Photoacoustic temperature imaging method based on delay signal dispersion weighting factor

Abstract

A photoacoustic temperature imaging method based on a delay signal dispersion weighting factor belongs to the technical field of photoacoustic / ultrasonic imaging, and comprises the following steps: S1, constructing a dual-bandwidth photoacoustic imaging system based on photoacoustic and ultrasonic dual modes; s2, a pulse laser of the imaging system emits laser, and a central computer of the imaging system preprocesses the ultrasonic modal signals; s3, calculation and linearization processing of an SDDP factor are carried out; s4, weighting of SDDP factors and temperature reconstruction are carried out; and S5, system verification and application. According to the method, by introducing the SDDP weighting factor, weighting calculation is provided for the reconstructed image, and the phenomena of high artifacts and multiple side lobes existing in a traditional image reconstruction algorithm are effectively inhibited. The invention provides a new method for reconstructing a photoacoustic temperature image, which obviously improves the non-intrusive temperature imaging resolution ratio based on the photoacoustic effect and improves the temperature measurement precision. Compared with other non-linear weighting factors, the SDDP factor provided by the invention can reconstruct photoacoustic temperature image information better in real time through linear processing.

Description

Technical Field

[0001] This invention belongs to the field of photoacoustic / ultrasonic imaging technology, specifically relating to a photoacoustic temperature imaging method based on a weighting factor for the dispersion of a time-delay signal. Background Technology

[0002] Photothermal therapy, as an emerging treatment method with the advantages of being non-invasive and precisely targeted, has attracted widespread attention in the field of cancer treatment. However, due to the lack of effective non-contact temperature measurement technology, it is very difficult to accurately measure the temperature and its distribution in the target area in real time. This may lead to damage to the target area and surrounding healthy tissue due to inaccurate temperature control during the thermotherapy process. 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 invention provides a photoacoustic temperature imaging method based on time-delay signal dispersion factor weighted fusion. This method significantly improves the temperature imaging resolution during photothermal therapy by introducing a linearized SDDP (time-delay signal dispersion) factor weighting during image reconstruction, thereby enhancing temperature measurement accuracy to some extent. Simultaneously, it reduces the complexity of the system hardware, making it suitable for clinical use in tumor photothermal therapy.

[0004] The technical solution adopted in this invention is:

[0005] The photoacoustic temperature imaging method based on the weighting factor of the discreteness of the delayed signal includes the following steps:

[0006] S1. Construct a dual-bandwidth photoacoustic imaging system based on photoacoustic and ultrasonic dual modes;

[0007] S2. The pulsed laser of the imaging system emits laser light, and the central computer of the imaging system preprocesses the ultrasonic modal signals;

[0008] S3. Calculate and linearize the SDDP factor;

[0009] S4. Weighting and temperature reconstruction of SDDP factor;

[0010] S5. System Verification and Application.

[0011] Compared with the prior art, the present invention has the following advantages:

[0012] 1. Traditional image reconstruction algorithms suffer from strong artifacts, numerous side lobes, and low resolution. This invention introduces the SDDP weighting factor to provide weighted calculations for the reconstructed image, effectively suppressing the high artifacts and numerous side lobes present in traditional image reconstruction algorithms.

[0013] 2. This invention proposes a new method for photoacoustic temperature image reconstruction, which significantly improves the resolution of non-invasive temperature imaging based on photoacoustic effects and enhances temperature measurement accuracy.

[0014] 3. The SDDP factor proposed in this invention has undergone linearization processing, and compared with other nonlinear weighting factors, it can better reconstruct photoacoustic temperature image information in real time. Attached Figure Description

[0015] Figure 1 This is a flowchart of the invention;

[0016] Figure 2 This is a schematic diagram of the imaging system's operating timing according to the present invention;

[0017] Figure 3 This is a comparison image of SDDPW temperature imaging and FBP temperature imaging. Detailed Implementation

[0018] To better understand the purpose, structure, and function of this invention, the invention will be described in further detail below with reference to the accompanying drawings.

[0019] This invention provides a photoacoustic temperature imaging method based on SDDP factor weighting, such as... Figure 1 As shown, the method includes the following steps:

[0020] Step 1: Hardware composition and configuration of a dual-bandwidth photoacoustic imaging system based on photoacoustic and ultrasonic dual-modality:

[0021] This invention provides a dual-bandwidth photoacoustic imaging system based on photoacoustic and ultrasonic dual-modality, aiming to provide the necessary basic information for subsequent temperature reconstruction and multimodal image fusion. The dual-bandwidth photoacoustic imaging system based on photoacoustic and ultrasonic dual-modality consists of the following main components: a pulsed laser, an optical path shaping system, a dual-bandwidth ring array ultrasonic transducer, a multi-channel data acquisition card, and a central computer. Specifically: the pulsed laser emits nanosecond-width pulsed light; the ultrashort pulse laser excites the light absorber in the target area, generating the original photoacoustic signal; the ring array ultrasonic transducer consists of two semi-rings with center frequencies of 2.5MHz and 5.5MHz respectively, used to simultaneously receive dual-bandwidth ultrasonic and photoacoustic dual-modal signals; the multi-channel data acquisition card digitizes the ultrasonic and photoacoustic dual-modal signals received by the ring array transducer, immediately saves the processed data in a data buffer, and transmits it to the central computer at a user-defined frame rate for further analysis and processing; the central computer provides a human-computer interaction interface, facilitating the user's rational scheduling of the various components in the system. During system operation, the user controls the pulsed laser by issuing commands from the central computer. The computer automatically coordinates the system components to match the timing of the ring array ultrasound transducer and the multi-channel data acquisition unit under different operating modes, completing the temperature imaging process. Ultrasound and photoacoustic signals are essentially sound pressure signals, and the ring array transducer can acquire information from both ultrasound and photoacoustic modalities. Through preset timing design, this system can achieve real-time ultrasound / photoacoustic dual-modal image reconstruction of the target area, thereby providing rich information on tumor structure and tissue function.

[0022] Step 2, Ultrasonic Modal Signal Preprocessing:

[0023] During the experiment, a pulsed laser emits short pulses of light, which are then directed onto the tissue within the target imaging area, exciting a photoacoustic signal. The intensity of the generated photoacoustic signal is related to the temperature of the target area, and can be characterized by the following formula:

[0024]

[0025] in, express The sound pressure level at location t. refer to The instantaneous temperature at position t. These are Cartesian coordinates at the imaging location, with the origin located at the center of the circular array. and These are linear coefficients, which can be calibrated experimentally. Therefore, by calculating the target region... The temperature at the target location can be obtained.

[0026] During implementation, linear coefficients and The standard calibration procedure is as follows: a temperature range is given within the range that includes the treatment temperature range, such as 30℃ to 70℃. A miniature thermocouple is inserted into the tissue phantom. The temperature value of the tissue phantom measured by the thermocouple is regarded as the true value. At the same time, the measurement data of the thermocouple and the intensity of the photoacoustic signal are recorded. Finally, the experimental data are processed by the least squares method to fit the linear coefficients.

[0027] like Figure 2 As shown, after the user issues an imaging command to the central computer, the central computer controls the pulsed laser to start sending light pulses and simultaneously activates the dual-bandwidth ring array transducer to start receiving signals. Through a predetermined timing design, each ring array transducer receives the photoacoustic and ultrasound signals from the tumor target area, respectively. These signals are acquired 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 acquired by the multi-channel data acquisition card are pre-processed in the central computer to remove noise from the received signals and enhance the effective parts of the signals, ensuring the accuracy and efficiency of subsequent dual-modal image reconstruction. The pre-processed signals are used to generate an ultrasound modality image using a traditional reconstruction algorithm. The target area location is selected, and the target area coordinates are obtained. The target area is set as a rectangle, and its coordinates are represented by four numbers: the x-coordinate of the upper left corner of the rectangle, the y-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.

[0028] Step 3: Calculation and linearization of the SDDP factor:

[0029] Step 3.1: Allocation of basic parameters and division of target area mesh:

[0030] Assignment of basic parameters: Specify the initial sound velocity, data delay of the ring array ultrasonic transducer, ring array radius, number of ring array transducers, horizontal and vertical coordinate range of the target area grid, and sampling frequency of the multi-channel data acquisition card in the program.

[0031] Target area grid division: To achieve high-resolution temperature image reconstruction, the target area coordinates obtained in step 2 are used to divide the photoacoustic image reconstruction into a Cartesian grid. The center of the ring array is set as the origin, corresponding to coordinates (0, 0). A relative coordinate in standard units (m) is assigned to each grid point. Using the specified radius of the ring array ultrasonic transducer, the parametric equation of a circle is applied. The relative coordinates of each ring array ultrasonic transducer to the origin were calculated.

[0032] At this point, the allocation of basic parameters and the division of the target area grid are complete.

[0033] Step 3.2, Calculation of SDDP factor and preliminary reconstruction of photoacoustic image:

[0034] Step 3.2.1, Preliminary image reconstruction calculation:

[0035] The formula for calculating the preliminary reconstructed image is as follows:

[0036]

[0037] in, Represents the coordinates of the region of interest in the reconstructed image. Preliminary estimate of the reconstructed sound pressure at the location corresponding to time t. Indicates the first Each transducer receives a signal at time [time]. The differential signal at the location, where , The sound source location vector is represented by grid coordinates. express, It is the position vector of the ring array ultrasonic transducer. It is the speed of sound propagating within the tissue, calculated in step 3.1. Refers to the first The line connecting the ring array transducer and the center of the circle to the target grid point The cosine of the angle between the line connecting the transducers and the transducer, where N is the total number of transducers. During the initial image reconstruction, the SDDP factor can be calculated in parallel because the required variables in the calculation formula are all the same.

[0038] Step 3.2.2, SDDP factor calculation:

[0039] The SDDP factor of the sound pressure signal is calculated using the sound pressure signal received by the ring array transducer. The calculation formula is as follows:

[0040]

[0041] in, The weighting factor is the value at time t. For the ring array ultrasonic transducer to receive signals in The value obtained at time t; N is the total number of transducers. The principle of the SDDP factor originates from the dispersion of the product between signals received by different ring array ultrasonic transducers. A series of mathematical derivations of the SDDP factor yields the following equivalent expression:

[0042]

[0043] in, and They are and The abbreviation for M is and The mean of the product is expressed as follows:

[0044]

[0045] It can be seen as and The variance of the product reflects the relationship between the original data signal and the degree of fluctuation of the transducer unit. If the reconstructed target point is the real sound source point, then because different transducers have different receiving sensitivities to the same sound source point at different angles, the variance of the product between the signals of different transducers will be relatively large. The factor is relatively large if the target point to be reconstructed is not the real sound source point, such as a point in the artifact region in a traditional reconstructed image. The signal size is significantly reduced because the signals at the corresponding time positions in the raw data received by different transducers are all consistently small, and the corresponding fluctuation is also very small.

[0046] Step 3.3, SDDP factor processing:

[0047] Since the SDDP factors are all greater than zero, there is no need to take their absolute values; normalization is achieved by directly dividing the SDDP factors by their maximum values. During implementation, [the following steps will be taken]. Normalization It is a weighting factor The result of normalization is:

[0048]

[0049] in, Representation factor To ensure the linear relationship between the reconstructed signal and temperature information, the SDDP factor proposed in this specification is linearly related to the initial sound pressure level and the temperature measurement value corresponding to the coordinate point, as the photoacoustic thermometry mechanism requires a linear relationship. Since the SDDP factor is a non-linear factor, it needs to be linearized to avoid disrupting the linear relationship between the reconstructed image and temperature. Because the factor is physically based on the discreteness of the signal (i.e., the artifact points have poor discreteness while the real sound source points have large and significant discreteness), values ​​greater than 0.75 in the normalized SDDP factor can be set to 1, while other values ​​remain unchanged. This completes the linearization of the SDDP factor for the region of interest. The linearization expression is as follows:

[0050]

[0051] Finally, the formula for reconstructing the sound pressure signal using SDDP factor weighting is:

[0052]

[0053] in, Coordinates of the initial sound pressure signal Location, corresponding time The precise weighted estimate information, the coordinates here. The coordinates have the same meaning as those in step 3.2.1, both representing the same pixel in the Cartesian coordinate system. The final calculation result after SDDP factor weighting... This is the preliminary estimated sound pressure signal obtained from the initial calculation in step 3.2.1.

[0054] Step 4: Weighting of factors and temperature reconstruction:

[0055] The temperature reconstruction image weighted by SDDP factor obtained in step 3.3 is fused with the preprocessed image of the ultrasonic mode obtained in step 2.4 to obtain the fused image information.

[0056] The formula for the linear relationship between sound pressure and temperature in step 2.1 Substituting the sound pressure signal into the reconstruction formula of step 3, we obtain the photoacoustic temperature image reconstruction formula:

[0057]

[0058] The above formula is the SDDP factor weighted temperature imaging algorithm SDDPW (Standard deviation of delay product weight). The temperature reconstruction image obtained through the above calculation effectively reduces the sidelobe and noise levels, and ultimately improves the SNR and the spatial resolution of the reconstructed image.

[0059] Step 5, System Verification and Application:

[0060] To verify the effectiveness of this invention, relevant experiments were conducted to verify its reliability and applicability in practical applications. Experimental results show that SDDPW performs excellently in dual-bandwidth photoacoustic imaging tasks. In in vivo experiments, the system was successfully applied to non-invasive temperature measurement of mouse tumor target areas after local injection of photothermal nanoprobes. Using SDDPW, the system demonstrated excellent performance in local temperature measurement resolution, accuracy, and temperature correlation, verifying its reliability and broad applicability in practical applications.

[0061] Figure 3 This demonstrates a comparison between the photoacoustic reconstruction image of the finger reconstructed by SDDPW and the photoacoustic temperature image reconstructed by traditional FBP, from... Figure 3 It is evident from the results that photoacoustic temperature imaging based on the SDDPW algorithm can image smaller targets. Compared with traditional FBP-based reconstructed images, this invention can more effectively remove artifacts while improving imaging resolution.

[0062] This invention demonstrates high-precision non-invasive temperature measurement capabilities, providing a more advanced non-invasive temperature monitoring method for photothermal therapy of tumors. The invention integrates imaging and temperature measurement modules, using an SDDP factor to weight reconstructed images, removing high artifacts and multiple side lobes from FBP-based reconstructed images, significantly improving the resolution of temperature imaging. This demonstrates significant advantages and great application potential in photothermal therapy. Furthermore, the use of multimodal image fusion methods ensures the acquisition of multimodal information about the target area during treatment, providing staff with more intuitive and visualized feedback on tumor status and improving treatment outcomes.

[0063] It is understood that the present invention has been described through some embodiments, and those skilled in the art will recognize that various changes or equivalent substitutions can be made to these features and embodiments without departing from the spirit and scope of the invention. Furthermore, under the teachings of the present invention, these features and embodiments can be modified to adapt to specific situations and materials without departing from the spirit and scope of the invention. Therefore, the present invention is not limited to the specific embodiments disclosed herein, and all embodiments falling within the scope of the claims of this application are within the protection scope of the present invention.

Claims

1. A photoacoustic temperature imaging method based on a delay signal dispersion weighting factor, characterized by: Includes the following steps: S1. Construct a dual-bandwidth photoacoustic imaging system based on photoacoustic and ultrasonic dual modes; S2. The pulsed laser of the imaging system emits laser light, and the central computer of the imaging system preprocesses the ultrasonic modal signals; S3. Calculate and linearize the SDDP factor; S4. Weighting and temperature reconstruction of SDDP factor; S5. System Verification and Application.

2. The photoacoustic temperature imaging method based on a delay signal dispersion weighting factor according to claim 1, characterized in that: In S1, the dual-bandwidth photoacoustic imaging system based on photoacoustic and ultrasonic dual-modality includes... A pulsed laser is used to emit pulses of light with nanosecond-level pulse widths to excite light absorbers in a target area and generate photoacoustic signals. The optical path shaping system is used to shape the spot shape emitted by the pulsed laser to ensure that the pulsed beam can be coupled into the optical system with sufficient coupling efficiency. A dual-bandwidth ring array ultrasonic transducer is used to acquire dual-bandwidth ultrasonic and photoacoustic dual-mode signals. The multi-channel data acquisition card is used to convert the ultrasonic and photoacoustic dual-mode signals received by the ring array transducer into digital-to-analog signals and transmit the processed data to the central computer for further analysis and processing. The central computer provides a human-computer interaction interface, enabling users to rationally schedule the orderly operation of various components within the system.

3. The photoacoustic temperature imaging method based on delay signal dispersion weighting factor according to claim 2, characterized in that: The dual-bandwidth ring array ultrasonic transducer consists of two half-rings with center frequencies of 2.5MHz and 5.5MHz respectively, and is used to simultaneously receive dual-bandwidth ultrasonic and photoacoustic dual-mode signals.

4. The photoacoustic temperature imaging method based on delay signal dispersion weighting factor of claim 2, wherein: The S2 preprocesses the ultrasonic modal signal, including the following steps: S21. A pulsed laser emits short pulses of light, which irradiate the tissue within the target imaging area, exciting a photoacoustic signal. The intensity of the generated photoacoustic signal is related to the temperature of the target area. S22. After receiving the imaging command from the central computer, the main control board triggers the pulsed laser to start sending light pulses and simultaneously starts the ring array transducer to start receiving signals. Each ring array transducer receives the photoacoustic signal and ultrasound signal from the tumor target area. These signals are acquired by the multi-channel data acquisition card and stored in the central computer. S23. The central computer performs preliminary filtering preprocessing on the signals acquired by the multi-channel data acquisition card to remove noise from the received signals and enhance the effective part of the signals; S24. The preprocessed signal is used to generate preprocessed images of multiple ultrasonic modalities and obtain the target area coordinates using a reconstruction algorithm.

5. The photoacoustic temperature imaging method based on delay signal dispersion weighting factor according to claim 4, characterized in that: The specific formula for S21 is as follows: wherein, represents the sound pressure value at the position at time t, denotes the instantaneous temperature at the position at time t, is the Cartesian coordinate at the imaging position, with the coordinate origin at the center of the ring array, and is a linear coefficient.

6. The photoacoustic temperature imaging method based on the weighting factor of the discreteness of the delayed signal according to claim 4, characterized in that: In S24, 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.

7. The photoacoustic temperature imaging method based on the weighting factor of the discreteness of the delayed signal according to claim 4, characterized in that: S3 calculates the SDDP factor and weights the reconstructed image, including the following steps: S31. Assign basic parameters and divide the target area into grids: S32. Calculate the SDDP factor and reconstruct the photoacoustic image initially; S33. Process the SDDP factor.

8. The photoacoustic temperature imaging method based on the weighting factor of the discreteness of the delayed signal according to claim 7, characterized in that: The calculation of the SDDP factor and the preliminary reconstructed photoacoustic image in S32 includes the following steps: S321. Preliminary image reconstruction calculation: The formula for calculating the preliminary reconstructed image is as follows: in, Represents the coordinates of the region of interest in the reconstructed image. Preliminary estimate of the reconstructed sound pressure at the location corresponding to time t. Indicates the first Each transducer receives a signal at time [time]. The differential signal at the location, where , The sound source location vector is represented by grid coordinates. express, It is the position vector of the ring array ultrasonic transducer. It is the speed of sound transmitted through the tissue, calculated in S31. Refers to the first The line connecting the ring array transducer and the center of the circle to the target grid point The cosine of the angle between the line connecting the transducer and the transducer, where N is the total number of transducers; S322. Calculate the SDDP factor: The SDDP factor of the sound pressure signal is calculated using the sound pressure signal received by the ring array transducer. The calculation formula is as follows: in, The weighting factor is the value at time t. For the ring array ultrasonic transducer to receive signals in The value obtained at time t; N is the total number of transducers.

9. The photoacoustic temperature imaging method based on the weighting factor of the discreteness of the delayed signal according to claim 8, characterized in that: The specific process for processing the SDDP factor in S33 is as follows: The normalization formula for the SDDP factor is as follows: in, Representation factor To ensure a linear relationship between the reconstructed signal and temperature information, the maximum value needs to be determined. Perform linearization: 。 10. The photoacoustic temperature imaging method based on the weighting factor of the discreteness of the delayed signal according to claim 9, characterized in that: The specific process of S4 is as follows: The formula for the linear relationship between sound pressure and temperature in S21 Substituting these values ​​into the reconstruction formula for the S321 sound pressure signal, we obtain the photoacoustic temperature image reconstruction formula: 。

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