Time dithering correction method for photoacoustic microscopic imaging

Abstract

The application discloses a time jitter correction method for photoacoustic microscopic imaging. An original photoacoustic signal is acquired; the original photoacoustic signal comprises a time signal; unsupervised training is performed based on the original photoacoustic signal to determine a signal offset parameter corresponding to the original photoacoustic signal; the signal offset parameter is related to the time signal; time jitter correction is performed on the original photoacoustic signal by using the signal offset parameter to obtain a corrected target photoacoustic signal, and the accuracy of photoacoustic microscopic imaging signal sampling can be effectively improved.

Description

Technical Field

[0001] This disclosure generally relates to the field of photoacoustic microscopy imaging technology, and specifically to a time jitter correction method for photoacoustic microscopy imaging. Background Technology

[0002] Photoacoustic microscopy is a high-resolution microscopic imaging technique that combines optical and acoustic imaging. It has wide applications in the biomedical field, particularly in imaging living tissues, such as the structural and functional imaging of biological microcirculatory networks. It utilizes laser pulses to excite the sample and generate sound waves, which are then captured by a detector. By measuring the propagation time and amplitude of the sound waves, the three-dimensional structural distribution of biological tissues can be reconstructed.

[0003] However, due to the inherent instability of the laser pulses and the response delay of electronic devices, the time at which the detector receives the photoacoustic signal is inaccurate, i.e., there is a time jitter effect. The time jitter effect manifests as random and non-uniform fluctuations in the time reference line, resulting in errors in the axial positioning of the final 3D reconstructed image. Summary of the Invention

[0004] In view of the above-mentioned defects or deficiencies in the prior art, it is desirable to provide a time jitter correction method for photoacoustic microscopy imaging, which can effectively improve the sampling accuracy of photoacoustic microscopy imaging signals.

[0005] In a first aspect, embodiments of this application provide a time jitter correction method for photoacoustic microscopy imaging, including:

[0006] Acquire the raw photoacoustic signal; the raw photoacoustic signal includes a time signal;

[0007] Unsupervised training is performed based on the original photoacoustic signal to determine the signal offset parameter corresponding to the original photoacoustic signal; the signal offset parameter is related to the time signal.

[0008] The original photoacoustic signal is time-jitter corrected using the signal offset parameter to obtain the corrected target photoacoustic signal.

[0009] In some embodiments, the step of performing unsupervised training based on the original photoacoustic signal to determine the signal offset parameter corresponding to the original photoacoustic signal includes:

[0010] The total signal change is determined based on adjacent photoacoustic signals; the adjacent photoacoustic signals are the adjacent target photoacoustic signals after correction of the original photoacoustic signal.

[0011] The offset of the time signal is updated based on the total change in the signal.

[0012] The signal offset parameter is determined based on the offset of the updated time signal.

[0013] In some embodiments, updating the offset of the time signal based on the total change in the signal includes:

[0014] The offset of the time signal is calculated using the Adam algorithm.

[0015] In some embodiments, determining the signal offset parameter based on the offset of the updated time signal includes:

[0016] Based on the offset of the time signal, determine the discrete coefficients corresponding to the offset;

[0017] The signal offset parameter is determined based on the offset of the time signal and the discrete coefficient.

[0018] In some embodiments, it also includes:

[0019] The signal offset parameter is determined based on an approximate integer of the offset of the time signal.

[0020] In some embodiments, the step of performing time jitter correction on the original photoacoustic signal using the signal offset parameter to obtain the corrected target photoacoustic signal includes:

[0021] The original photoacoustic signal is convolved using the signal offset parameter.

[0022] In some embodiments, the convolution operation of the signal offset parameters satisfies the following relationship:

[0023]

[0024] in, The corrected photoacoustic signal, The original photoacoustic signal, The signal offset parameter is denoted as .

[0025] Secondly, embodiments of this application provide a time jitter correction device for photoacoustic microscopy imaging, comprising:

[0026] The acquisition module is used to acquire the raw photoacoustic signal; the raw photoacoustic signal includes a time signal.

[0027] The determination module is used to perform unsupervised training based on the original photoacoustic signal to determine the signal offset parameter corresponding to the original photoacoustic signal; the signal offset parameter is related to the time signal.

[0028] The correction module is used to perform time jitter correction on the original photoacoustic signal using the signal offset parameter to obtain the corrected target photoacoustic signal.

[0029] Thirdly, embodiments of this application provide an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the method described in embodiments of this application.

[0030] Fourthly, embodiments of this application provide a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method described in embodiments of this application.

[0031] The time jitter correction method for photoacoustic microscopy provided in this application can determine the signal offset parameter for time jitter correction of the original photoacoustic signal by performing unsupervised training on the original photoacoustic signal. The signal offset parameter can be used to correct the time jitter of the original photoacoustic signal to obtain a target photoacoustic signal with high accuracy. Without the need to improve the hardware of the photoacoustic microscopy system or perform model training in advance, it can effectively improve the sampling accuracy of photoacoustic microscopy signal, improve the resolution scale of photoacoustic microscopy, and meet the requirements of high-precision imaging.

[0032] Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0033] Other features, objects, and advantages of this application will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings:

[0034] Figure 1 A schematic diagram illustrating the principle of the time jitter effect provided in the embodiments of this application is shown;

[0035] Figure 2 A schematic diagram of the structure of a synchronous light-probe photoacoustic microscopy imaging system provided in an embodiment of this application is shown;

[0036] Figure 3 A schematic flowchart of a time jitter correction method for photoacoustic microscopy provided in an embodiment of this application is shown;

[0037] Figure 4 A flowchart illustrating a time jitter correction method for photoacoustic microscopy provided in another embodiment of this application is shown.

[0038] Figure 5 A comparison diagram of the time jitter correction effect provided in an embodiment of this application is shown;

[0039] Figure 6 A schematic diagram of the structure of a time jitter correction device for photoacoustic microscopy provided in an embodiment of this application is shown;

[0040] Figure 7 A schematic diagram of the structure of a computer system suitable for implementing an electronic device or server according to embodiments of this application is shown. Detailed Implementation

[0041] The present application will now be described in further detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and not intended to limit it. Furthermore, it should be noted that, for ease of description, only the parts relevant to the invention are shown in the accompanying drawings.

[0042] It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other. This application will now be described in detail with reference to the accompanying drawings and embodiments.

[0043] Photoacoustic microscopy, as an advanced imaging technique, is widely used in biomedical research for high-resolution structural and functional imaging. Specifically, during photoacoustic microscopy, biological tissue absorbs high-energy nanosecond laser pulses, causing rapid thermoelastic expansion and contraction. This rapid expansion generates an acoustic signal with specific time-of-flight characteristics, which can be detected at a certain distance from the biological tissue. Since the intensity of the acoustic signal is proportional to the light absorption of the biological tissue, it can reflect the absorptivity distribution at a specific excitation wavelength. Therefore, photoacoustic microscopy is widely used in subcutaneous microvascular morphology imaging, blood oxygen saturation measurement, single-cell behavior analysis, and melanoma detection.

[0044] The pulse excitation used in photoacoustic microscopy can provide axial resolution: since the speed of ultrasonic waves is much slower than the speed of light, the distance from which the photoacoustic signal is generated can be calculated based on the measured arrival time of the ultrasonic waves, thus providing axial layering capability. This endows photoacoustic microscopy with the ability to resolve axial information, enabling three-dimensional volumetric imaging through two-dimensional point scanning. Compared to pure optical three-dimensional imaging techniques that require combination with three-dimensional mechanical scanning, photoacoustic microscopy offers faster three-dimensional imaging speed and has significant advantages in terms of imaging signal-to-noise ratio and sample bleaching damage.

[0045] However, due to the inherent instability of laser pulses and the response delay of electronic devices, the timing of the acoustic signal received by the acoustic detection device is inaccurate, i.e., a time jitter effect exists. Under the influence of the time jitter effect, random or non-uniform fluctuations in the time baseline will occur during 3D image reconstruction, such as... Figure 1As shown, this leads to axial positioning errors in the 3D image, which severely affects the accuracy of 3D reconstruction in photoacoustic microscopy, especially when high-resolution depth information is required. For example, the propagation speed of ultrasound signals in soft tissue is approximately 1.5 μm / ns, meaning that a 1 ns time jitter can result in a 1.5 μm positioning error.

[0046] To address the timing jitter effect, related technologies utilize synchronized optical detection to correct timing errors. Specifically, high-frequency acoustic detection equipment, such as a 50MHz ultrasonic transducer, is used because its axial resolution is below 30μm, meaning that a few nanoseconds of timing jitter has a relatively small impact on the overall axial resolution of the system. Combining this with a standard photodiode (PD) and a data acquisition card (DAQ) with a bandwidth of several hundred MHz can meet certain imaging resolution requirements. Figure 2 As shown, the synchronous light-probe photoacoustic microscopy imaging system includes: a control unit FPGA, a timing signal generator, a beam emitting unit, a feedback correction unit, a laser shaping unit, an acoustic wave receiving unit, a signal amplification unit, and a data acquisition card (DAQ). The control unit FPGA receives the timing signal from the timing signal generator, generates a pulse control signal, and sends it to the beam emitting unit. The beam emitting unit can be a nanosecond pulse laser source, such as a 532nm Q-switched laser, which generates a 13ns pulse width under the action of the pulse control signal. With the generation of the laser pulse, the feedback correction unit receives the optical pulse signal, generates a feedback signal, and inputs the feedback signal to the data acquisition card (DAQ). The laser pulse is focused onto biological tissue by the laser shaping unit (e.g., a lens) to generate a photoacoustic signal. The acoustic wave receiving unit receives the acoustic wave signal and converts it into an electrical signal. The acoustic wave receiving unit can be an ultrasonic transducer. The electrical signal converted by the acoustic wave receiving unit is input to the signal amplification unit for signal amplification before being input to the data acquisition card (DAQ). However, despite using a photodiode with a bandwidth of 2GHz and a data acquisition card with a bandwidth of several hundred MHz, an axial positioning error of several micrometers still occurs.

[0047] However, with the advancements in photoacoustic microscopy in recent years, the requirements for axial resolution have been significantly increased by orders of magnitude. Synchronous light detection still produces axial positioning errors of a few micrometers, which seriously affect the axial positioning accuracy of photoacoustic microscopy.

[0048] Based on this, this application proposes a time jitter correction method for photoacoustic microscopy, which can use an unsupervised learning framework to correct the original photoacoustic signal to sub-pixel accuracy without real data.

[0049] To further illustrate the technical solutions provided in the embodiments of this application, a detailed description is provided below in conjunction with the accompanying drawings and specific implementation methods. Although the embodiments of this application provide method operation instruction steps as shown in the following embodiments or drawings, the method may include more or fewer operation instruction steps based on conventional or non-creative effort. In steps where there is no logically necessary causal relationship, the execution order of these steps is not limited to the execution order provided in the embodiments of this application. In actual processing or when the device executes the method, it may be executed sequentially or in parallel according to the method shown in the embodiments or drawings.

[0050] Please refer to Figure 3 , Figure 3 A schematic flowchart of a time jitter correction method for photoacoustic microscopy provided in an embodiment of this application is shown. Figure 3 As shown, the method includes:

[0051] Step 301: Obtain the original photoacoustic signal.

[0052] The original photoacoustic signal includes the acoustic signal received by the acoustic wave receiving unit and its corresponding time signal, wherein the time signal is denoted as... , The signal location is the i-th signal point. For variables.

[0053] Step 302: Perform unsupervised training based on the original photoacoustic signal to determine the signal offset parameters corresponding to the original photoacoustic signal.

[0054] It should be noted that unsupervised training involves discovering hidden structures and patterns from unlabeled data. The signal offset parameter is a correction parameter used to correct time jitter in the original photoacoustic signal; the signal offset parameter is related to the offset of the time signal in the original photoacoustic signal.

[0055] Step 303: Use the signal offset parameter to perform time jitter correction on the original photoacoustic signal to obtain the corrected target photoacoustic signal.

[0056] It should be understood that the core of time jitter correction is to align each time signal with the same time reference line. Therefore, in the embodiments of this application, time jitter correction of the original photoacoustic signal is to adjust the photoacoustic signal that has generated time offset to the correct time reference line.

[0057] In other words, in this embodiment of the application, by performing unsupervised training on the original photoacoustic signal, the signal offset parameter used for time jitter correction of the original photoacoustic signal can be determined, and the original photoacoustic signal can be time jitter corrected using the signal offset parameter to obtain a target photoacoustic signal with high precision. Without improving the hardware of the photoacoustic microscopy imaging system or performing model training in advance, the accuracy of photoacoustic microscopy imaging signal sampling is effectively improved, the resolution scale of photoacoustic microscopy imaging is improved, and the high-precision imaging requirements are met.

[0058] In one feasible embodiment, such as Figure 4 As shown, step 302 involves unsupervised training based on the original photoacoustic signal to determine the signal offset parameters corresponding to the original photoacoustic signal, including:

[0059] Step 3021: Determine the total amount of signal change based on adjacent photoacoustic signals.

[0060] It should be noted that for spatially continuous three-dimensional objects, temporal jitter can disrupt the smoothness of adjacent photoacoustic signals along the time dimension. Therefore, in this embodiment, the spatial continuity of photoacoustic signals with spatiotemporal information is evaluated using the total amount of signal variation, and this is used as the loss function for training. Specifically, using the total amount of signal variation for spatial continuity analysis tends to result in piecewise smoothness, allowing for abrupt edges within the volume of the three-dimensional object.

[0061] Among them, the adjacent photoacoustic signal is the adjacent target photoacoustic signal after the original photoacoustic signal has been corrected.

[0062] Specifically, in the embodiments of the application, the total amount of signal change can be expressed as:

[0063]

[0064] in, This represents the total signal change between the original photoacoustic signals. and These are the photoacoustic signals of two adjacent targets.

[0065] It should be understood that when the original photoacoustic signal has not been corrected in the initial stage, the total signal change is determined using the original photoacoustic signal. As the original photoacoustic signal in the initial stage is corrected, the total signal change changes to the total signal change between the corrected adjacent target photoacoustic signals.

[0066] Step 3022: Update the offset of the time signal based on the total amount of signal change.

[0067] In one feasible embodiment, the Adam algorithm is used to calculate the offset of the time signal.

[0068] Specifically, the gradient corresponding to the offset of the time signal is calculated based on the offset of the time signal. Then determine the first moment estimate of the gradient change. and second-order moment estimation That is, the momentum and variance of the offset gradient change, for the first moment estimate and second-order moment estimation Perform bias correction and use the bias-corrected estimated value. and Update the offset of the time signal.

[0069] Specifically, the offset of the time signal can be updated using the following formula:

[0070]

[0071]

[0072]

[0073]

[0074]

[0075]

[0076]

[0077] in, This represents the gradient corresponding to the offset of the time signal. For first-order moment estimation, For second-order moment estimation, and The result is the deviation correction. This represents the offset of the time signal. For learning rate, and This represents the exponential decay rate.

[0078] It should be understood that within a sampling time i, the offset of the time signal can be updated once or multiple times (k), as long as the sampling efficiency and update efficiency can meet the requirements of optical microscopy imaging and the hardware computing efficiency can be achieved. This application does not make any specific limitations.

[0079] Step 3023: Determine the signal offset parameter based on the offset of the updated time signal.

[0080] It should be noted that the signal offset parameter is a probability density function that satisfies a Gaussian distribution. The offset of the time signal can describe the central tendency of the Gaussian distribution. Therefore, it is necessary to further determine the discrete coefficients corresponding to the offset to determine the signal offset parameter.

[0081] Specifically, the discrete coefficients corresponding to the offset are determined based on the offset of the time signal, and the signal offset parameters are determined based on the offset and discrete coefficients of the time signal.

[0082] Specifically, the offset of the time signal and the signal offset parameter satisfy the following relationship:

[0083]

[0084] in, For signal offset parameters, σ is the offset of the time signal, and σ is the discrete coefficient.

[0085] It should be understood that when the discrete coefficient σ approaches 0, it indicates that the offset distribution of the time signal is concentrated and tends towards the offset of the time signal. At this point, the offset of the time signal Restricted to integer values, the Gaussian kernel in the signal offset parameter can be simplified to the Dirac delta function, i.e.:

[0086]

[0087] It should also be understood that, in the embodiments of this application, the Gaussian kernel approximation is selected as the signal offset parameter. Based on its differentiability at any point and its ability to suppress noise through variance, it can help correct time jitter.

[0088] Furthermore, when using the signal offset parameter to correct the time jitter of the original photoacoustic signal to obtain the corrected target photoacoustic signal, the signal offset parameter is specifically used to perform a convolution operation on the original photoacoustic signal.

[0089] Specifically, the convolution operation of the signal offset parameters satisfies the following relationship:

[0090]

[0091] in, The corrected photoacoustic signal, The original photoacoustic signal, This is the signal offset parameter.

[0092] Therefore, the time jitter correction method for photoacoustic microscopy provided in this application can update the offset of the time signal by using the total signal change between adjacent photoacoustic signals, thereby determining a reasonable signal offset parameter. By using the signal offset parameter to correct the time jitter of the original photoacoustic signal, the accuracy of the corrected target photoacoustic signal can be effectively improved to sub-pixel accuracy.

[0093] In one embodiment, the aforementioned synchronous light probe photoacoustic microscopy system is used to perform one-dimensional imaging scanning of horizontal ferrous metals. Figure 5 Spatiotemporal slices of the photoacoustic signal XT from a thin metal sheet are shown. (a) is the original photoacoustic signal without time jitter correction; (b) is the photoacoustic signal corrected using the synchronous detection function of a synchronous light-detecting photoacoustic microscopy system; (c) is the photoacoustic signal corrected using the time jitter correction method proposed in this application; and (d) is the photoacoustic signal corrected using both the time jitter correction method and the synchronous detection function proposed in this application. It can be seen that although the high-speed synchronous detection function in (b) significantly reduces the impact of time jitter, the corrected photoacoustic signal still has obvious residual jitter. In contrast, (c) and (d), which use the time jitter correction method proposed in this application, show better correction results. Moreover, the correction results of (c) and (d) are essentially the same, indicating that by using the time jitter correction method proposed in this application, no additional synchronous detection function is needed, effectively reducing costs while ensuring correction effectiveness.

[0094] It should be noted that although the operation of the method of the present invention is described in a specific order in the accompanying drawings, this does not require or imply that the operations must be performed in that specific order, or that all the operations shown must be performed in order to achieve the desired result.

[0095] Figure 6 A schematic diagram of the structure of a time jitter correction device for photoacoustic microscopy provided in an embodiment of this application is shown.

[0096] like Figure 6 As shown, the time jitter correction device 10 for photoacoustic microscopy includes:

[0097] Acquisition module 11 is used to acquire the original photoacoustic signal; the original photoacoustic signal includes a time signal;

[0098] The determination module 12 is used to perform unsupervised training based on the original photoacoustic signal to determine the signal offset parameter corresponding to the original photoacoustic signal; the signal offset parameter is related to the time signal;

[0099] The correction module 13 is used to perform time jitter correction on the original photoacoustic signal using the signal offset parameter to obtain the corrected target photoacoustic signal.

[0100] In some embodiments, the determining module 12 is specifically used for:

[0101] Determine the total signal change based on adjacent photoacoustic signals;

[0102] The offset of the time signal is updated based on the total change in the signal.

[0103] The signal offset parameter is determined based on the offset of the updated time signal.

[0104] In some embodiments, the determining module 12 is specifically used for:

[0105] The offset of the time signal is calculated using the Adam algorithm.

[0106] In some embodiments, the determining module 12 is specifically used for:

[0107] Based on the offset of the time signal, determine the discrete coefficients corresponding to the offset;

[0108] The signal offset parameter is determined based on the offset of the time signal and the discrete coefficient.

[0109] In some embodiments, the determining module 12 is specifically used for:

[0110] The signal offset parameter is determined based on an approximate integer of the offset of the time signal.

[0111] In some embodiments, the correction module 13 is specifically used for:

[0112] The original photoacoustic signal is convolved using the signal offset parameter.

[0113] In some embodiments, the convolution operation of the signal offset parameters satisfies the following relationship:

[0114]

[0115] in, The corrected photoacoustic signal, The original photoacoustic signal, The signal offset parameter is denoted as .

[0116] It should be understood that the modules or modules described in the time jitter correction device 10 for photoacoustic microscopy are related to the reference... Figure 3The steps in the described method correspond to each other. Therefore, the operations and features described above for the method are also applicable to the time jitter correction device 10 for photoacoustic microscopy and the modules contained therein, and will not be repeated here. The time jitter correction device 10 for photoacoustic microscopy can be pre-implemented in the browser or other secure applications of an electronic device, or it can be loaded into the browser or other secure applications of an electronic device by downloading. The corresponding modules in the time jitter correction device 10 for photoacoustic microscopy can cooperate with modules in the electronic device to implement the solutions of the embodiments of this application.

[0117] The division of modules or units mentioned in the detailed description above is not mandatory. In fact, according to the embodiments of this disclosure, the features and functions of two or more modules or units described above can be embodied in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided and embodied by multiple modules or units.

[0118] The following is for reference. Figure 7 , Figure 7 A schematic diagram of the structure of a computer system suitable for implementing the embodiments of this application is shown.

[0119] like Figure 7 As shown, the computer system includes a central processing unit (CPU) 701, which can perform various appropriate actions and processes based on programs stored in read-only memory (ROM) 702 or programs loaded from storage section 708 into random access memory (RAM) 703. RAM 703 also stores various programs and data required for the system's operating instructions. CPU 701, ROM 702, and RAM 703 are interconnected via bus 704. Input / output (I / O) interface 705 is also connected to bus 704.

[0120] The following components are connected to I / O interface 705: an input section 706 including a keyboard, mouse, etc.; an output section 707 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and speakers, etc.; a storage section 708 including a hard disk, etc.; and a communication section 709 including a network interface card such as a LAN card, modem, etc. The communication section 709 performs communication processing via a network such as the Internet. A drive 710 is also connected to I / O interface 705 as needed. A removable medium 711, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed on drive 710 as needed so that computer programs read from it can be installed into storage section 708 as needed.

[0121] Specifically, according to embodiments of this application, the flowchart above refers to... Figure 2The described process can be implemented as a computer software program. For example, embodiments of this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowchart. In such an embodiment, the computer program contains program code for performing the methods shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network via communication section 709, and / or installed from removable medium 711. When the computer program is executed by central processing unit (CPU) 701, it performs the functions defined in the system of this application.

[0122] It should be noted that the computer-readable medium shown in this application can be a computer-readable signal medium or a computer-readable storage medium, or any combination of the two. A computer-readable storage medium can be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this application, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In this application, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. Computer-readable signal media can also be any computer-readable medium other than computer-readable storage media, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to: wireless, wire, optical fiber, RF, etc., or any suitable combination thereof.

[0123] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operational instructions of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two connected blocks may actually be executed substantially in parallel, or they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified functions or operational instructions, or using a combination of dedicated hardware and computer instructions.

[0124] The units or modules described in the embodiments of this application can be implemented in software or hardware. The described units or modules can also be housed in a processor; for example, a processor can be described as including an acquisition module, a determination module, and a correction module. The names of these units or modules do not necessarily limit the specific unit or module itself; for example, an acquisition module can also be described as "acquiring a raw photoacoustic signal; the raw photoacoustic signal includes a time signal."

[0125] In another aspect, this application also provides a computer-readable storage medium, which may be included in the electronic device described in the above embodiments, or may exist independently and not assembled into the electronic device. The computer-readable storage medium stores one or more programs that, when used by one or more processors, execute the time jitter correction method for photoacoustic microscopy described in this application.

[0126] The above description is merely a preferred embodiment of this application and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of disclosure in this application is not limited to technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the foregoing disclosed concept. For example, technical solutions formed by substituting the above features with (but not limited to) technical features with similar functions disclosed in this application.

Claims

1. A temporal dithering correction method for photoacoustic microscopic imaging, characterized in that, The method comprises: acquiring an original photoacoustic signal; the original photoacoustic signal comprises a time signal; performing unsupervised training based on the original photoacoustic signal to determine a signal offset parameter corresponding to the original photoacoustic signal; the signal offset parameter is related to the time signal; performing time jitter correction on the original photoacoustic signal by using the signal offset parameter to obtain a corrected target photoacoustic signal; wherein the performing unsupervised training based on the original photoacoustic signal to determine a signal offset parameter corresponding to the original photoacoustic signal comprises: determining a total signal change based on adjacent photoacoustic signals; the adjacent photoacoustic signals are adjacent target photoacoustic signals corrected from the original photoacoustic signal; updating the offset of the time signal based on the total signal change; determining the signal offset parameter based on the updated offset of the time signal; wherein the determining the signal offset parameter based on the updated offset of the time signal comprises: determining a discrete coefficient corresponding to the offset of the time signal based on the offset of the time signal; determining the signal offset parameter based on the offset of the time signal and the discrete coefficient; and wherein the offset of the time signal and the signal offset parameter satisfy the following relationship: wherein is a signal offset parameter, is an offset of the time signal, σ is a dispersion coefficient, and the offset of the time signal is restricted to integer values, a Gaussian kernel approximation is chosen as the signal offset parameter, is a signal position, i.e. the i-th signal point, is a variable.

2. The temporal dithering correction method for photoacoustic microscopic imaging according to claim 1, wherein, the updating the offset of the time signal based on the total signal change comprises: calculating the offset of the time signal by using an Adam algorithm. 3.The time dithering correction method for photoacoustic microscopic imaging according to claim 1, wherein, the performing time jitter correction on the original photoacoustic signal by using the signal offset parameter to obtain a corrected target photoacoustic signal comprises: performing convolution operation on the original photoacoustic signal by using the signal offset parameter.

4. The temporal dithering correction method for photoacoustic microscopic imaging according to claim 3, wherein, the convolution operation of the signal offset parameter satisfies the following relationship: wherein is the corrected photoacoustic signal, is the original photoacoustic signal, is the signal offset parameter.

5. A temporal dithering correction device for photoacoustic microscopy, characterized in that, The method comprises: an acquisition module configured to acquire an original photoacoustic signal; the original photoacoustic signal comprises a time signal; a determination module configured to perform unsupervised training based on the original photoacoustic signal to determine a signal offset parameter corresponding to the original photoacoustic signal; the signal offset parameter is related to the time signal; a correction module configured to perform time jitter correction on the original photoacoustic signal by using the signal offset parameter to obtain a corrected target photoacoustic signal; wherein the determination module is further configured to determine a total signal change based on adjacent photoacoustic signals; the adjacent photoacoustic signals are adjacent target photoacoustic signals corrected from the original photoacoustic signal; update the offset of the time signal based on the total signal change; determine the signal offset parameter based on the updated offset of the time signal; wherein the determining the signal offset parameter based on the updated offset of the time signal comprises: determining a discrete coefficient corresponding to the offset of the time signal based on the offset of the time signal; determining the signal offset parameter based on the offset of the time signal and the discrete coefficient; and wherein the offset of the time signal and the signal offset parameter satisfy the following relationship: wherein is a signal offset parameter, is an offset of the time signal, σ is a dispersion coefficient, and the offset of the time signal is restricted to integer values, a Gaussian kernel approximation is chosen as the signal offset parameter, is a signal position, i.e. the i-th signal point, is a variable.

6. An electronic device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, The processor executes the program to implement the time jitter correction method for photoacoustic microscopic imaging according to any one of claims 1-4.

7. A computer readable storage medium having stored thereon a computer program, characterized in that, The program, when executed by the processor, implements the time dithering correction method for photoacoustic microscopic imaging according to any one of claims 1-4.

Images