A dynamic acoustic velocity adaptive ultrasonic photoacoustic dual-mode imaging method and system

Abstract

The present application relates to the field of sound velocity, photoacoustic and ultrasonic imaging, and particularly relates to a dynamic sound velocity adaptive ultrasonic photoacoustic dual-mode imaging method and system. The method comprises the following steps: obtaining ultrasonic signals and photoacoustic signals; reconstructing a sound velocity distribution map according to the ultrasonic signals; reconstructing a relevant time delay map based on the sound velocity distribution map; and reconstructing an ultrasonic image and a photoacoustic image based on the relevant time delay map. The present application solves the problems of limited application range, inconvenient operation, high cost and low resolution of traditional sound velocity correction methods; the sound velocity correction algorithm adopted has high resolution, is suitable for various transducers such as linear array, convex array, ring array and sphere, and is widely applied to most parts of the human body; can accurately distinguish cancerous tissue from normal tissue, muscle from fat, etc.; is not affected by light, has high sound velocity resolution and signal-to-noise ratio, and supports seamless correction and registration of ultrasonic and photoacoustic dual-mode imaging, promoting the clinical application and development of ultrasonic photoacoustic dual-mode imaging.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of acoustic velocity, photoacoustic and ultrasonic imaging, in particular to a dynamic acoustic velocity adaptive ultrasonic photoacoustic dual-modality imaging method and system. BACKGROUND

[0002] Photoacoustic imaging (PA) has been increasingly valued in the field of medical imaging due to its high molecular and functional contrast and high resolution. Meanwhile, ultrasonic imaging (US) plays an important role in clinical diagnosis due to its rich anatomical information, low cost, portability, high biological safety and strong penetration. At present, seamless combination of photoacoustic imaging and ultrasonic imaging can obtain joint registration images with complementary contrast by using a common ultrasonic transducer and data acquisition system, which provides more accurate information for tumor diagnosis and staging, intraoperative navigation, etc. However, due to the complex structure of the human body, there are significant differences in acoustic velocity of different tissues and different parts of the same tissue. Traditional photoacoustic and ultrasonic imaging techniques mostly perform image reconstruction based on constant acoustic velocity, which leads to distorted reconstructed images and affects the clinical application effect.

[0003] In order to solve the above problems, a variety of acoustic velocity correction algorithms have been developed. For example, the transmission type ultrasonic tomography acoustic velocity correction method based on ring-shaped ultrasonic transducer can reconstruct the acoustic velocity distribution for correction, but the iterative calculation is time-consuming and the dual-speed method has low resolution, and is only suitable for acoustically transparent tissues such as breast, which is inconvenient to operate and has high hardware cost. Although the compressed sensing method can compensate the acoustic velocity of cortical bone ultrasonic imaging, it is only suitable for regular medium models with large difference in multi-layer acoustic velocity, has low lateral resolution and limited application range. The frequency domain analysis method compensates the acoustic velocity of photoacoustic image, but is easily affected by uneven illumination and low signal-to-noise ratio. The method of reconstructing acoustic velocity distribution based on prior information (such as CT or MRI) is theoretically feasible, but the reconstructed acoustic velocity map has large deviation, is not easy to register and has high cost, which is not conducive to clinical transformation.

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

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

[0006] In a first aspect, the present application provides a dynamic sound speed adaptive ultrasonic photoacoustic dual-mode imaging method, comprising the following steps: obtaining ultrasonic signals and photoacoustic signals; reconstructing a sound speed distribution map according to the ultrasonic signals; reconstructing a correlation time delay map based on the sound speed distribution map; and reconstructing an ultrasonic image and a photoacoustic image based on the correlation time delay map. The present application utilizes the complementary advantages of ultrasonic signals and photoacoustic signals in imaging to improve the imaging quality; the sound speed distribution map reconstructed according to the ultrasonic signals can accurately reflect the sound speed changes in the tissue, and the tissue sound speed as a new contrast provides more reference information for disease diagnosis; the correlation time delay map further reconstructed based on the sound speed distribution map can accurately capture the time difference of signal propagation and enhance the spatial resolution of the image; the ultrasonic image and the photoacoustic image reconstructed according to the correlation time delay map remove the propagation speed error artifacts and have more anatomical details, thereby providing strong visual support for early detection and precise treatment of diseases.

[0007] Optionally, the obtaining of the ultrasonic signals and the photoacoustic signals comprises: exciting a measured tissue by using different angle plane waves generated by an ultrasonic transducer to generate echo signals, the echo signals being received by the ultrasonic transducer, the ultrasonic transducer being used for receiving ultrasonic signals and photoacoustic signals, and including a linear array, a convex array, a ring array and a spherical transducer; performing signal acquisition on the echo signals received by the ultrasonic transducer by using an ultrasonic acquisition system to obtain acquired ultrasonic signals; triggering a pulsed laser by using the ultrasonic acquisition system based on the ultrasonic signals to emit pulsed laser, the pulsed laser being used for irradiating the measured tissue to generate photoacoustic signals, the photoacoustic signals being received by the ultrasonic transducer; and performing signal acquisition on the photoacoustic signals received by the ultrasonic transducer by using the ultrasonic acquisition system to obtain acquired photoacoustic signals. The present application excites the measured tissue by using different angle plane waves generated by the ultrasonic transducer to obtain the internal structure information of the tissue in all directions, and the reception of the echo signals further ensures the integrity of the information; the ultrasonic acquisition system is used to accurately acquire the echo signals, thereby effectively improving the signal-to-noise ratio and the resolution of the ultrasonic signals and providing a high-quality data basis for subsequent image processing; the ultrasonic signals are used to trigger the pulsed laser to emit pulsed laser, thereby not only ensuring the time synchronization of the photoacoustic signals and the ultrasonic signals, but also improving the imaging efficiency.

[0008] Optionally, reconstructing the sound velocity distribution map based on the ultrasonic signal includes: setting an assumed average sound velocity for each emission angle in the 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 between the assumed average sound velocity and the actual sound velocity; obtaining a relative time delay error based on the relative phase difference obtained by the same pixel under different propagation paths; constructing a sound velocity reconstruction model based on the relative time delay error and the time delay error; and obtaining the sound velocity distribution map through the sound velocity reconstruction model. This invention precisely quantifies time delay error by pre-setting an assumed average sound velocity and identifying its inconsistency with the actual sound velocity distribution, providing a crucial foundation for subsequent calculations. By utilizing the relative phase difference of the same pixel under different propagation paths, it effectively captures the phase change caused by sound velocity variations, enhancing the sensitivity of sound velocity distribution reconstruction. By obtaining the relative time delay error through the relative phase difference and establishing a sound velocity reconstruction model accordingly, it accurately reflects the true distribution of sound velocity in tissues, providing precise sound velocity parameters for subsequent image reconstruction, significantly improving imaging resolution and signal-to-noise ratio, and providing information on the true sound velocity distribution within tissues for medical diagnosis.

[0009] Optionally, the relative phase difference satisfies the following expression:

[0010]

[0011] in, Indicates the first The first angle and the second The relative phase difference in the ultrasound image corresponding to each angle. The frequency of the ultrasonic signal. Indicates the first The first angle and the second The relative time delay error in the ultrasound image corresponding to each angle. The difference between the actual speed of sound and the estimated speed of sound. The sound velocity reconstruction model is a finite set of pixels within a predefined imaging region, satisfying the following expression:

[0012]

[0013] in, It is the reciprocal of the actual speed of sound. This is due to time delay error. The application provides a scientific basis for quantifying the unevenness of the sound velocity distribution through the mathematical expression of the relative phase difference; the reciprocal of the real sound velocity is calculated through the sound velocity reconstruction model, which provides accurate algorithm support for the construction of the sound velocity distribution map; through the above two expressions, the resolution and signal-to-noise ratio of the sound velocity reconstruction are improved, and the resolving power of the imaging technology for complex tissue structures is enhanced.

[0014] Optionally, the reconstructing the relevant time delay map based on the sound velocity distribution map comprises: constructing a time delay model of different array elements and different ultrasonic emission angles based on the sound velocity distribution map by using a multi-module fast marching method, the time delay model being used to describe the propagation mode of ultrasonic waves in the sound velocity uneven tissue; and reconstructing the relevant time delay map based on the time delay model.

[0015] Optionally, the time delay model satisfies the following expression:

[0016]

[0017] wherein, is the sound velocity at the reconstruction pixel point is the time delay between different array elements, is the sound velocity at the reconstruction pixel point The application accurately describes the time delay distribution of ultrasonic waves in the tissue through the relationship between the gradient vector and the reciprocal of the sound velocity, and provides a scientific mathematical basis for the reconstruction of the relevant time delay map; the model fully considers the unevenness of the sound velocity in space, so that the reconstructed time delay map can truly reflect the propagation characteristics of ultrasonic waves in complex tissues, and the resolution and signal-to-noise ratio of the imaging are improved; the application of the model not only optimizes the imaging process, but also enhances the resolving power of the imaging technology for the tissue structure, and provides more detailed time dimension information for medical diagnosis.

[0018] Optionally, the reconstructing the ultrasound image and the photoacoustic image based on the correlation time delay map comprises: reconstructing the ultrasound image based on the correlation time delay map; and reconstructing the photoacoustic image based on the correlation time delay map. The present application efficiently processes a large amount of data by the multi-module fast marching method, and quickly and accurately reconstructs the ultrasound image and the photoacoustic image, thereby significantly improving the imaging speed; the image reconstructed based on the correlation time delay map has high spatial resolution and contrast, and clearly shows the microstructure and functional information of the tissue, thereby helping to improve the early detection rate and diagnostic accuracy of clinical diseases.

[0019] Optionally, the reconstructing the ultrasound image based on the correlation time delay map comprises: performing time delay compensation on the ultrasound signal based on the correlation time delay map; and reconstructing the ultrasound image after correction of the sound speed by the time delay compensation. The present application effectively solves the time delay problem of the ultrasound signal in the propagation process due to the non-uniform sound speed, thereby improving the signal-to-noise ratio and resolution of the ultrasound image; by applying the multi-module fast marching method, the time delay compensation process can be efficiently and accurately completed, thereby greatly shortening the image reconstruction time and improving the imaging efficiency; by the time delay compensation processing, the reconstructed ultrasound image more truly reflects the structure and functional information of the tissue.

[0020] Optionally, the reconstructing the photoacoustic image based on the correlation time delay map comprises: correcting the sound speed and the time delay in the non-uniform tissue based on the correlation time delay map; and reconstructing the photoacoustic image after correction of the sound speed and the time delay. The present application significantly improves the resolution and signal-to-noise ratio of the photoacoustic image by accurately correcting the sound speed and the time delay in the non-uniform tissue, so that the image more truly reflects the structure and functional information of the tissue; by applying the multi-module fast marching method, the correction process can be efficiently and accurately completed, thereby greatly shortening the image reconstruction time and improving the imaging efficiency.

[0021] In a second aspect, the present application provides a dynamic sound speed adaptive ultrasonic photoacoustic dual-modality imaging system, which comprises an input device, a processor, an output device and a memory, and the input device, the processor, the output device and the memory are connected with each other, wherein the memory is used for storing a computer program, the computer program comprises program instructions, the processor is configured to call the program instructions, and the system uses the dynamic sound speed adaptive ultrasonic photoacoustic dual-modality imaging method. The system has the following three creative effects: first, by integrating advanced signal processing algorithms and adaptive technology, the sound speed change can be accurately captured, and the image reconstruction sound speed parameters at different positions can be adjusted in real time, thereby effectively avoiding the image distortion problem caused by uneven sound speed, significantly improving the accuracy and reliability of ultrasonic photoacoustic dual-modality imaging, and providing more accurate information support for clinical diagnosis and treatment; second, by optimizing the hardware design and algorithm process, the overall cost is reduced while ensuring the imaging quality, so that the technology is more easily popularized and applied in the clinical environment; third, by adjusting the system parameters and configurations, various complex imaging scenes can be flexibly coped with, including tissue imaging of different parts and different depths, so that the system has potential application value in tumor diagnosis and staging, intraoperative navigation and other fields, and provides more comprehensive support for clinical diagnosis and treatment.

[0022] Compared with the prior art, the beneficial effects of the present application include: the use of the creative sound speed correction algorithm breaks through the limitations of traditional technology, is suitable for linear array, convex array and ring array and other transducers, is widely applicable to most parts of the human body, does not require complex operation, and greatly reduces the discomfort of patients and the burden of operators. At the same time, it supports multiple transducer types, enhances the flexibility and applicability of the system. It has high-resolution imaging capability, can accurately distinguish tissues with small sound speed differences, and improves the accuracy and timeliness of diagnosis. It is not affected by light, has high sound speed resolution and signal-to-noise ratio, and has stable and reliable imaging quality. Seamless integration and registration of ultrasonic and photoacoustic dual-modality imaging are realized, rich diagnostic information is provided, no additional registration steps are required, and the workflow is simplified. In addition, the hardware cost is reduced, the cost performance is improved, which is conducive to clinical wide application, improves patient comfort and doctor diagnosis efficiency, and provides a new means for clinical diagnosis and treatment. BRIEF DESCRIPTION OF DRAWINGS

[0023] Figure 1 Flowchart of the dynamic sound speed adaptive ultrasonic photoacoustic dual-modality imaging method of the embodiment of the present application;

[0024] Figure 2 Flowchart of excitation and collection of ultrasonic signals and photoacoustic signals of the embodiment of the present application;

[0025] Figure 3An image flow chart of a dynamic sound speed adaptive ultrasonic photoacoustic dual-modality imaging algorithm of an embodiment of the present application;

[0026] Figure 4 A sound speed distribution map corresponding to a simulation model simulating different tissue distributions of a human arm of an embodiment of the present application;

[0027] Figure 5 A result comparison map of photoacoustic images obtained by different imaging methods of an embodiment of the present application;

[0028] Figure 6 A half-wave full-width value comparison map of photoacoustic images obtained by different imaging methods of an embodiment of the present application;

[0029] Figure 7 A system performance verification map of an ultrasonic photoacoustic dual-modality imaging experiment based on an ex vivo tissue of an embodiment of the present application;

[0030] Figure 8 A distortion result map and a result map after correction of distortion of an embodiment of the present application;

[0031] Figure 9 A histogram of pencil core diameters at different position points of different imaging methods of an embodiment of the present application;

[0032] Figure 10 A structural schematic diagram of a dynamic sound speed adaptive ultrasonic photoacoustic dual-modality imaging system of an embodiment of the present application. DETAILED DESCRIPTION

[0033] Specific embodiments of the present application will be described in detail below, it should be noted that the embodiments described herein are only used for illustration and do not limit the present application. In the following description, a large number of specific details are set forth in order to provide a thorough understanding of the present application. However, it is obvious to those skilled in the art that the present application does not have to be implemented with these specific details. In other instances, well-known circuits, software or methods have not been specifically described in order to avoid obscuring the present application.

[0034] Throughout the specification, the mention of "one embodiment", "an embodiment", "one example" or "an example" means that a particular feature, structure or characteristic described in connection with the embodiment or example is included in at least one embodiment of the present application. Therefore, the phrases "in one embodiment", "in an embodiment", "one example" or "an example" appearing throughout the specification are not necessarily all referring to the same embodiment or example. In addition, specific features, structures or characteristics can be combined in any appropriate combination and / or subcombination in one or more embodiments or examples. In addition, those skilled in the art should understand that the diagrams provided herein are for illustrative purposes only and the diagrams are not necessarily drawn to scale.

[0035] Referring to Figure 1 Embodiments of the present application provide a dynamic sound speed adaptive ultrasonic photoacoustic dual-mode imaging method, which comprises the following steps:

[0036] S1. Obtain an ultrasonic signal and a photoacoustic signal.

[0037] S1 further comprises the following steps:

[0038] S11. Obtain an ultrasonic signal.

[0039] Referring to Figure 2 In one embodiment, an ultrasonic transducer and an ultrasonic acquisition system are used to realize excitation and acquisition of the ultrasonic signal.

[0040] Specifically, first, the ultrasonic transducer is connected to the ultrasonic acquisition system.

[0041] Further, different transmission time delays of each transmitting element of the ultrasonic transducer are set by programming to form plane waves of different angles and transmit them to the measured tissue.

[0042] Further, the measured tissue generates corresponding echo signals, which are received by the ultrasonic transducer.

[0043] Further, the ultrasonic acquisition system collects the echo signals received by the ultrasonic transducer to obtain the ultrasonic signal. The ultrasonic transducer includes a linear array, a convex array, a semi-ring array, a ring array, and a spherical ultrasonic transducer.

[0044] S12. Obtain a photoacoustic signal.

[0045] In one embodiment, after the ultrasonic signal is collected in step S11, the ultrasonic acquisition system triggers a pulsed laser to emit pulsed laser.

[0046] Further, the pulsed laser irradiates the measured tissue to generate a photoacoustic signal.

[0047] Further, the ultrasonic acquisition system collects the photoacoustic signal through the ultrasonic transducer. The ultrasonic transducer is the same as the ultrasonic transducer mentioned in step S11.

[0048] S2. Reconstruct a sound speed distribution map according to the ultrasonic signal.

[0049] In one embodiment, referring to Figure 3 , Figure 3 The first three steps in the above method are used to obtain a sound speed distribution image by using a sound speed reconstruction algorithm.

[0050] Specifically, Figure 3The precondition of step 1 is that conventional ultrasound imaging usually adopts a delay-and-sum (DAS) algorithm for image reconstruction, and the core of the algorithm is to compensate and solve the propagation delay of ultrasound. Strictly speaking, the calculation of the propagation delay needs to know the distribution of the speed-of-sound (SOS) of the region through which the transmitting element and the receiving element pass to the target pixel point The calculation expression of the propagation delay is as follows:

[0051]

[0052] wherein, is the actual propagation delay of the ultrasound signal, is a limited number of pixel point sets of a predefined imaging region, is a propagation path of a specific pixel point, is a real speed of sound. Usually, the distribution of the real speed of sound cannot be accurately obtained, so the estimated value thereof, for example, the average speed of soft tissue (1540 m / s), is often used for related image reconstruction.

[0053] Further, based on the above precondition, in Figure 3 step 1, the image reconstruction is performed according to the assumed average speed of sound (1540 m / s) for each transmission angle in ultrasound imaging. Due to the inconsistency between the assumed average speed of sound during reconstruction and the real speed of sound distribution of the tissue, the actual propagation delay is inconsistent with the calculated propagation delay, thereby producing a time delay error, which satisfies the following expression:

[0054]

[0055] wherein, is the time delay error, is the actual propagation delay of the ultrasound signal, is the calculated propagation delay, is the estimated speed of sound, is the reciprocal of the real speed of sound, is the reciprocal of the estimated speed of sound, is the difference between the real speed of sound and the estimated speed of sound, is the real speed of sound, is the propagation path of a specific pixel point. Due to the existence of the time delay error, phase distortion occurs in the image reconstruction process, and 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 point under different propagation paths can be calculated, as shown in step 2 in Figure 3 the phase shift diagram obtained by step 2 is used to reflect the phase distortion.

[0056] Further, a relationship between the relative phase difference and the relative time delay error is established.

[0057] Specifically, the relationship between the relative phase difference and the relative time delay error is as follows:

[0058]

[0059] wherein, denotes the relative phase difference in the ultrasound image corresponding to the th angle and the th angle, is the ultrasound signal frequency, denotes the relative time delay error in the ultrasound image corresponding to the th angle and the th angle, is the difference between the true sound speed and the estimated sound speed, is a finite number of pixel point sets of the predefined imaging region. The relationship describes the forward problem based on the spatial domain method.

[0060] Further, a sound speed reconstruction model is constructed, which reconstructs the sound speed according to the matrix-form forward problem, as shown in step 3 in Figure 3 , and the expression satisfied by the sound speed reconstruction model is as follows:

[0061]

[0062] wherein, is the reciprocal of the true sound speed, is the time delay error, is the propagation path of different target pixel points relative to different transmitting and receiving elements.

[0063] Further, according to the sound speed reconstruction model, a sound speed distribution map is reconstructed.

[0064] S3. Based on the sound speed distribution map, a relevant time delay map is reconstructed.

[0065] In one embodiment, in order to utilize the obtained sound speed distribution map to perform sound speed correction on the photoacoustic image and the ultrasound image, in step 4 in Figure 3 , a series of time delay maps based on the sound speed map are calculated using the multi-module fast marching method (MSFM). Based on the MSFM method, a time delay model between different elements is constructed, which is used to describe the propagation manner of the ultrasound wave in the sound speed inhomogeneous tissue: the time delay model satisfies the following expression:

[0066]

[0067] wherein, is the reconstructed pixel point relative to the time delay between different array elements, is the reconstructed pixel point at the sound speed.

[0068] Further, the correlation time delay map is reconstructed by using the time delay expression.

[0069] S4. An ultrasound image and a photoacoustic image are reconstructed by using the correlation time delay map.

[0070] wherein, S4 further comprises the following steps:

[0071] S41. An ultrasound image is reconstructed by using the correlation time delay map.

[0072] In one embodiment, based on the correlation time delay map obtained in step S3, a conventional composite plane wave (CPW) is used to reconstruct the ultrasound image. The principle of image reconstruction is to perform a delay coherent summation on the signal received by the linear array ultrasonic transducer. The ultrasound imaging is divided into two parts of receiving and transmitting, and the formula is as follows:

[0073]

[0074] wherein, is the total ultrasound signal at the target pixel point , is the total ultrasound signal at the target pixel point is the ultrasound signal received by the th receiving array element at the time , is the time, is the total channel number of the photoacoustic signal received by the receiving array element, is the relative time delay at the target pixel point is the transmitting time delay at the target pixel point is the receiving time delay at the target pixel point, and the transmitting time delay and the receiving time delay satisfy the following expressions respectively:

[0075]

[0076] wherein, is the different deflection angles, is the relative position of the different receiving array elements, is the estimated sound speed.

[0077] ​​​​It is important to note that this image reconstruction theory only applies to tissues with uniform sound velocity and known tissue sound velocity. For tissues with non-uniform sound velocity and unknown tissue sound velocity, it will cause severe shape distortion and dimensional inaccuracies in the reconstruction results. Therefore, sound velocity correction is necessary. The MSFM method is used to compensate for the time delay of both the transmitting and receiving portions of the ultrasound signal. The relevant expressions are as follows:

[0078]

[0079] in, To perform time delay compensation using the MSFM method at the target pixel The relative time delay at that location To perform time delay compensation using the MSFM method at the target pixel Launch time delay at the location, To perform time delay compensation using the MSFM method at the target pixel The reception time delay at the location, For time, This refers to the total number of channels of photoacoustic signals received by the receiving array element. To perform time delay compensation using the MSFM method, the first... Each receiving element in The ultrasound signals received at all times To perform time delay compensation using the MSFM method at the target pixel Total ultrasound signal at the location.

[0080] S42. Reconstruct the photoacoustic image using the relevant time delay map.

[0081] In one embodiment, a theory is given on how to correct photoacoustic images based on Delay Reconstruction Algorithm (DAS) and Delay Multiply Reconstruction Algorithm (DMAS) when reconstructing photoacoustic images.

[0082] Specifically, firstly, based on the photoacoustic imaging principle, the signal received by the linear array ultrasonic transducer is coherently summed with time delay, and the formula is expressed as:

[0083]

[0084] in, For the first Each receiving element in The photoacoustic signals received at all times, This refers to the total number of channels of photoacoustic signals received by the receiving array element. To receive transducer array elements to the target pixel Time delay at the point, For time, For target pixel The total photoacoustic signal obtained based on the DAS reconstruction algorithm, For target pixel The total photoacoustic signal obtained based on the DMAS reconstruction algorithm, For the first Each receiving element in The photoacoustic signals received at all times, For the first Each receiving element in The photoacoustic signals received at all times.

[0085] Typically, the sound velocity distribution within tissue cannot be known in advance, so the average sound velocity of soft tissue (1540 m / s) is often chosen as the reconstructed sound velocity for photoacoustic image reconstruction. However, choosing a constant sound velocity is only suitable for imaging tissues with uniform sound velocity, which is inconsistent with reality and will lead to a severe deterioration in the image quality of tissues with non-uniform sound velocity. Therefore, it is necessary to perform relevant sound velocity and time delay corrections based on the CUTE and MSFM methods from the previous theory, as shown in the following formulas:

[0086]

[0087] in, This refers to the time delay of the corresponding receiving array element relative to each pixel in the imaging region, obtained based on the sound velocity map and using the MSFM method. For target pixel The total photoacoustic signal obtained based on the DAS reconstruction algorithm and MSFM method, For the first Each receiving element in The photoacoustic signals received at all times, This refers to 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 For the first Each receiving element in The photoacoustic signals received at all times, For the first Each receiving element in The photoacoustic signals received at all times.

[0088] In one specific embodiment, a numerical model was established using the K-WAVE toolbox in MATLAB for acoustic simulation to verify the feasibility of the imaging algorithm of the present invention. The relevant parameters in the simulation process remained consistent with the actual physical parameters.

[0089] Specifically, in photoacoustic bimodal imaging of the human arm, the difference in sound velocity between the fat and muscle layers significantly reduces imaging accuracy. Specifically, the sound velocity in adipose tissue is generally lower than that in muscle tissue. This difference in acoustic properties causes distortion of the sound wave propagation path, leading to signal attenuation and scattering. This not only obscures the details of vascular structures, making accurate identification and localization of blood vessels difficult, but also interferes with the accurate measurement of the size and thickness of the fat layer, causing errors in fat distribution assessment. Therefore, the sound velocity difference has become a critical problem that urgently needs to be solved in photoacoustic bimodal imaging.

[0090] Therefore, this invention provides a set of simulation models that mimic the distribution of different tissues in a human arm, and the sound velocity distribution diagram is as follows. Figure 4 As shown in (a), the upper layer of the sound velocity diagram simulates the propagation path (sound velocity: 1540 m / s, density: 1000 m / s), the middle layer simulates fat (sound velocity: 1430 m / s, density: 960 m / s) with a thickness of 10 mm, and the lower layer simulates muscle (sound velocity: 1560 m / s, density: 1100 m / s). For photoacoustic imaging simulation, this invention sets up a 5x5 matrix of absorption points, with a row and column spacing of 5 mm and a diameter of 0.5 mm. For ultrasonic imaging simulation, plane waves at different angles are generated by setting different time delays for different emission array elements to perform composite plane wave imaging. The sampling frequency in the simulation is 62.5 MHz to ensure numerical stability in both ultrasonic and photoacoustic simulations; the computational grid consists of 1000×1000 pixels with a pixel size of 0.05 mm. The specific process is as follows:

[0091] First, this invention reconstructs the sound velocity distribution map based on ultrasonic simulation data, and the results are shown in the appendix. Figure 4 As shown in (b), the reconstruction results can not only distinguish the three different sound velocities well, but also the average sound velocity of the corresponding region has a very small error compared with the preset sound velocity.

[0092] Furthermore, ultrasound reconstruction was performed, demonstrating both the traditional ultrasound imaging method based on a constant sound velocity of 1540 m / s and the sound velocity correction imaging method based on sound velocity maps of this invention. It can be seen that the thickness of the fat layer in the ultrasound image reconstructed by the method of this invention is closer to the actual fat layer thickness compared to the thickness of the fat layer in the ultrasound image reconstructed based on a constant sound velocity. Figure 4 As shown in (c)(d). Figure 5 (a)(b)(c)(d) respectively demonstrate the photoacoustic image comparison results of the traditional delay summation method with a preset sound velocity of 1525 m / s, the delay summation method based on sound velocity map correction, the traditional delay multiplication method with a preset sound velocity of 1525 m / s, and the photoacoustic image comparison results of the proposed method based on sound velocity map correction. Visually, our proposed algorithm achieves the best reconstruction effect for each sound source absorption point, such as...Figure 5 As shown in (e)(f)(g)(h). We also demonstrate the highest resolution of our proposed algorithm by analyzing its half-wavelength full width (FWHM). The FWHM values ​​for different reconstruction methods are: delay summation vs. delay multiplication vs. sound velocity correction delay summation vs. sound velocity correction delay multiplication = 1.51mm vs 0.85mm vs 1.04mm vs 0.72mm. Among them, our method (sound velocity correction delay multiplication) is closest to the true value (0.5mm), as shown in (e)(f)(g)(h). Figure 6 As shown.

[0093] In another specific embodiment, the effectiveness of the proposed dynamic sound velocity adaptive ultrasound-photoacoustic dual-modal imaging algorithm is further verified through an ultrasound-photoacoustic dual-modal imaging experiment based on ex vivo tissue.

[0094] Specifically, first, the degassed chicken breast tissue is placed in a cube-shaped container.

[0095] Furthermore, the degassed adipose tissue is stacked on top of the chicken breast tissue.

[0096] Furthermore, a solid coupling layer with a known sound velocity was placed above the adipose tissue. The purpose of this solid coupling layer was to remove the system from the water bath environment, greatly increasing the system's applicability. The container material used in the experiment was polymethyl methacrylate (PMMA) with a wall thickness of 3 mm. One pencil lead (diameter: 0.5 mm) was placed between the chicken breast and the fat, and another pencil lead (diameter: 0.5 mm) was placed between the fat layer and the solid coupling layer, as shown. Figure 7 As shown in (a).

[0097] Furthermore, photoacoustic imaging was performed using pulsed laser light emitted from a pulsed laser. According to literature review and the phantom formulation, the sound velocity of the uppermost solid coupling layer (composed of agar-glycerol) is 1560 m / s, the middle layer of fat has a sound velocity of 1430 m / s, and the lowermost layer of chicken breast tissue has a sound velocity of 1560 m / s. The sound velocity map reconstructed using pulse-echo acoustic reconstruction can distinguish not only the three types of tissue but also two different types of adipose tissue, such as… Figure 7 As shown in (b), it is worth explaining that the fat in this ultrasound image appears to have two layers. This is because during the fabrication of the ex vivo sample, there are two types of fat (dense and loose), which can be clearly demarcated in the ultrasound image, as shown in the image. Figure 7 As shown in (c). For ultrasound imaging, by comparing the average sound velocity reconstruction and the sound velocity map-based reconstruction, it was found that the sound velocity-corrected ultrasound image showed a smaller fat layer thickness, which is closer to the true value, such as... Figure 7 (c) and Figure 7 As shown in (d).

[0098] Furthermore, comparing the results of different photoacoustic reconstruction algorithms revealed that, compared to the time-delay summation and time-delay multiplication after sound speed correction, the shape of the pencil lead on the lower left side of the constant-speed time-delay summation and time-delay multiplication had become distorted, such as... Figure 8 As shown in (e)(g), the distortion artifacts caused by incorrect sound velocity were corrected by the method of sound velocity map reconstruction, such as... Figure 8 As shown in (f)(h). By analyzing its half-wavelength full width (FWHM), it can be found that the algorithm proposed in this invention has the highest resolution, such as... Figure 9 As shown, the experimental results based on ex vivo tissues are consistent with the simulation results, providing strong support for the applicability of the algorithm proposed in this invention to the human body.

[0099] Please see Figure 10 , Figure 10 This is a schematic diagram of the structure of a dynamic sound velocity adaptive ultrasound-photoacoustic dual-modal imaging system according to an embodiment of the present invention. The system includes an input device, a processor, an output device, and a memory. The input device, processor, output device, and memory are interconnected. The memory stores a computer program, which includes program instructions. The processor is configured to call the program instructions. The system uses the described dynamic sound velocity adaptive ultrasound-photoacoustic dual-modal imaging method.

[0100] In this embodiment, the input device includes an ultrasonic transducer, a pulsed laser, and a control unit;

[0101] Specifically, the ultrasonic transducer receives control signals from the system and emits plane waves at different angles to the tissue under test according to a preset emission time delay. Simultaneously, it acts as a receiver, acquiring the ultrasonic echo signals generated by the tissue under test. The pulsed laser receives trigger signals from the system and emits pulsed laser light to irradiate the tissue under test, thereby exciting photoacoustic signals. The control unit includes a keyboard and a touchscreen, allowing users to input control commands, such as setting the emission time delay of the ultrasonic transducer, triggering the pulsed laser, and selecting imaging parameters.

[0102] The processor includes a central processing unit for receiving signals and data from input devices, executing imaging algorithms, and reconstructing ultrasound and photoacoustic images; the signals and data include signals acquired by the ultrasound transducer and instruction data input by the user through the control unit; the imaging algorithms include the CUTE method and the MSFM method.

[0103] The output device includes a display for displaying reconstructed ultrasound images, photoacoustic images, and sound velocity distribution maps.

[0104] The memory uses a high-speed solid-state drive, which features fast read and write speeds, large capacity, and high reliability. It is mainly used to store data input from input devices and the result data after processing by the processor, and can meet the needs of storing large amounts of data.

[0105] In summary, this invention overcomes the limitations of traditional technologies, is widely applicable to most parts of the human body, requires no complex operations, and reduces patient discomfort and operator burden. Simultaneously, it supports multiple transducer types, enhancing the system's flexibility and applicability. High-resolution imaging capabilities can accurately distinguish tissues with minute differences in sound velocity, improving diagnostic accuracy and timeliness. Unaffected by lighting conditions, it boasts high sound velocity resolution and signal-to-noise ratio, ensuring stable and reliable imaging quality. Seamless integration and registration of ultrasound and photoacoustic dual-modal imaging provide rich diagnostic information without the need for additional registration steps, simplifying the workflow. Furthermore, it reduces hardware costs, improves cost-effectiveness, facilitates widespread clinical application, enhances patient comfort and physician diagnostic efficiency, and provides new tools for clinical diagnosis and treatment.

[0106] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention, and they should all be covered within the scope of the claims and specification of the present invention.

Claims

1. A dynamic sound velocity adaptive ultrasonic-photoacoustic dual-modal imaging method, characterized in that, The method includes the following steps: Acquiring ultrasonic and photoacoustic signals; Based on the ultrasonic signal, a sound velocity distribution map is reconstructed, including: An assumed average sound velocity of 1540 m / s is set for each emission angle in ultrasound imaging, and this assumed average sound velocity is inconsistent with the actual sound velocity distribution. The time delay error is obtained based on the inconsistent distribution between the assumed average sound speed and the actual sound speed. The relative time delay error is obtained based on the relative phase difference of the same pixel under different propagation paths. The relative phase difference satisfies the following expression: in, Indicates the first The first angle and the second The relative phase difference in the ultrasound image corresponding to each angle. The frequency of the ultrasonic signal. Indicates the first The first angle and the second The relative time delay error in the ultrasound image corresponding to each angle. The difference between the actual speed of sound and the estimated speed of sound. Given a finite set of pixels within a predefined imaging region; the sound velocity reconstruction model satisfies the following expression: in, It is the reciprocal of the actual speed of sound. This is due to time delay error. The propagation paths of different target pixels relative to different transmit and receive array elements; Based on the relative time delay error and the time delay error, a sound speed reconstruction model is constructed; The sound velocity distribution map is obtained through the sound velocity reconstruction model. Based on the sound velocity distribution map, reconstruct the relevant time delay map; Based on the aforementioned time delay map, the ultrasound image and photoacoustic image are reconstructed.

2. The dynamic sound velocity adaptive ultrasonic-photoacoustic dual-modal imaging method according to claim 1, characterized in that, The acquisition of ultrasonic and photoacoustic signals includes: The test tissue is excited by plane waves of different angles generated by an ultrasonic transducer to generate echo signals. The echo signals are received by the ultrasonic transducer, which is used to receive ultrasonic and photoacoustic signals, including linear array, convex array, ring array and spherical transducer. An ultrasonic acquisition system is used to acquire the echo signal received by the ultrasonic transducer to obtain the acquired ultrasonic signal. Based on the ultrasound signal, the ultrasound acquisition system triggers a pulsed laser to emit a pulsed laser. The pulsed laser is used to irradiate the tissue under test and generate a photoacoustic signal, which is received by the ultrasound 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 dynamic sound velocity adaptive ultrasonic-photoacoustic dual-modal imaging method according to claim 1, characterized in that, The reconstruction of the relevant time delay map based on the sound velocity distribution map includes: Based on the sound velocity distribution map, a time delay model for different emission angles and array elements is constructed using the multi-module fast travel method. The time delay model is used to describe the propagation mode of ultrasonic waves in tissues with non-uniform sound velocity. Based on the time delay model, the relevant time delay map is reconstructed.

4. The dynamic sound velocity adaptive ultrasonic-photoacoustic dual-modal imaging method according to claim 3, characterized in that, The time delay model satisfies the following expression: in, To reconstruct pixels Compared to the time delay between different array elements, To reconstruct pixels The speed of sound at that location.

5. The dynamic sound velocity adaptive ultrasonic-photoacoustic dual-modal imaging method according to claim 1, characterized in that, The reconstruction of the ultrasound image and photoacoustic image based on the relevant time delay map includes: Based on the aforementioned time delay map, reconstruct the ultrasound image; Based on the aforementioned time delay map, the photoacoustic image is reconstructed.

6. The dynamic sound velocity adaptive ultrasonic-photoacoustic dual-modal imaging method according to claim 5, characterized in that, The reconstruction of the ultrasound image based on the relevant time delay map includes: Based on the aforementioned time delay diagram, time delay compensation is calculated for the ultrasonic signal to obtain a time delay compensated ultrasonic signal. An ultrasound image is reconstructed using the time-delay-compensated ultrasound signal.

7. The dynamic sound velocity adaptive ultrasonic-photoacoustic dual-modal imaging method according to claim 5, characterized in that, The reconstruction of the photoacoustic image based on the relevant time delay map includes: Based on the aforementioned time delay diagram, time delay compensation is calculated for the photoacoustic signal to obtain a time delay compensated photoacoustic signal. The photoacoustic image is reconstructed by compensating the time delay photoacoustic signal.

8. A dynamic sound velocity adaptive ultrasound-photoacoustic dual-modal imaging system, wherein the system uses the dynamic sound velocity adaptive ultrasound-photoacoustic dual-modal imaging method according to any one of claims 1 to 7, characterized in that, The system includes an input device, a processor, an output device, and a memory, which are interconnected. The memory stores a computer program, which includes program instructions, and the processor is configured to invoke the program instructions.

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