcting image distortion caused by sound velocity heterogeneity, providing more reliable ultrasound and photoacoustic images for clinical diagnosis and treatment. Summary of the invention

[0005] In view of the defects in the prior art, the present invention provides a dynamic sound velocity adaptive ultrasonic photoacoustic dual-modality imaging method and system.

[0006] In the first aspect, the present invention provides a dynamic sound velocity adaptive ultrasound-photoacoustic dual-modal imaging method, comprising the following steps: acquiring ultrasound signals and photoacoustic signals; reconstructing a sound velocity distribution map based on the ultrasound signals; reconstructing a related time delay map based on the sound velocity distribution map; and reconstructing ultrasound images and photoacoustic images based on the related time delay map. The present invention improves imaging quality by utilizing the complementary advantages of ultrasound signals and photoacoustic signals in imaging; the sound velocity distribution map reconstructed based on ultrasound signals can accurately reflect the sound velocity changes inside the tissue, and the tissue sound velocity, as a new contrast, provides more reference information for disease diagnosis; the related time delay map further reconstructed based on the sound velocity distribution map can accurately capture the time difference of signal propagation and enhance the spatial resolution of the image; the ultrasound image and photoacoustic image reconstructed based on the related time delay map remove the propagation velocity error artifacts and have more anatomical details, providing strong visualization support for early detection and precise treatment of diseases.

[0007] Optionally, the acquisition of ultrasonic signals and photoacoustic signals includes: using plane waves of different angles generated by an ultrasonic transducer to excite the measured tissue and generate echo signals, which are received by the ultrasonic transducer, and the ultrasonic transducer is used to receive ultrasonic and photoacoustic signals, including linear arrays, convex arrays, circular arrays and spherical transducers; using an ultrasonic acquisition system to acquire the echo signals received by the ultrasonic transducer to obtain acquired ultrasonic signals; based on the ultrasonic signal, using the ultrasonic acquisition system to trigger a pulse laser to emit a pulse laser, and the pulse laser is used to irradiate the measured tissue to generate photoacoustic signals, which are received by the ultrasonic transducer; using the ultrasonic acquisition system to acquire the photoacoustic signals received by the ultrasonic transducer to obtain acquired photoacoustic signals. The present invention utilizes plane waves of different angles generated by an ultrasonic transducer to excite the measured tissue and obtain the internal structure information of the tissue in all directions. The reception of echo signals further ensures the integrity of the information. The echo signals are accurately collected by an ultrasonic acquisition system, which effectively improves the signal-to-noise ratio and resolution of the ultrasonic signals, and provides a high-quality data basis for subsequent image processing. The pulsed laser is triggered by the ultrasonic signal to emit a pulsed laser, which not only ensures the temporal synchronization of the photoacoustic signal and the ultrasonic signal, but also improves the imaging efficiency.

[0008] Optionally, reconstructing a sound velocity distribution map based on the ultrasonic signal includes: setting an assumed average sound velocity for each emission angle in ultrasonic imaging, wherein the assumed average sound velocity is 1540 m / s and is inconsistent with the actual sound velocity distribution; obtaining a time delay error based on the inconsistent distribution of the assumed average sound velocity and the actual sound velocity; obtaining a relative time delay error based on the relative phase difference obtained for the same pixel point under different propagation paths; constructing a sound velocity reconstruction model based on the relative time delay error and the time delay error; and obtaining a sound velocity distribution map through the sound velocity reconstruction model. The present invention presets an assumed average sound speed and identifies its inconsistency with the actual sound speed distribution, accurately quantifies the time delay error, and provides a key basis for subsequent calculations; by utilizing the relative phase difference of the same pixel point under different propagation paths, the phase change caused by the sound speed change is effectively captured, and the sensitivity of sound speed distribution reconstruction is enhanced; the relative time delay error is obtained through the relative phase difference, and a sound speed reconstruction model is established based on it, which accurately reflects the actual distribution of sound speed in the tissue, provides accurate sound speed parameters for subsequent image reconstruction, significantly improves the resolution and signal-to-noise ratio of imaging, and provides medical diagnosis with the actual sound speed distribution information inside the tissue.

[0009] Optionally, the relative phase difference satisfies the following expression: in, Indicates Angle and The relative phase difference in the ultrasound image corresponding to the angle is is the ultrasonic signal frequency, Indicates Angle and The relative time delay error in the ultrasound image corresponding to the angle is is the difference between the true speed of sound and the estimated speed of sound, is a set of finite number of pixels in a predefined imaging area; the sound speed reconstruction model satisfies the following expression: in, is the reciprocal of the true speed of sound, is the time delay error, The propagation path of different target pixels relative to different transmitting and receiving array elements. The present invention provides a scientific basis for quantifying the unevenness of sound velocity distribution through the mathematical expression of relative phase difference; through the sound velocity reconstruction model, the inverse of the real sound velocity is calculated, providing accurate algorithm support for the construction of the sound velocity distribution map; through the above two expressions, not only the resolution and signal-to-noise ratio of sound velocity reconstruction are improved, but also the imaging technology's ability to analyze complex tissue structures is enhanced.

[0010] Optionally, the reconstruction of the relevant time delay map based on the sound velocity distribution map includes: based on the sound velocity distribution map, using a multi-module rapid marching method to construct a time delay model for different array elements and different ultrasonic emission angles, the time delay model is used to describe the propagation mode of ultrasonic waves in tissues with uneven sound velocity; based on the time delay model, reconstructing the relevant time delay map. The present invention constructs a time delay model using a multi-module rapid marching method, efficiently handles complex propagation paths in tissues with uneven sound velocity, accurately simulates the propagation mode of ultrasonic waves, and provides a solid theoretical basis for the reconstruction of relevant time delay maps; the time delay model not only takes into account the spatial distribution of sound velocity, but also incorporates the propagation characteristics of ultrasonic waves, accurately describing the time delay differences of ultrasonic waves in different tissue regions.

[0011] Optionally, the time delay model satisfies the following expression: in, To reconstruct pixels Relative to the time delay between different array elements, To reconstruct pixels The present invention accurately describes the time delay distribution of ultrasound propagation in tissues through the inverse relationship between the gradient vector and the speed of sound, providing a scientific mathematical basis for the reconstruction of related time delay maps; the model fully considers the inhomogeneity of the speed of sound in space, so that the reconstructed time delay map can truly reflect the propagation characteristics of ultrasound in complex tissues, improving the resolution and signal-to-noise ratio of imaging; the application of this model not only optimizes the imaging process, but also enhances the imaging technology's ability to analyze tissue structure, providing more sophisticated time dimension information for medical diagnosis.

[0012] Optionally, reconstructing the ultrasound image and the photoacoustic image based on the related time delay map includes: reconstructing the ultrasound image based on the related time delay map; reconstructing the photoacoustic image based on the related time delay map. The present invention uses a multi-module fast marching method to efficiently process a large amount of data, quickly and accurately reconstruct ultrasound images and photoacoustic images, and significantly improves the imaging speed; the image reconstructed based on the related time delay map has a high spatial resolution and contrast, and more clearly displays the microstructure and functional information of the tissue, which helps to improve the early detection rate and diagnostic accuracy of clinical diseases.

[0013] Optionally, the reconstructing of the ultrasound image based on the related time delay map includes: based on the related time delay map, performing time delay compensation on the ultrasound signal; and reconstructing the ultrasound image after correcting the sound velocity through the time delay compensation. The present invention effectively solves the time delay problem caused by uneven sound velocity during the propagation of ultrasound signals through precise time delay compensation, thereby improving the signal-to-noise ratio and resolution of ultrasound images; by applying the multi-module fast marching method, the time delay compensation process can be completed efficiently and accurately, greatly shortening the image reconstruction time and improving imaging efficiency; through the time delay compensation processing, the reconstructed ultrasound image more truly reflects the structure and functional information of the tissue.

[0014] Optionally, the reconstruction of the photoacoustic image based on the related time delay map includes: based on the related time delay map, correcting the sound velocity and time delay in the inhomogeneous tissue; and reconstructing the photoacoustic image after the correction of the sound velocity and time delay. The present invention significantly improves the resolution and signal-to-noise ratio of the photoacoustic image by accurately correcting the sound velocity and time delay in the inhomogeneous tissue, so that the image more realistically reflects the structure and functional information of the tissue; by applying the multi-module fast marching method, the correction process can be completed efficiently and accurately, greatly shortening the image reconstruction time and improving the imaging efficiency.

[0015] In a second aspect, the present invention provides a dynamic sound velocity adaptive ultrasound-photoacoustic dual-modality imaging system, which includes an input device, a processor, an output device and a memory, wherein the input device, the processor, the output device and the memory are interconnected, wherein the memory is used to store a computer program, the computer program includes program instructions, the processor is configured to call the program instructions, and the system uses the dynamic sound velocity adaptive ultrasound-photoacoustic dual-modality imaging method. The system has the following three creative effects: First, by integrating advanced signal processing algorithms and adaptive technologies, it can accurately capture changes in sound speed and instantly adjust the sound speed parameters for image reconstruction at different positions, thereby effectively avoiding image distortion problems caused by uneven sound speed, significantly improving the accuracy and reliability of ultrasound and photoacoustic dual-modality imaging, and providing more accurate information support for clinical diagnosis and treatment; second, by optimizing hardware design and algorithm processes, while ensuring imaging quality, it reduces overall costs, making the technology easier to promote and apply in clinical environments; third, by adjusting system parameters and configurations, it can flexibly respond to various complex imaging scenarios, including tissue imaging at different locations and depths, making the system have potential application value in multiple fields such as tumor diagnosis and staging, intraoperative navigation, etc., providing more comprehensive support for clinical diagnosis and treatment.

[0016] Compared with the prior art, the beneficial effects of the present invention include: using a creative sound velocity correction algorithm, breaking through the limitations of traditional technology, being applicable to a variety of transducers such as linear arrays, convex arrays and circular arrays, being widely applicable to most parts of the human body, and requiring no complicated operations, greatly reducing patient discomfort and the burden on operators. At the same time, it supports a variety of transducer types, enhancing the flexibility and applicability of the system. It has high-resolution imaging capabilities, can accurately distinguish tissues with tiny differences in sound velocity, and improves diagnostic accuracy and timeliness. It is not affected by light, has high sound velocity resolution and signal-to-noise ratio, and stable and reliable imaging quality. It achieves seamless integration and registration of ultrasound and photoacoustic dual-modality imaging, provides rich diagnostic information, does not require additional registration steps, and simplifies the workflow. In addition, it reduces hardware costs, improves cost-effectiveness, is conducive to widespread clinical application, improves patient comfort and doctor diagnostic efficiency, and provides a new means for clinical diagnosis and treatment. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 It is a flow chart of a dynamic sound velocity adaptive ultrasound-photoacoustic dual-modality imaging method according to an embodiment of the present invention; Figure 2 This is a flow chart of the excitation and collection of ultrasonic signals and photoacoustic signals according to an embodiment of the present invention; Figure 3 An image flow chart of a dynamic sound velocity adaptive ultrasound-photoacoustic dual-modality imaging algorithm according to an embodiment of the present invention; Figure 4 A sound velocity distribution diagram corresponding to a simulation model simulating distribution of different tissues of a human arm according to an embodiment of the present invention; Figure 5 A comparison diagram of photoacoustic images obtained by different imaging methods according to an embodiment of the present invention; Figure 6 A comparison diagram of the half-wave full width values ​​of photoacoustic images obtained by different imaging methods according to an embodiment of the present invention; Figure 7 This is a diagram for verifying the system performance of an ultrasound-photoacoustic dual-modality imaging experiment based on ex vivo tissue according to an embodiment of the present invention; Figure 8 A distortion result diagram and a result diagram after distortion correction according to an embodiment of the present invention; Fig. 9 A histogram of pencil lead diameters at different positions according to different imaging methods of an embodiment of the present invention; Fig.10 Schematic diagram of the structure of a dynamic sound velocity adaptive ultrasonic and photoacoustic dual-modality imaging system according to an embodiment of the present invention. DETAILED DESCRIPTION

[0018] The specific embodiments of the present invention will be described in detail below. It should be noted that the embodiments described herein are only for illustration and are not intended to limit the present invention. In the following description, a large number of specific details are set forth in order to provide a thorough understanding of the present invention. However, it is obvious to those of ordinary skill in the art that these specific details do not need to be adopted to implement the present invention. In other examples, in order to avoid confusing the present invention, known circuits, software or methods are not specifically described.

[0019] Throughout the specification, references to "one embodiment," "an embodiment," "an example," or "an example" mean that a particular feature, structure, or characteristic described in conjunction with the embodiment or example is included in at least one embodiment of the present invention. Therefore, the phrases "in one embodiment," "in an embodiment," "an example," or "an example" appearing in various places throughout the specification do not necessarily all refer to the same embodiment or example. In addition, particular features, structures, or characteristics may be combined in one or more embodiments or examples in any suitable combination and / or subcombination. In addition, it should be understood by those of ordinary skill in the art that the figures provided herein are for illustrative purposes and that the figures are not necessarily drawn to scale.

[0020] See also Figure 1 The embodiment of the present invention provides a dynamic sound velocity adaptive ultrasound photoacoustic dual-modality imaging method, the method comprising the following steps: S1. Acquire ultrasonic signals and photoacoustic signals.

[0021] Among them, S1 includes the following steps: S11. Acquire ultrasonic signals.

[0022] See also Figure 2 In one embodiment, an ultrasonic transducer and an ultrasonic acquisition system are used to realize the excitation and acquisition of ultrasonic signals.

[0023] Specifically, first, the ultrasonic transducer is connected to the ultrasonic acquisition system.

[0024] Furthermore, by programming different emission time delays of each emission element of the ultrasonic transducer, plane waves of different angles are formed and emitted to the measured tissue.

[0025] Furthermore, the measured tissue generates a corresponding echo signal, which is received by the ultrasonic transducer.

[0026] Furthermore, the ultrasonic acquisition system acquires the echo signal received by the ultrasonic transducer to obtain the ultrasonic signal. The ultrasonic transducer includes a linear array, a convex array, a semi-circular array, a circular array, and a spherical ultrasonic transducer.

[0027] S12. Acquire photoacoustic signals.

[0028] In one embodiment, after the ultrasonic signal is collected in step S11, the pulse laser is triggered by the ultrasonic collection system to emit pulse laser.

[0029] Furthermore, the pulsed laser is irradiated on the tissue to be measured to generate a photoacoustic signal.

[0030] Furthermore, the ultrasonic acquisition system acquires the photoacoustic signal through an ultrasonic transducer, which is the same as the ultrasonic transducer mentioned in step S11.

[0031] S2. Reconstruct a sound velocity distribution map according to the ultrasonic signal.

[0032] In one embodiment, see Figure 3 , Figure 3 The first three steps in the process are to obtain the sound velocity distribution images using the sound velocity reconstruction algorithm.

[0033] Specifically, Figure 3 The premise of step 1 is that traditional ultrasound imaging usually uses the delay-and-sum (DAS) algorithm for image reconstruction. The core of the algorithm is to compensate for the ultrasonic propagation delay. Strictly speaking, the calculation of propagation delay requires knowing the sound velocity of the area passed by the transmitting array element and the receiving array element to the target pixel point. The distribution of speed-of-sound (SOS). The propagation delay is calculated as follows: in, is the actual propagation delay of the ultrasonic signal, is a set of finite number of pixels in a predefined imaging area. is the propagation path of a specific pixel, is the true speed of sound. Usually, the distribution of the true speed of sound cannot be accurately obtained, so its estimated value is often used, such as the average speed of sound of soft tissue (1540m / s), for related image reconstruction.

[0034] Furthermore, based on the above premise, Figure 3 In step 1, image reconstruction is performed for each emission angle in ultrasound imaging according to the assumed average sound speed (1540 m / s). Since the assumed average sound speed during reconstruction is inconsistent with the actual sound speed distribution of the tissue, the actual propagation delay is inconsistent with the calculated propagation delay, which in turn generates a time delay error, which satisfies the following expression: in, is the time delay error, is the actual propagation delay of the ultrasonic signal, To calculate the propagation delay, To estimate the speed of sound, is the reciprocal of the true speed of sound, To estimate the inverse of the speed of sound, is the difference between the true speed of sound and the estimated speed of sound, is the true speed of sound, is the propagation path of a specific pixel. Due to the existence of time delay error, phase distortion occurs in the image reconstruction process. The phase distortion is the difference between the phase of the signal corresponding to the real time delay and the phase of the signal corresponding to the estimated time delay. The phase distortion cannot be directly measured in a single ultrasound image, but the relative phase difference obtained by the same pixel under different propagation paths can be calculated, such as Figure 3 As shown in step 2 in , a phase shift diagram is obtained through step 2 to reflect phase distortion.

[0035] Furthermore, based on the relative phase difference, a relationship with the relative time delay error is established.

[0036] Specifically, the relationship between the relative phase difference and the relative time delay error is as follows: in, Indicates Angle and The relative phase difference in the ultrasound image corresponding to the angle is is the ultrasonic signal frequency, Indicates Angle and The relative time delay error in the ultrasound image corresponding to the angle is is the difference between the true speed of sound and the estimated speed of sound, is a set of finite number of pixels in a predefined imaging area. This relation describes the relationship based on the spatial domain. Forward problem of method.

[0037] Furthermore, a sound velocity reconstruction model is constructed, and the sound velocity reconstruction model performs sound velocity reconstruction according to a forward problem in matrix form, such as Figure 3 As shown in step 3 in , the sound speed reconstruction model satisfies the following expression: in, is the reciprocal of the true speed of sound, is the time delay error, It is the propagation path of different target pixels relative to different transmitting and receiving array elements.

[0038] Furthermore, a sound speed distribution map is reconstructed according to the sound speed reconstruction model.

[0039] S3. Based on the sound speed distribution diagram, reconstruct a related time delay diagram.

[0040] In one embodiment, in order to use the obtained sound velocity distribution diagram to perform sound velocity correction on the photoacoustic image and the ultrasound image, Figure 3 In step 4, a series of time delay diagrams based on the sound velocity diagram are calculated using the multi-module fast marching method (MSFM). Based on the MSFM method, a time delay model between different array elements is constructed. The time delay model is used to describe the propagation mode of ultrasound in tissues with uneven sound velocity: the time delay model satisfies the following expression: in, To reconstruct pixels Relative to the time delay between different array elements, To reconstruct pixels The speed of sound at .

[0041] Furthermore, the delay expression is used to reconstruct a related delay graph.

[0042] S4. Reconstruct the ultrasound image and the photoacoustic image through the related time delay map.

[0043] Among them, S4 includes the following steps: S41. Reconstruct an ultrasound image using the related time delay graph.

[0044] In one embodiment, based on the correlation delay graph obtained in step S3, the ultrasound image is reconstructed using conventional composite plane waves (CPW). The image reconstruction principle is to perform delayed coherent summation of the signals received by the linear array ultrasound transducer. Ultrasound imaging is divided into two parts: receiving and transmitting, and the formula is as follows: in, The target pixel The total ultrasonic signal at For the The receiving array element The ultrasonic signal received at any time, For time, is the total number of channels of photoacoustic signals received by the receiving array element, The target pixel The relative time delay at The target pixel The launch time delay at The target pixel The receiving time delay at the location, the transmitting time delay and the receiving time delay respectively satisfy the following expressions: in, For different deflection angles, is the relative position of different receiving array elements, To estimate the speed of sound.

[0045] It should be noted that this image reconstruction theory is only applicable to tissues with uniform sound velocity and known tissue sound velocity. For tissues with non-uniform sound velocity and unknown tissue sound velocity, the reconstruction results will be seriously distorted in shape and size. Therefore, it is necessary to perform sound velocity correction and use the MSFM method to compensate for the delay of the transmitting and receiving parts of the ultrasonic signal. The relevant expressions are as follows: in, To use the MSFM method to compensate for the delay at the target pixel The relative time delay at To use the MSFM method to compensate for the delay at the target pixel The launch time delay at To use the MSFM method to compensate for the delay at the target pixel The receiving time delay at For time, is the total number of channels of photoacoustic signals received by the receiving array element, To use the MSFM method to compensate for the delay The receiving array element The ultrasonic signal received at any time, To use the MSFM method to compensate for the delay at the target pixel The total ultrasonic signal at .

[0046] S42. Reconstruct a photoacoustic image using the relevant time delay image.

[0047] In one embodiment, when reconstructing a photoacoustic image, a theory of how to correct a photoacoustic image based on a delayed reconstruction algorithm (DAS) and a delayed multiplication and sum reconstruction algorithm (DMAS) is given.

[0048] Specifically, firstly, based on the principle of photoacoustic imaging, the signals received by the linear array ultrasonic transducer are subjected to delayed coherent summation, which is expressed as follows: in, For the The receiving array element The photoacoustic signal received at any time, is the total number of channels of photoacoustic signals received by the receiving array element, To receive the transducer array element to the target pixel The time delay at For time, The target pixel The total photoacoustic signal obtained based on the DAS reconstruction algorithm, The target pixel The total photoacoustic signal obtained based on the DMAS reconstruction algorithm, For the The receiving array element The photoacoustic signal received at any time, For the The receiving array element The photoacoustic signal received at all times.

[0049] Normally, the sound velocity distribution in the tissue cannot be known in advance, so the average sound velocity of soft tissue (1540m / s) is often selected as the reconstruction sound velocity for photoacoustic image reconstruction. The choice of constant sound velocity is obviously only applicable to imaging of tissue with uniform sound velocity, which is inconsistent with the actual situation and will lead to serious deterioration of the imaging quality of tissue with uneven sound velocity. Therefore, it is necessary to perform relevant sound velocity and time delay correction based on the CUTE method and MSFM method in the previous theory, and the formula is as follows: in, is the time delay of the corresponding receiving array element relative to each pixel in the imaging area obtained based on the sound velocity map and using the MSFM method, The target pixel The total photoacoustic signal obtained based on the DAS reconstruction algorithm and the MSFM method, For the The receiving array element The photoacoustic signal received at any time, is the total number of channels of photoacoustic signals received by the receiving array element, Target pixel Based on DMAS reconstruction algorithm and The total photoacoustic signal obtained by the method is For the The receiving array element The photoacoustic signal received at any time, For the The receiving array element The photoacoustic signal received at all times.

[0050] In a specific embodiment, a numerical model is established by using the acoustic simulation software K-WAVE toolbox in MATLAB to verify the feasibility of the imaging algorithm of the present invention, wherein the relevant parameters in the simulation process are consistent with the actual physical parameters.

[0051] Specifically, when performing photoacoustic dual-modality imaging on the human arm, the difference in sound speed between the fat layer and the muscle layer significantly reduces the accuracy of imaging. Specifically, the sound speed of fat tissue is usually lower than that of muscle tissue. This difference in acoustic properties leads to distortion of the sound wave propagation path, causing signal attenuation and scattering. This not only blurs the details of the vascular structure, making it difficult to accurately identify and locate the blood vessels, but also interferes with the precise measurement of the size and thickness of the fat layer, causing errors in the assessment of fat distribution. Therefore, the difference in sound speed has become a key issue that needs to be solved in photoacoustic dual-modality imaging.

[0052] Therefore, the present invention sets up a group of simulation models simulating the distribution of different tissues in the human arm, and its sound velocity distribution diagram is as follows: Figure 4 (a). The upper layer in the sound velocity diagram simulates the propagation sound path (sound velocity: 1540m / s, density: 1000m / s), the middle layer simulates fat (sound velocity: 1430m / s, density: 960m / s), its thickness is 10mm, and the lower layer simulates muscle (sound velocity: 1560m / s, density: 1100m / s). For photoacoustic imaging simulation, the present invention sets up a 5-row 5-column absorption point matrix, the spacing between rows and the spacing between columns are both 5mm, and the diameter is 0.5mm. For ultrasound imaging simulation, plane waves of different angles are generated by setting the time delay of different transmitting array elements, and composite plane wave imaging is performed. The sampling frequency in the simulation is 62.5MHz to ensure numerical stability in ultrasound and photoacoustic simulation; the calculation grid consists of 1000×1000 pixels, and the pixel size is 0.05mm. The specific process is as follows: First, the present invention reconstructs the sound velocity distribution map based on the ultrasonic simulation data, and the result is shown in the attached figure. Figure 4 As shown in (b), the reconstruction result can not only distinguish the three tissues with different sound velocities very well, but also the average sound velocity of the corresponding area has a very small error with the preset sound velocity.

[0053] Furthermore, ultrasound was reconstructed, and the conventional ultrasound imaging method based on a constant sound velocity of 1540 m / s and the sound velocity correction imaging method based on a sound velocity map of the present invention were respectively demonstrated. It can be seen that the thickness of the fat layer in the ultrasound image reconstructed by the method of the present invention is closer to the actual fat layer thickness than the thickness of the fat layer in the ultrasound image reconstructed based on a constant sound velocity, as shown in FIG. Figure 4 As shown in (c)(d). Figure 5(a)(b)(c)(d) show the photoacoustic image comparison results of the traditional delay summation method with a preset sound speed of 1525m / s, the delay summation method based on sound speed map correction, the traditional delay multiplication method with a preset sound speed of 1525m / s, and the delay multiplication method based on sound speed map correction of the present invention. Visually, the algorithm we proposed has the best reconstruction effect for each sound source absorption point, such as Figure 5 (e)(f)(g)(h) As shown. We also analyzed its half-wave full width (FWHM) to prove that our proposed algorithm has the highest resolution. The half-wave full widths of different reconstruction methods are: delay sum vs delay multiplication vs sound velocity correction delay sum vs sound velocity correction delay multiplication = 1.51mm vs 0.85mm vs 1.04mm vs 0.72mm, among which this method (sound velocity correction delay multiplication) is closest to the true value (0.5mm), as shown in Figure 6 shown.

[0054] In another specific embodiment, the effect of the dynamic sound velocity adaptive ultrasound-photoacoustic dual-modality imaging algorithm proposed in the present invention is further verified by an ultrasound-photoacoustic dual-modality imaging experiment based on ex vivo tissue.

[0055] Specifically, first, the degassed chicken breast tissue is placed in a cubic container.

[0056] Furthermore, the degassed fat tissue is stacked on top of the chicken breast tissue.

[0057] Furthermore, a solid coupling layer with a known sound velocity is placed above the fat tissue. The purpose of using the solid coupling layer is to make the system out of the water bath environment, greatly increasing the scope of application of the system. The container material used in the experiment is polymethyl methacrylate (PMMA) with a wall thickness of 3mm. A pencil lead (diameter: 0.5mm) is placed between the chicken breast and the fat, and another pencil lead (diameter: 0.5mm) is placed between the fat layer and the solid coupling layer. Figure 7 (a) shown.

[0058] Furthermore, pulsed lasers emitted by a pulsed laser were used for photoacoustic imaging. According to the literature and the phantom formula, the sound velocity of the top solid coupling layer is 1560m / s, which is made of agar glycerol, the sound velocity of the middle layer of fat is 1430m / s, and the sound velocity of the bottom chicken breast tissue is 1560m / s. The sound velocity map obtained by pulse echo sound velocity reconstruction can not only distinguish the three tissues, but also distinguish the two different fat tissues, such as Figure 7 (b) is shown. It is worth explaining that the fat in the ultrasound image has two layers. This is because when the in vitro model is made, there are two types of fat (dense type and loose type). A clear dividing line can be seen from the ultrasound image, such as Figure 7 As shown in (c). For ultrasound imaging, by comparing the ultrasound image reconstructed based on the average sound velocity and the ultrasound image reconstructed based on the sound velocity map, it is found that the fat layer thickness of the ultrasound image after sound velocity correction is smaller and closer to the true value, as shown in Figure 7 (c) with Figure 7 (d) as shown.

[0059] Furthermore, by comparing the results of different photoacoustic reconstruction algorithms, it is found that compared with the delay sum and delay multiplication sum after sound velocity correction, the shape of the pencil lead on the lower left side of the delay sum and delay multiplication sum at constant speed has been distorted, as shown in Figure 2. Figure 8 As shown in (e) and (g), the method of using the sound velocity map reconstruction corrects the distortion artifacts caused by incorrect sound velocity, such as Figure 8 (f)(h) As shown. By analyzing its half-wave full width (FWHM), it can be found that the algorithm proposed by the present invention has the highest resolution, as shown in Fig. 9 The experimental results based on ex vivo tissue are consistent with the simulation results, which provides strong support for the algorithm proposed in the present invention to be applicable to the human body.

[0060] See also Fig.10 , Fig.10 The structure diagram of the dynamic sound velocity adaptive ultrasound photoacoustic dual-modality imaging system in the embodiment of the present invention is shown. The system includes an input device, a processor, an output device, and a memory, wherein the input device, the processor, the output device, and the memory are interconnected, wherein the memory is used to store a computer program, the computer program includes program instructions, the processor is configured to call the program instructions, and the system uses the dynamic sound velocity adaptive ultrasound photoacoustic dual-modality imaging method.

[0061] In this embodiment, the input device includes an ultrasonic transducer, a pulsed laser, and a control unit; Specifically, the ultrasonic transducer is used to receive a control signal from the system, and transmit plane waves of different angles to the measured tissue according to a preset transmission time delay. At the same time, as a receiver, it collects ultrasonic echo signals generated by the measured tissue; the pulse laser is used to receive a trigger signal from the system, and emit a pulse laser to irradiate the measured tissue to stimulate a photoacoustic signal; the control unit includes a keyboard and a touch screen, allowing the user to input control instructions, such as setting the transmission time delay of the ultrasonic transducer, triggering the pulse laser, and selecting imaging parameters.

[0062] The processor includes a central processing unit, which is used to receive signals and data from an input device, execute an imaging algorithm, and reconstruct ultrasound and photoacoustic images; the signals and data include signals collected by an ultrasound transducer and instruction data input by a user through a control unit; the imaging algorithm includes a CUTE method and an MSFM method.

[0063] The output device includes a display for displaying the reconstructed ultrasound image, photoacoustic image, and sound velocity distribution diagram.

[0064] The memory uses a high-speed solid-state hard drive, which has the characteristics of fast reading and writing speed, large capacity and high reliability. It is mainly used to store data input by the input device and the result data processed by the processor, and can meet the needs of large data storage.

[0065] In summary, the present invention breaks through the limitations of traditional technology, is widely applicable to most parts of the human body, does not require complicated operations, and reduces patient discomfort and operator burden. At the same time, it supports multiple transducer types, enhancing the flexibility and applicability of the system. The high-resolution imaging capability can accurately distinguish tissues with tiny differences in sound velocity, improving the accuracy and timeliness of diagnosis. It is not affected by light, has high sound velocity resolution and signal-to-noise ratio, and stable and reliable imaging quality. It achieves seamless integration and registration of ultrasound and photoacoustic dual-modality imaging, provides rich diagnostic information, does not require additional registration steps, and simplifies the workflow. In addition, it also reduces hardware costs and improves cost-effectiveness, is conducive to widespread clinical application, improves patient comfort and doctor diagnostic efficiency, and provides a new means for clinical diagnosis and treatment.

[0066] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein by equivalents. These modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present invention, and they should all be included in the scope of the claims and specification of the present invention.

Claims

1. A dynamic sound velocity adaptive ultrasonic photoacoustic dual-modality imaging method, characterized in that: The method comprises the following steps: Acquiring ultrasonic signals and photoacoustic signals; reconstructing a sound velocity distribution map according to the ultrasonic signal; Reconstructing a related time delay graph based on the sound speed distribution graph; Based on the correlation time delay map, an ultrasound image and a photoacoustic image are reconstructed.

2. The method of dynamic sound velocity adaptive ultrasonic photoacoustic dual-modality imaging according to claim 1, characterized in that: The obtaining of ultrasonic signals and photoacoustic signals comprises: Using plane waves of different angles generated by an ultrasonic transducer to excite the tissue under test and generate echo signals, the echo signals are received by the ultrasonic transducer, and the ultrasonic transducer is used to receive ultrasound and photoacoustic signals, including linear array, convex array, circular array and spherical transducers; Using an ultrasonic acquisition system to acquire the echo signal received by the ultrasonic transducer to obtain an acquired ultrasonic signal; Based on the ultrasonic signal, the ultrasonic acquisition system is used to trigger a pulse laser to emit a pulse laser, wherein the pulse laser is used to irradiate the measured tissue to generate a photoacoustic signal, and the photoacoustic signal is received by the ultrasonic transducer; The ultrasonic acquisition system is used to acquire the photoacoustic signal received by the ultrasonic transducer to obtain the acquired photoacoustic signal.

3. The method of dynamic sound velocity adaptive ultrasonic photoacoustic dual-modality imaging according to claim 1, characterized in that: The reconstructing the sound velocity distribution map according to the ultrasonic signal comprises: An assumed average sound speed is set for each emission angle in ultrasound imaging, wherein the assumed average sound speed is 1540 m / s and is inconsistent with the actual sound speed distribution; Obtaining a time delay error based on the inconsistent distribution of the assumed average sound speed and the actual sound speed; Based on the relative phase difference obtained for the same pixel under different propagation paths, the relative time delay error is obtained; constructing a sound speed reconstruction model based on the relative time delay error and the time delay error; A sound velocity distribution diagram is obtained through the sound velocity reconstruction model.

4. The method of dynamic sound velocity adaptive ultrasound dual-modality imaging according to claim 3, characterized in that: The relative phase difference satisfies the following expression: in, Indicates Angle and The relative phase difference in the ultrasound image corresponding to the angle is is the ultrasonic signal frequency, Indicates Angle and The relative time delay error in the ultrasound image corresponding to the angle is is the difference between the true speed of sound and the estimated speed of sound, is a set of finite number of pixels in a predefined imaging area; the sound speed reconstruction model satisfies the following expression: in, is the reciprocal of the true speed of sound, is the time delay error, It is the propagation path of different target pixels relative to different transmitting and receiving array elements.

5. The method of dynamic sound velocity adaptive ultrasonic photoacoustic dual-modality imaging according to claim 1, characterized in that: The reconstructing the relevant time delay graph based on the sound speed distribution graph comprises: Based on the sound velocity distribution diagram, a time delay model with different emission angles and array elements is constructed using a multi-module rapid marching method, wherein the time delay model is used to describe the propagation mode of ultrasound in tissue with uneven sound velocity; Based on the time delay model, a related time delay graph is reconstructed.

6. The method of dynamic sound velocity adaptive ultrasonic photoacoustic dual-modality imaging according to claim 5, characterized in that: The time delay model satisfies the following expression: in, To reconstruct pixels Relative to the time delay between different array elements, To reconstruct pixels The speed of sound at .

7. The method of dynamic sound velocity adaptive ultrasonic photoacoustic dual-modality imaging according to claim 1, characterized in that: The reconstructing of the ultrasound image and the photoacoustic image based on the correlation time delay graph comprises: reconstructing an ultrasound image based on the correlation time delay map; Based on the correlation time delay map, a photoacoustic image is reconstructed.

8. The method of dynamic sound velocity adaptive ultrasonic photoacoustic dual-modality imaging according to claim 7, characterized in that: The reconstructing the ultrasound image based on the related time delay graph comprises: Based on the relevant time delay graph, solving the time delay compensation of the ultrasonic signal and obtaining the time delay compensated ultrasonic signal; The ultrasonic image is reconstructed by using the time delay compensated ultrasonic signal.

9. The method of dynamic sound velocity adaptive ultrasonic photoacoustic dual-modality imaging according to claim 7, characterized in that: The reconstructing the photoacoustic image based on the relevant time delay graph comprises: Based on the relevant time delay graph, performing time delay compensation on the photoacoustic signal and obtaining a time delay compensated photoacoustic signal; The photoacoustic image is reconstructed by using the time-delay compensated photoacoustic signal.

10. A dynamic sound velocity adaptive ultrasound-photoacoustic dual-modality imaging system, the system using a dynamic sound velocity adaptive ultrasound-photoacoustic dual-modality imaging method according to any one of claims 1 to 9, characterized in that: The system includes an input device, a processor, an output device and a memory, wherein the input device, the processor, the output device and the memory are connected to each other, wherein the memory is used to store a computer program, the computer program includes program instructions, and the processor is configured to call the program instructions.

Images