Photoacoustic temperature imaging method based on coherence factor weighted fusion

Abstract

The present invention discloses a photoacoustic temperature imaging method based on weighted fusion of coherence factors, and the method is as follows: step 1, hardware composition and configuration of a multi-bandwidth photoacoustic imaging system based on photoacoustic and ultrasonic dual modalities; step 2, preprocessing of ultrasonic modal signals; step 3, calculation of coherence factors and weighting of reconstructed images. The present invention demonstrates high-precision non-invasive temperature measurement capabilities, providing a more advanced non-invasive temperature monitoring method for photothermal treatment of tumors. The present invention integrates imaging, segmentation, temperature measurement, treatment and other functional modules, and weights the reconstructed image by coherence factors to remove high artifacts and multiple sidelobes in the FBP reconstructed image, significantly improving the resolution of temperature imaging, and showing significant advantages and huge application potential in the application of photothermal treatment. Assisted by a multimodal image fusion method, it is ensured that multimodal information of the target area can be obtained during the treatment process, providing staff with more intuitive visual feedback on the tumor status and improving the treatment effect.

Description

Technical Field

[0001] The present invention belongs to the technical field of photoacoustic / ultrasonic imaging, and relates to a photoacoustic temperature imaging method, and in particular to a photoacoustic temperature imaging method based on coherence factor weighted fusion. Background Art

[0002] Photothermal therapy, an emerging treatment method with the advantages of non-invasiveness and high selectivity, has attracted widespread attention in the field of tumor treatment. However, due to the lack of effective non-contact temperature measurement technology, accurate real-time measurement of the temperature and distribution of the target area is very difficult, which may cause damage to the target area and surrounding healthy tissue during treatment. Fortunately, the rapid development of photoacoustic image reconstruction technology, especially its application in image reconstruction and signal processing, has provided a new solution to this problem. Summary of the Invention

[0003] To overcome the lack of high-resolution non-invasive temperature imaging in existing photothermal therapy, this paper provides a photoacoustic temperature imaging method based on coherence factor weighted fusion. By introducing coherence factor weighting during image reconstruction, this method significantly improves the temperature imaging resolution during photothermal therapy, enhances temperature measurement accuracy to a certain extent, and reduces system hardware complexity, making it suitable for clinical use in tumor photothermal therapy.

[0004] The purpose of the present invention is achieved through the following technical solutions:

[0005] A photoacoustic temperature imaging method based on coherence factor weighted fusion includes the following steps:

[0006] Step 1. Hardware composition and configuration of the multi-bandwidth photoacoustic imaging system based on photoacoustic and ultrasound dual modalities:

[0007] The multi-bandwidth photoacoustic imaging system based on photoacoustic and ultrasonic dual modalities consists of a pulsed laser, a ring array ultrasonic transducer, a multi-channel data acquisition card, a central computer, and a main control board. The pulsed laser is used to emit pulsed light with a nanosecond pulse width to excite the light absorber in the target area and generate a photoacoustic signal. The ring array ultrasonic transducer is used to obtain ultrasonic and photoacoustic dual-modal signals (expressed as sound pressure signals). The multi-channel data acquisition card is used to perform digital-to-analog conversion on the ultrasonic and photoacoustic dual-modal signals received by the ring array transducer and transmit the processed data to the central computer for further analysis and processing. The main control board is used to match the operating timing of each system component after receiving commands from the central computer to ensure the normal operation of the system.

[0008] Step 2: Ultrasonic modal signal preprocessing:

[0009] Step 2.1: A pulsed laser emits short pulses of light that illuminate the tissue within the target imaging area, stimulating a photoacoustic signal. The intensity of the generated photoacoustic signal is related to the temperature of the target area and is specifically characterized by the following formula:

[0010] P(x,y;t)=A1+A2T(x,y;t)

[0011] Where P(x, y; t) represents the sound pressure value at the position (x, y) at time t, T(x, y; t) refers to the instantaneous temperature at the position (x, y) at time t, (x, y) is the Cartesian coordinate of the imaging position, with the origin at the center of the ring array, and A1 and A2 are linear coefficients.

[0012] Step 2.2: After receiving the imaging command from the central computer, the main control board triggers the pulsed laser to start emitting light pulses and simultaneously activates the ring array transducers to start receiving signals. Each ring array transducer receives the photoacoustic and ultrasound signals from the tumor target area. These signals are collected by a multi-channel data acquisition card and stored in the central computer.

[0013] Step 2.3: Preliminary preprocessing is performed on the signals collected by the multi-channel data acquisition card in the central computer to remove noise from the received signals and enhance the effective parts of the signals;

[0014] Step 2.4: Using a reconstruction algorithm, the preprocessed signal is reconstructed to generate preprocessed images of multiple ultrasound modalities and obtain the target area coordinates;

[0015] Step 3: Calculation of coherence factor and weighting of reconstructed image:

[0016] Step 3.1: Assignment of basic parameters and division of target area grid:

[0017] Assignment of basic parameters: specify the initial sound velocity, delay time of the array ultrasonic transducer, array radius, target area grid size and sampling frequency of the multi-channel data acquisition card in the program;

[0018] Target area grid division: Use the target area coordinates obtained in step 2.4 to divide the grid for photoacoustic image reconstruction. Take the center of the ring array as the coordinate origin, the corresponding coordinate is (0,0), assign the relative coordinate of the standard unit system to each grid point, and use the parametric equation of the circle according to the specified radius of the ring array ultrasonic transducer. Calculate the relative coordinates of each circular array ultrasonic transducer and the origin;

[0019] Step 3.2: Photoacoustic temperature image reconstruction based on coherence factor weighted fusion:

[0020] Step 3.2.1: Reconstruct the sound pressure signal using the sound pressure signal received by the ring array transducer. The reconstruction formula is as follows:

[0021]

[0022] Among them, P0(x,y;t) represents the sound pressure information reconstructed at the position (x,y) at time t, Δs i (t+δt i ) represents the signal received by the i-th transducer at time t+δt i The differential signal at r S is the sound source position vector, expressed in grid coordinates (x, y), r d is the position vector of the ultrasonic transducer array, calculated in step 3.1. cosα is the cosine of the angle between the line connecting the ith transducer array and the center of the circle and the line connecting the target grid point (x, y) and the transducer. N is the total number of transducers. is the result of normalization of the coherence weighting factor CF(x,y;t), that is:

[0023]

[0024] Where max(CF(x, y; t)) represents the maximum value of CF(x, y; t), and the coherence weighting factor CF(x, y; t) is calculated by the following formula:

[0025]

[0026] Among them, CF(x,y;t) is the value of the coherent weighting factor at time t, s i (t+Δt i ) is the signal received by the array ultrasonic transducer at t+Δt i The value obtained at the moment;

[0027] Step 3.2.2: Substitute the linear relationship between sound pressure and temperature formula P(x, y; y) = A1 + A2T(x, y; t) in step 2.1 into the sound pressure signal reconstruction formula in step 3.2.1 to obtain the photoacoustic temperature image reconstruction formula:

[0028]

[0029] Step 3.3: Fuse the coherence factor-weighted temperature reconstructed image obtained in step 3.2.2 with the preprocessed image of the ultrasound modality obtained in step 2.4 to obtain fused image information.

[0030] Compared with the prior art, the present invention has the following advantages:

[0031] 1. Traditional reconstructed images have strong artifacts, many side lobes, and low resolution. The present invention introduces a coherent weighting factor to provide weighted calculation for the reconstructed image, effectively suppressing the high artifacts and multiple side lobes that exist in traditional image reconstruction algorithms.

[0032] 2. The present invention proposes a new method for photoacoustic temperature image reconstruction, which significantly improves the resolution of non-invasive temperature imaging based on the photoacoustic effect and improves the temperature measurement accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 Schematic diagram of the temperature image reconstruction structure based on the coherence factor;

[0034] Figure 2 This is a schematic diagram of the system working sequence;

[0035] Figure 3 A comparison of CFWTM temperature imaging and FBP temperature imaging. DETAILED DESCRIPTION

[0036] The technical solution of the present invention is further described below with reference to the accompanying drawings, but is not limited thereto. Any modification or equivalent replacement of the technical solution of the present invention that does not depart from the spirit and scope of the technical solution of the present invention should be included in the scope of protection of the present invention.

[0037] The present invention provides a photoacoustic temperature imaging method based on coherence factor weighted fusion, such as Figure 1 As shown, the method includes the following steps:

[0038] Step 1. Hardware composition and configuration of the multi-bandwidth photoacoustic imaging system based on photoacoustic and ultrasound dual modalities:

[0039] The present invention provides a multi-bandwidth photoacoustic imaging system based on photoacoustic and ultrasonic dual modalities, designed to provide the basic information required for subsequent temperature reconstruction and multimodal image fusion. The multi-bandwidth photoacoustic imaging system based on photoacoustic and ultrasonic dual modalities consists of the following main components: a pulsed laser, a ring array ultrasonic transducer, a multi-channel data acquisition card, a central computer, and a main control board. The pulsed laser is used to emit nanosecond pulsed light to excite light absorbers in the target area and generate photoacoustic signals; the ring array ultrasonic transducer is used to acquire ultrasonic and photoacoustic dual modal signals; the multi-channel data acquisition card is used to digitize the ultrasonic and photoacoustic dual modal signals received by the ring array transducer and transmit the processed data to the central computer for further analysis and processing; and the main control board is used to match the operating timing of each system component after receiving commands from the central computer to ensure normal operation of the system. During operation, the system controls the operation of the pulsed laser by issuing commands to the central computer. The main control board automatically matches the operating timing of the ring array ultrasonic transducer and the multi-channel data acquisition card under different operating modes to complete temperature imaging and photothermal therapy. Ultrasound and photoacoustic signals are essentially sound pressure signals, and the ring array transducer can capture dual-modal information from both ultrasound and photoacoustics. Through a pre-set timing design, this system can achieve real-time ultrasound / photoacoustic dual-modal image reconstruction of the target area, providing rich information on tumor structure and function.

[0040] Step 2: Ultrasonic modal signal preprocessing:

[0041] During the experimental operation, the pulsed laser emits short pulses of light, which illuminate the tissue within the target imaging area and stimulate the generation of photoacoustic signals. The intensity of the generated photoacoustic signal is related to the temperature of the target area and can be specifically represented by the following formula:

[0042] P(x,y;t)=A1+A2T(x,y;t)

[0043] Where P(x, y; t) represents the sound pressure at position (x, y) at time t, T(x, y; t) refers to the instantaneous temperature at position (x, y) at time t, (x, y) are the Cartesian coordinates of the imaging position, with the origin at the center of the array, and A1 and A2 are linear coefficients that can be calibrated experimentally. Therefore, by calculating P(t) in the target area, the temperature at the target location can be obtained.

[0044] like Figure 2As shown, after receiving imaging instructions from the central computer, the main control board triggers the pulsed laser to begin emitting light pulses and simultaneously activates the circular array transducer to begin receiving signals. Through a predetermined timing design, individual circular array transducers receive the photoacoustic and ultrasound signals of the tumor target area, respectively. These signals are collected by a multi-channel data acquisition card and stored in the central computer. To ensure the accuracy and efficiency of subsequent image reconstruction, the signals collected by the multi-channel data acquisition card undergo preliminary preprocessing in the central computer to remove noise from the received signals and enhance the effective signal portion, ensuring the accuracy and efficiency of subsequent dual-modality image reconstruction. The preprocessed signals are then used to generate ultrasound modality images using a traditional reconstruction algorithm. The target area is selected and its coordinates are obtained. The target area is set as a rectangle, and its coordinates are represented by four numbers: the horizontal coordinate of the upper left corner of the rectangle, the vertical coordinate of the upper left corner of the rectangle, the length of the rectangle in the x-direction, and the length of the rectangle in the y-direction.

[0045] Step 3: Calculation of coherence factor and weighting of reconstructed image:

[0046] Step 3.1: Assignment of basic parameters and division of target area grid:

[0047] Allocation of basic parameters: specify the initial sound velocity, delay time of the array ultrasonic transducer, array radius, target area grid size and sampling frequency of the multi-channel data acquisition card in the program.

[0048] Target area grid division: In order to achieve high-definition temperature image reconstruction, the target area coordinates obtained in step 2 are used to divide the grid for photoacoustic image reconstruction. The center of the ring array is the coordinate origin, and the corresponding coordinate is (0,0). The relative coordinates of the standard unit (m) are assigned to each grid point. By specifying the radius of the ring array ultrasonic transducer, the parametric equation of the circle is used. The relative coordinates of each circular array ultrasonic transducer and the origin are calculated.

[0049] At this point, the allocation of basic parameters and the division of the target area grid are completed.

[0050] Step 3.2: Photoacoustic temperature image reconstruction based on coherence factor weighted fusion:

[0051] Step 3.2.1: Reconstruct the sound pressure signal using the sound pressure signal received by the ring array transducer. The reconstruction formula is as follows:

[0052]

[0053] Among them, P0(x,y;t) represents the sound pressure information reconstructed at the position (x,y) at time t, Δs i (t+δt i ) represents the signal received by the i-th transducer at time t+δt iThe differential signal at r S is the sound source position vector, expressed in grid coordinates (x, y), r d is the position vector of the ultrasonic transducer array, calculated in step 3.1. cosα is the cosine of the angle between the line connecting the ith transducer array and the center of the circle and the line connecting the target grid point (x, y) and the transducer. N is the total number of transducers. is the normalized result of the coherence weighting factor CF(x, y; t), which is calculated by the following formula:

[0054]

[0055] Among them, CF(x,y;t) is the value of the coherent weighting factor at time t, s i (t+Δt i ) is the signal received by the array ultrasonic transducer at t+Δt i The principle of coherence factor is based on the coherence between the signals received by different array ultrasonic transducers. The numerator of CF(x,y;t) will contain s after being squared. i and s j This reflects the coherence calculation relationship. If the reconstructed target point is the real sound source point, then the coherence here is good and CF(x,y;t) is large. If the reconstructed target point is not the real sound source point, such as the point in the artifact area of ​​the traditional reconstructed image, CF(x,y;t) will be significantly reduced. In the implementation process, because the CF operator value is less than 1, in order to avoid the undesirable small value when calculating the sound pressure value P(t) in the weighted image, CF(x,y;t) needs to be normalized. It is the result of normalization of the coherence weighting factor CF(x,y;t), namely:

[0056]

[0057] Wherein, max(CF(x,y;t)) represents the maximum value of CF(x,y;t).

[0058] Step 3.2.2: Substitute the linear relationship between sound pressure and temperature formula P(x, y; t) = A1 + A2T(x, y; t) in step 2.1 into the sound pressure signal reconstruction formula in step 3.2.1 to obtain the photoacoustic temperature image reconstruction formula:

[0059]

[0060] The above formula is the coherent factor weighing temperature imaging algorithm CFWTM. The temperature reconstructed image obtained through the above calculation effectively reduces the sidelobes and noise level, ultimately improving the signal-to-noise ratio (SNR) and the spatial resolution of the reconstructed image.

[0061] Step 3.3: Fuse the coherence factor-weighted temperature reconstructed image obtained in step 3.2.2 with the preprocessed image of the ultrasound modality obtained in step 2.4 to obtain fused image information.

[0062] Step 4: System verification and application:

[0063] To validate the effectiveness of this invention, experiments were conducted to verify its reliability and applicability in practical applications. The experimental results demonstrated that CFWTM performed exceptionally well in multi-bandwidth photoacoustic imaging tasks. In in vivo experiments, the system was successfully applied to non-invasively measure the temperature of mouse tumor targets following local injection of photothermal nanoprobes. Using CFWTM, the system demonstrated excellent local temperature resolution, accuracy, and temperature correlation, demonstrating its reliability and broad applicability in practical applications.

[0064] Figure 3 The comparison between the finger photoacoustic reconstruction image reconstructed by CFWTM and the photoacoustic temperature image reconstructed by traditional FBP is shown. Figure 3 It can be clearly seen that the photoacoustic temperature imaging based on the CFWTM algorithm can image smaller targets. Compared with the images reconstructed by traditional FBP, the present invention can more effectively remove artifacts and improve imaging resolution.

[0065] This invention demonstrates high-precision non-invasive temperature measurement capabilities, providing a more advanced non-invasive temperature monitoring method for photothermal therapy of tumors. It integrates imaging, segmentation, temperature measurement, and treatment functional modules. By weighting the reconstructed image with a coherence factor, it removes high artifacts and multiple sidelobes from FBP reconstructed images, significantly improving the resolution of temperature imaging. This technology demonstrates significant advantages and enormous potential for photothermal therapy applications. Utilizing multimodal image fusion methods, it ensures that multimodal information of the target area can be obtained during treatment, providing personnel with more intuitive visual feedback on tumor status and enhancing treatment effectiveness.

Claims

1. A photoacoustic temperature imaging method based on coherence factor weighted fusion, characterized in that The method comprises the following steps: Step 1. Hardware composition and configuration of the multi-bandwidth photoacoustic imaging system based on photoacoustic and ultrasound dual modalities: The multi-bandwidth photoacoustic imaging system based on photoacoustic and ultrasonic dual modalities consists of a pulsed laser, a ring array ultrasonic transducer, a multi-channel data acquisition card, a central computer, and a main control board. The pulsed laser is used to emit nanosecond-level pulsed light to excite light absorbers in the target area and generate photoacoustic signals. The ring array ultrasonic transducer is used to acquire ultrasonic and photoacoustic dual-modal signals. The multi-channel data acquisition card is used to perform digital-to-analog conversion on the ultrasonic and photoacoustic dual-modal signals received by the ring array transducer and transmit the processed data to the central computer for further analysis and processing. The main control board is used to match the operating timing of each system component after receiving commands from the central computer to ensure the normal operation of the system. Step 2: Ultrasonic modal signal preprocessing: Step 2.1: A pulsed laser emits short pulses of light that illuminate the tissue within the target imaging area, stimulating a photoacoustic signal. The intensity of the generated photoacoustic signal is related to the temperature of the target area and is specifically characterized by the following formula: P(x,y;t)=A1+A2T(x,y;t) Where P(x, y; t) represents the sound pressure value at the position (x, y) at time t, T(x, y; t) refers to the instantaneous temperature at the position (x, y) at time t, (x, y) is the Cartesian coordinate of the imaging position, with the origin at the center of the ring array, and A1 and A2 are linear coefficients. Step 2.2: After receiving the imaging command from the central computer, the main control board triggers the pulsed laser to start emitting light pulses and simultaneously activates the ring array transducers to start receiving signals. Each ring array transducer receives the photoacoustic and ultrasound signals from the tumor target area. These signals are collected by a multi-channel data acquisition card and stored in the central computer. Step 2.3: Preliminary preprocessing is performed on the signals collected by the multi-channel data acquisition card in the central computer to remove noise from the received signals and enhance the effective parts of the signals; Step 2.4: Using a reconstruction algorithm, the preprocessed signal is reconstructed to generate preprocessed images of multiple ultrasound modalities and obtain the target area coordinates; Step 3: Calculation of coherence factor and weighting of reconstructed image: Step 3.1: Assignment of basic parameters and division of target area grid: Assignment of basic parameters: specify the initial sound velocity, delay time of the array ultrasonic transducer, array radius, target area grid size and sampling frequency of the multi-channel data acquisition card in the program; Target area grid division: Use the target area coordinates obtained in step 2.4 to divide the grid for photoacoustic image reconstruction. Take the center of the ring array as the coordinate origin, the corresponding coordinate is (0,0), assign the relative coordinate of the standard unit system to each grid point, and use the parametric equation of the circle according to the specified radius of the ring array ultrasonic transducer. Calculate the relative coordinates of each circular array ultrasonic transducer and the origin; Step 3.2: Photoacoustic temperature image reconstruction based on coherence factor weighted fusion: Step 3.2.1: Reconstruct the sound pressure signal using the sound pressure signal received by the ring array transducer. The reconstruction formula is as follows: Among them, P0(x,y;t) represents the sound pressure information reconstructed at the time t at the position (x,y), Δs i (t+δt i ) represents the signal received by the i-th transducer at time t+δt i The differential signal at , cosα refers to the cosine of the angle between the line connecting the i-th ring array transducer and the center of the circle and the line connecting the target grid point (x, y) and the transducer, and N is the total number of transducers; is the normalized result of the coherence weighting factor CF(x,y;t); Step 3.2.2: Substitute the linear relationship between sound pressure and temperature in step 2.1 into the sound pressure signal reconstruction formula in step 3.2.1 to obtain the photoacoustic temperature image reconstruction formula: Step 3.3: Fuse the coherence factor-weighted temperature reconstructed image obtained in step 3.2.2 with the preprocessed image of the ultrasound modality obtained in step 2.4 to obtain fused image information.

2. The photoacoustic temperature imaging method based on coherence factor weighted fusion according to claim 1 is characterized in that The target area is set as a rectangle, and its coordinates are represented by four numbers, which are the horizontal coordinate of the upper left corner of the rectangle, the vertical coordinate of the upper left corner of the rectangle, the length of the rectangle in the x direction, and the length of the rectangle in the y direction.

3. The photoacoustic temperature imaging method based on coherence factor weighted fusion according to claim 1 is characterized in that described r S is the sound source position vector, expressed in grid coordinates (x, y), r d is the position vector of the circular array ultrasonic transducer.

4. The photoacoustic temperature imaging method based on coherence factor weighted fusion according to claim 1 is characterized in that described Calculated by the following formula: In this case, max(CF(x,y;t)) represents the maximum value of CF(x,y;t).

5. The photoacoustic temperature imaging method based on coherence factor weighted fusion according to claim 1 or 4, characterized in that The coherence weighting factor CF(x, y; t) is calculated by the following formula: Among them, CF(x,y;t) is the value of the coherent weighting factor at time t, s i (t+Δt i ) is the signal received by the array ultrasonic transducer at t+Δt i The value obtained at the moment.

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