Phase spectrum-based differential dynamic microscopic image acquisition and processing method and related device

Abstract

The application discloses a differential dynamic microscopic image acquisition processing method based on a phase spectrum and a related device, relates to the technical field of particle microscopic image processing, and can measure kinetic information such as a diffusion coefficient of Brown particles. Compared with traditional microscopic image technology, the application is a new technology combining light scattering and optical microscopy. The experimental equipment used in the application is simpler, and the experimental steps are fewer; the application is more convenient to combine with other technologies; the application can well solve the sample concentration limitation problem; and the application can measure a wider variety of particles. The method is to use a high-speed camera to shoot time sequence nanoparticle Brown motion microscopic images, then calculate phase changes of two images with different time intervals through a cross-correlation function, find the relationship between the data obtained in the previous steps and the diffusion coefficient, and thus obtain the diffusion coefficient and other kinetic information of the Brown particles.

Description

Technical Field

[0001] This invention relates to the field of particle microscopic image processing technology, and in particular to a differential dynamic microscopic image acquisition and processing method and related apparatus based on phase spectrum. Background Technology

[0002] In recent years, image processing-based nanoparticle surface detection techniques have gradually developed, such as digital Fourier microscopy and traditional differential dynamic microscopy. These techniques successfully combine image difference and spatial Fourier transform and are widely used in the study of colloid dynamics under ordinary white light systems. Compared with traditional point detection techniques—dynamic light scattering—these methods use incoherent light sources, which not only reduces the requirements for experimental equipment but also avoids the effects of multiple scattering, making them suitable for measuring high-concentration samples. The experimental setup for this technique is simple, requiring only ordinary light sources and inverted microscopes, and it allows for integration with other techniques. Furthermore, based on image processing, dynamic signals from different scattering angles can be acquired simultaneously, greatly simplifying the multi-angle synchronous measurement process of point detection techniques. However, we found in our experiments that current surface detection techniques cannot measure low-concentration samples or hollow materials. This is mainly because these methods theoretically obtain nanoparticle size information by analyzing changes in power spectral density. However, the power spectrum essentially only represents the set characteristics of image grayscale values ​​and cannot reflect its spatial distribution. Therefore, if the number of particles in the image is too small or the material is hollow, the small changes in the power spectrum caused by particle motion are insufficient to provide a sufficient signal-to-noise ratio for the measurement, which will lead to significant errors in the measurement results. Summary of the Invention

[0003] To address the shortcomings of existing technologies, this invention provides a differential dynamic microscopic image acquisition and processing method and related apparatus based on phase spectrum, which more accurately captures particle dynamics information by utilizing changes in the phase spectrum.

[0004] To achieve the above objectives, the present invention provides the following technical solution:

[0005] In a first aspect, the present invention provides a differential dynamic microscopic image processing method based on phase spectrum, comprising:

[0006] To acquire microscopic images that can be displayed on particles;

[0007] The microscopic image is subjected to differential processing to obtain a series of differential image data; a one-dimensional Fourier transform operation is performed on the differential image data in the column direction or row direction to obtain intermediate result matrix data; a one-dimensional Fourier transform operation is performed on the intermediate result matrix data in another direction to obtain two-dimensional transform result data; the phase spectrum of the cross spectrum is obtained according to the cross-correlation function of the two-dimensional transform result data, and it is determined as Fourier phase spectrum image data.

[0008] The Fourier phase spectrum image data is subjected to dimensionality reduction processing. Based on the dimensionality-reduced Fourier phase spectrum image data and intermediate scattering functions, the dynamic information of the particle is obtained.

[0009] Secondly, the present invention provides a differential dynamic microscopic image processing system based on phase spectrum, comprising:

[0010] An image acquisition unit is used to acquire microscopic images that can be displayed on particles;

[0011] An image processing unit is used to perform differential processing on the microscopic image to obtain a series of differential image data; to perform a one-dimensional Fourier transform operation on the differential image data in the column direction or row direction to obtain intermediate result matrix data; to perform a one-dimensional Fourier transform operation on the intermediate result matrix data in another direction to obtain two-dimensional transform result data; and to obtain the phase spectrum of the cross spectrum based on the cross-correlation function of the two-dimensional transform result data, and determine it as Fourier phase spectrum image data.

[0012] The data processing unit is used to perform dimensionality reduction processing on the Fourier phase spectrum image data, and obtain the dynamic information of the particle based on the dimensionality-reduced Fourier phase spectrum image data and the intermediate scattering function.

[0013] Thirdly, the present invention also provides an electronic device, including a processor and a memory;

[0014] The memory is used to store programs;

[0015] The processor executes the program to implement the method described above.

[0016] Fourthly, the present invention also provides a computer-readable storage medium storing a program that is executed by a processor to implement the methods described above.

[0017] Fifthly, the present invention also provides a computer program product or computer program comprising computer instructions stored in a computer-readable storage medium. A processor of a computer device can read the computer instructions from the computer-readable storage medium and execute the computer instructions to cause the computer device to perform the preceding method.

[0018] In a sixth aspect, the present invention also provides a microscopic image acquisition device, which includes: an illumination component, a collimation component, a reflection component, a focusing component, a sample cell component, and an imaging module;

[0019] The white light emitted by the illumination component is sequentially irradiated onto the sample cell component by the collimation component, the reflection component, and the focusing component, so that the white light beam is perpendicularly irradiated onto the surface of the sample cell component, thereby forming a light field;

[0020] The sample cell assembly contains a solution, and the solution contains the particles to be tested; and,

[0021] An imaging module is used to acquire microscopic images that can be displayed on the particles.

[0022] Compared with the prior art, the advantages of this invention are as follows:

[0023] 1. The difference between this invention and traditional microscopic image processing methods lies in the fact that this invention is a new technique combining light scattering and optical microscopy. This technique acquires microscopic images of samples in real space and reconstructs dynamic scattering patterns by analyzing the changes in the intensity of scattered light in the time and spatial domains of the microscopic image, thereby obtaining the dynamic information of the sample. Compared with traditional dynamic microscopy techniques, we mainly utilize changes in the image's phase spectrum, rather than the amplitude spectrum. The amplitude spectrum essentially only represents the set characteristics of image grayscale values ​​and cannot reflect the spatial grayscale distribution characteristics. Therefore, it is no longer sensitive to small changes in the image. The interpretability of the image is essentially reflected more in the phase spectrum than the amplitude spectrum. Therefore, by utilizing changes in the phase spectrum, we can effectively capture the dynamic information of particles.

[0024] 2. The experimental equipment used in this invention is simpler, and the experimental steps are fewer. Traditional methods for measuring particles, such as dynamic light scattering, require a relatively complex experimental optical path and a laser as the input light source. In contrast, this invention only requires a white light illumination device as the light source, which greatly reduces costs.

[0025] 3. This invention is easier to combine with other technologies. Compared to other methods for measuring particles, this invention offers the possibility of combination with other technologies, and it can be arbitrarily applied to various fields by adding other fields. For example, it can be used for the detection of microbial systems.

[0026] 4. Compared to DDM or DLS technologies, phase differential dynamic microscopy effectively addresses sample concentration limitations in particle size measurement through its algorithm. This reduces the need for experimental equipment and simplifies sample preparation compared to other methods. Furthermore, the results obtained using this invention are more reliable than those obtained with other technologies when the sample concentration is too high or too low.

[0027] 5. Regarding the types of samples to be tested, the present invention has a wider measurable range. It is particularly advantageous in measuring certain special particles, such as nanobubbles and microorganisms, which are not particularly noticeable under a microscope, making measurement more difficult. The particle size information obtained by the present invention closely matches the measurement results of DLS, which has been proven to detect nanobubbles. Attached Figure Description

[0028] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0029] Figure 1 This is a flowchart of a method according to an embodiment of the present invention;

[0030] Figure 2 This is a schematic diagram of the apparatus according to an embodiment of the present invention;

[0031] Figure 3 This is an operation flowchart of the device according to an embodiment of the present invention;

[0032] Figure 4 This is a schematic diagram of the system structure in an embodiment of the present invention;

[0033] Figure 5 This is a schematic diagram of an electronic device in an embodiment of the present invention.

[0034] The components include: 1. Illumination assembly; 2. Collimation assembly; 3. Reflection assembly; 4. Concentrating assembly; 5. Sample cell assembly; 6. Focusing assembly; and 7. Imaging module. Detailed Implementation

[0035] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0036] Example:

[0037] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, in the embodiments of this invention are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0038] Example 1

[0039] This invention acquires microscopic images of samples in real space and reconstructs dynamic scattering patterns by analyzing the changes in scattered light intensity in the time and spatial domains, thereby obtaining dynamic information about the sample. Compared to traditional dynamic microscopy techniques, this invention primarily utilizes changes in the image's phase spectrum, rather than the amplitude spectrum. The amplitude spectrum essentially only represents the set characteristics of image grayscale values ​​and cannot reflect the spatial grayscale distribution characteristics. Therefore, it is less sensitive to minute changes in the image, and the interpretability of the image is essentially reflected more in the phase spectrum than the amplitude spectrum. Thus, this invention effectively captures particle dynamics information by utilizing changes in the phase spectrum.

[0040] See Figure 1 A differential dynamic microscopic image processing method based on phase spectrum may specifically include the following steps:

[0041] Step 101: Obtain a microscopic image that can display the particles.

[0042] In this step, a microscopic image of the particles can be obtained by the following operation: a beam of illumination light is collimated through a collimation system and then vertically illuminates the surface of the sample cell to form a uniform light field. The Brownian motion of the particles is then observed in the imaging device. A set of microscopic images is captured in a frame-by-frame manner, and the captured images are required to clearly show the particles.

[0043] In the above operation, the light field only needs to consist of a white light illumination field. When the white light field illuminates the sample cell, the light field intensity should be uniform and stable so that the particles in the sample cell are clearly visible. The captured microscopic images are of uniform size, the number of captured images is at least 2000, and the frame rate is at least 160 frames.

[0044] In the above operation, the light field needs to be perpendicularly irradiated onto the surface of the sample cell. When taking microscopic images using an imaging device, the imaging device needs to be connected to a computer. When a clear microscopic image is generated on the computer, the microscopic image of particle motion is captured at a certain size. After frame capture, a set of Brownian particle images is obtained, thus realizing the acquisition of raw data.

[0045] In the above operation, the particles are specifically Brownian motion particles with a diameter D in the micrometer range, ranging in size from about 0.4 μm to 2 μm. They are made of polystyrene and nanobubbles and have stable physical properties.

[0046] In the above operation, the micro-nano particles or bulk nanobubbles to be separated are further pretreated so that they can move freely and be suspended in the liquid and placed in the sample cell.

[0047] For example, this step acquires 2,400 raw images containing the distribution of polystyrene microparticles over time.

[0048] The pretreatment in step S0 of this embodiment is as follows: First, using a pipette with a volume range of 10 μl, take 10 μl of Brownian particle size standard material (solid content 0.3%, refractive index n = 1.50~1.60) and dilute it in 10 ml of ultrapure water to make a volume ratio of 1:1000. Then, sonicate the solution for 10 minutes to ensure that the Brownian particles are evenly distributed in the liquid. Finally, use a microsyringe with a volume range of 10 μl to take some sample and drop it into the sample cell. Place the sample cell on the sample stage and fix it with a tablet clamp.

[0049] Step 102: Perform differential processing on the microscopic image to obtain a series of differential image data; perform a one-dimensional Fourier transform operation on the differential image data in the column direction or row direction to obtain intermediate result matrix data; perform a one-dimensional Fourier transform operation on the intermediate result matrix data in another direction to obtain two-dimensional transform result data; obtain the phase spectrum of the cross spectrum based on the cross-correlation function of the two-dimensional transform result data, and determine it as Fourier phase spectrum image data.

[0050] In this step, the obtained image is subjected to differential processing. The differential image is defined as the difference between the images of the target scene at adjacent time points. It is obtained by subtracting the images of the target scene at adjacent time points, so as to obtain the change of the target scene over time. Through differential processing, the movement of the Brownian particles with positional distribution over time can be obtained.

[0051] Then, perform a Fourier transform on the images captured at time interval Δt:

[0052] Then, calculate the cross-correlation function of the Fourier transform:

[0053] C(u x ,uy ,t,Dt)=FFT·[I(x,y,t)]FFT· * [I(x,y,t+Dt)]

[0054] In the formula C(u x ,u y The cross spectrum (i, t, Dt) is called the cross spectrum, FFT stands for Fast Fourier Transform, and * denotes complex conjugation. The image I(x, y, t) depends on the time it was captured, while (x, y) represents the pixel coordinate system of the image.

[0055] Finally, obtain the phase spectrum of the cross spectrum:

[0056]

[0057] In the formula P(u x ,u y (u, t, Δt) represents the obtained phase spectrum, and the Angle function is used to calculate the complex phase angle. x ,u y () refers to the coordinate system of the Fourier domain. This represents the phase change between the two images.

[0058] Step 103: Perform dimensionality reduction processing on the Fourier phase spectrum image data, and obtain the dynamic information of the particle based on the dimensionality-reduced Fourier phase spectrum image data and intermediate scattering function.

[0059] In this step, the independent q-value kinetic analysis method for colloidal dispersion systems is employed. Mathematically, the phase spectrum is reduced in dimension so that pixels at the same distance from the image center can be represented by the same spatial frequency u. Therefore, in the two-dimensional reciprocal space, different components with the same spatial frequency u can be radially averaged and processed in one dimension. To facilitate comparison with scattering experiments, the spatial frequency u is replaced with the wave vector q = 2πu. The above equation can then be transformed into:

[0060]

[0061] Then, the diffusion motion of the particles is obtained from the phase changes. For the Brownian motion of the particles, the concentration patterns corresponding to the wave vectors decay exponentially in the form of exp(-Δt / τ(q)). The difference values ​​corresponding to each wave vector change with the time interval Δt according to the following intermediate scattering function:

[0062]

[0063] In the formula, C(q) is a correction term related to the optical system, L(q) represents the baseline corresponding to the value of q and related to the number of data points, and τ qThe characteristic time of exponential decay. The characteristic time τ corresponding to each wave vector. q Satisfying Relationship:

[0064] τ q =1 / D m q 2

[0065] Where τ q The characteristic time of exponential decay, D m The diffusion coefficient of particles, q 2 The wave vector is used. The data is fitted using the formula described above to obtain the particle diffusion coefficient.

[0066] Example 2

[0067] See Figure 4 Based on the same inventive concept, embodiments of the present invention provide a differential dynamic microscopic image processing system based on phase spectrum, comprising:

[0068] An image acquisition unit is used to acquire microscopic images that can be displayed on particles;

[0069] An image processing unit is used to perform differential processing on the microscopic image to obtain a series of differential image data; to perform a one-dimensional Fourier transform operation on the differential image data in the column direction or row direction to obtain intermediate result matrix data; to perform a one-dimensional Fourier transform operation on the intermediate result matrix data in another direction to obtain two-dimensional transform result data; and to obtain the phase spectrum of the cross spectrum based on the cross-correlation function of the two-dimensional transform result data, and determine it as Fourier phase spectrum image data.

[0070] The data processing unit is used to perform dimensionality reduction processing on the Fourier phase spectrum image data, and obtain the dynamic information of the particle based on the dimensionality-reduced Fourier phase spectrum image data and the intermediate scattering function.

[0071] Since this system corresponds to the differential dynamic microscopic image processing method based on phase spectrum in this embodiment of the invention, and the principle of solving the problem in this system is similar to that of this method, the implementation of this system can refer to the implementation process of the above method embodiment, and the repeated parts will not be described again.

[0072] Example 3

[0073] See Figure 2 and Figure 3Based on the same inventive concept, this invention provides a microscopic image acquisition device, which can be used to acquire microscopic images with particles as described in the above embodiments, and further used to measure the dynamic information of low-concentration Brownian particles suspended and freely moving in a sample cell. The device specifically includes: an illumination component 1, a collimation component 2, a reflection component 3, a focusing component 4, a sample cell component 5, and an imaging module 7.

[0074] The white light emitted by the illumination component is sequentially irradiated onto the sample cell component by the collimation component, the reflection component, and the focusing component, so that the white light beam is perpendicularly irradiated onto the surface of the sample cell component to form a light field; the sample cell component contains a solution containing the particles to be measured; the imaging module is used to acquire a microscopic image that can display the particles.

[0075] The aforementioned device acquires microscopic images through the following steps: The micro / nanoparticles or bulk nanobubbles to be separated are pre-treated to allow free movement and suspension in a liquid, and then placed in a sample cell. Illumination light emitted from an LED light source is modulated by a collimation system, primarily composed of a lens, to ensure the beam is as parallel as possible. The collimated beam is then reflected by a mirror onto an objective lens for focusing, creating an illumination field on the sample cell. Finally, the illumination light passes through the sample cell, and the light carrying the dynamic information of the Brownian particles or bulk nanobubbles is focused and fully received by an objective lens, ultimately recorded by a camera.

[0076] In the above embodiments, the brightness of the illumination light can be adjusted by LEDs, and the optimal brightness is such that the movement of Brownian particles can be clearly seen in the camera.

[0077] In the above embodiments, the pretreatment specifically involves: first, using a 10 μl pipette, taking 10 μl of Brownian particle size standard material (solid content 0.3%, refractive index n = 1.50–1.60) and diluting it in 10 ml of ultrapure water to achieve a volume ratio of 1:1000. The solution is then sonicated for 10 minutes to ensure uniform distribution of the Brownian particles in the liquid. Finally, using a 10 μL microsyringe, some sample is taken and dropped into the sample cell. The sample cell is placed on the sample stage and secured with a tablet clamp.

[0078] Specifically, the illumination assembly consists of a white light field emitted by a white LED, which is collimated (shaped into parallel light) by a collimating assembly (which may be a convex lens), and then almost completely reflected by a reflecting assembly (which may be a dichroic beam splitter placed at 45°) to the upper focusing assembly (which may be a focusing objective lens, and may also include a microscope module). Finally, the light is reflected by an objective lens with a numerical aperture of NA = 0.25 (×10) to illuminate the sample cell. The sample cell assembly includes a sample stage and a sample cell. The sample stage has the sample cell on its surface, containing a Brownian particle solution of a certain concentration to be tested. The microscopy module (specifically installed within the condenser assembly) receives all light carrying sample dynamics information through a 25mm objective lens with a numerical aperture of NA = 0.40. By adjustment, two objectives positioned above and below the sample cell are made confocal, allowing illumination light to reach the sample cell and be recorded by the camera. The imaging module, in this embodiment, uses a CCD mounted on an inverted microscope to record the intensity distribution characteristics of scattered light, obtaining microscopic images of the Brownian motion of the particles (specifically, this could be a high-speed camera with a frame rate exceeding 160 frames per second connected to a computer). When a clear particle distribution is generated on the computer, microscopic images of the particle motion are captured at a certain size, and a set of particle images is obtained by frame extraction. Images with some black dots are captured against a bright background. These black dots are dust on the microscope system and are considered a static background distribution. By calculating the phase change or amplitude difference between two images captured at different times, we can eliminate the static background and highlight the dynamic information of the Brownian particles.

[0079] Compared with traditional dynamic differential microscopy, this invention no longer uses power spectrum to obtain the dynamic information of Brownian particles, but calculates it through phase spectrum, which has the advantage of not being limited by the concentration and type of the particles being measured.

[0080] Example 4

[0081] See Figure 5 Based on the same inventive concept, embodiments of the present invention also provide an electronic device, the electronic device including a processor and a memory, the memory storing at least one instruction, at least one program, code set or instruction set, the at least one instruction, the at least one program, the code set or instruction set being loaded and executed by the processor to realize the differential dynamic microscopic image processing method based on phase spectrum as described above.

[0082] It is understood that the memory may include random access memory (RAM) or read-only memory. Optionally, the memory may include non-transitory computer-readable storage medium. The memory can be used to store instructions, programs, code, code sets, or instruction sets. The memory may include a stored program area and a stored data area, wherein the stored program area may store instructions for implementing an operating system, instructions for at least one function, instructions for implementing the various method embodiments described above, etc.; the stored data area may store data created according to the use of the server, etc.

[0083] A processor may include one or more processing cores. The processor connects to various parts of the server via various interfaces and lines, executing instructions, programs, code sets, or instruction sets stored in memory, and accessing data stored in memory to perform various server functions and process data. Optionally, the processor may be implemented using at least one hardware form of Digital Signal Processing (DSP), Field-Programmable Gate Array (FPGA), or Programmable Logic Array (PLA). The processor may integrate one or more of a Central Processing Unit (CPU) and a modem. The CPU primarily handles the operating system and applications; the modem handles wireless communication. It is understood that the modem may also be implemented as a separate chip without being integrated into the processor.

[0084] Since the electronic device is the electronic device corresponding to the differential dynamic microscopic image processing method based on phase spectrum in the embodiments of the present invention, and the principle of the electronic device in solving the problem is similar to that of the method, the implementation of the electronic device can refer to the implementation process of the above method embodiments, and the repeated parts will not be described again.

[0085] Example 5

[0086] Based on the same inventive concept, embodiments of the present invention also provide a computer-readable storage medium storing at least one instruction, at least one program, code set, or instruction set, wherein the at least one instruction, the at least one program, the code set, or the instruction set is loaded and executed by a processor to implement the differential dynamic microscopic image processing method based on phase spectrum as described above.

[0087] Those skilled in the art will understand that all or part of the steps in the various methods of the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, including read-only memory (ROM), random access memory (RAM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), one-time programmable read-only memory (OTPROM), electrically-erasable programmable read-only memory (EEPROM), compact disc read-only memory (CD-ROM) or other optical disc storage, disk storage, magnetic tape storage, or any other computer-readable medium capable of carrying or storing data.

[0088] Since the storage medium is the storage medium corresponding to the differential dynamic microscopic image processing method based on phase spectrum in the embodiments of the present invention, and the principle of the storage medium in solving the problem is similar to that of the method, the implementation of the storage medium can refer to the implementation process of the above method embodiments, and the repeated parts will not be described again.

[0089] Example 6

[0090] In some possible implementations, various aspects of the methods of the embodiments of the present invention can also be implemented as a program product comprising program code that, when run on a computer device, causes the computer device to perform the steps of the phase spectrum-based differential dynamic microscopic image processing method according to various exemplary embodiments of the present application described above. The executable computer program code or "code" for performing the various embodiments can be written in high-level programming languages ​​such as C, C++, C#, Smalltalk, Java, JavaScript, Visual Basic, Structured Query Language (e.g., Transact-SQL), Perl, or in various other programming languages.

[0091] It should be understood that various parts of the present invention can be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0092] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0093] The above embodiments are merely illustrative of the technical concept and features of the present invention, and are intended to enable those skilled in the art to understand the content of the present invention and implement it accordingly. They should not be construed as limiting the scope of protection of the present invention. All equivalent changes or modifications made based on the essence of the content of the present invention should be covered within the scope of protection of the present invention.

Claims

1. A differential dynamic microscopic image processing method based on phase spectrum, characterized in that, include: To acquire microscopic images that can be displayed on particles; The microscopic image is subjected to differential processing to obtain a series of differential image data; A one-dimensional Fourier transform operation is performed on the differential image data in the column direction or row direction to obtain intermediate result matrix data; a one-dimensional Fourier transform operation is performed on the intermediate result matrix data in another direction to obtain two-dimensional transform result data; the phase spectrum of the cross spectrum is obtained based on the cross-correlation function of the two-dimensional transform result data, and it is determined as Fourier phase spectrum image data. The Fourier phase spectrum image data is subjected to dimensionality reduction processing, wherein, spatial frequency Replacing it with the wave vector q = 2πu, we get: Based on the dimension-reduced Fourier phase spectrum image data and intermediate scattering function, the dynamic information of the particle is obtained.

2. The differential dynamic microscopic image processing method based on phase spectrum according to claim 1, characterized in that, The phase spectrum of the cross spectrum is obtained based on the cross-correlation function of the two-dimensional transformation result data, specifically including: The cross spectrum is determined according to the following formula: In the formula, For cross spectrum, For Fast Fourier Transform, * denotes complex conjugation, image. It depends on the time t when it is photographed, and The pixel coordinate system representing the image; The phase spectrum of the cross spectrum is determined according to the following formula: In the formula, The Angle function is used to calculate the complex phase angle for the obtained phase spectrum. The coordinate system of the Fourier domain. This represents the phase change between the two images.

3. The differential dynamic microscopic image processing method based on phase spectrum according to claim 2, characterized in that, Based on the dimension-reduced Fourier phase spectrum image data and intermediate scattering functions, the dynamic information of the particles is obtained, specifically including: for the Brownian motion of the particles, the concentration patterns corresponding to the wave vectors decay exponentially in the form of exp(-Δt / τ(q)), and the difference values ​​corresponding to each wave vector change with the time interval Δt according to the following intermediate scattering function: In the formula, C(q) is a correction term related to the optical system, L(q) represents the baseline corresponding to the value of q and related to the number of data points, and τ q The characteristic time of exponential decay; the characteristic time τ corresponding to each wave vector. q Satisfying Relationship: In the formula, The characteristic time of exponential decay, D m The diffusion coefficient of particles, q 2 The wave vector is used to fit the data according to the above formula, and finally the diffusion coefficient of the particle is obtained.

4. A differential dynamic microscopic image processing system based on phase spectrum, characterized in that, include: An image acquisition unit is used to acquire microscopic images that can be displayed on particles; An image processing unit is used to perform differential processing on the microscopic image to obtain a series of differential image data; A one-dimensional Fourier transform operation is performed on the differential image data in the column direction or row direction to obtain intermediate result matrix data; a one-dimensional Fourier transform operation is performed on the intermediate result matrix data in another direction to obtain two-dimensional transform result data; the phase spectrum of the cross spectrum is obtained based on the cross-correlation function of the two-dimensional transform result data, and it is determined as Fourier phase spectrum image data. The data processing unit is used to perform dimensionality reduction processing on the Fourier phase spectrum image data, wherein... spatial frequency Replacing it with the wave vector q = 2πu, we get: Based on the dimension-reduced Fourier phase spectrum image data and intermediate scattering function, the dynamic information of the particle is obtained.

5. An electronic device, characterized in that, The electronic device includes a processor and a memory, wherein the memory stores at least one instruction, at least one program, a code set, or an instruction set, and the at least one instruction, the at least one program, the code set, or the instruction set is loaded and executed by the processor to implement the differential dynamic microscopic image processing method based on phase spectrum as described in any one of claims 1 to 3.

6. A computer-readable storage medium, characterized in that, The storage medium stores at least one instruction, at least one program, code set, or instruction set, wherein the at least one instruction, the at least one program, the code set, or the instruction set is loaded and executed by a processor to implement the differential dynamic microscopic image processing method based on phase spectrum as described in any one of claims 1 to 3.

7. A microscopic image acquisition device, characterized in that, include: Illumination components, collimation components, reflection components, focusing components, sample cell components, and imaging modules; The white light emitted by the illumination component is sequentially irradiated onto the sample cell component by the collimation component, the reflection component, and the focusing component, so that the white light beam is perpendicularly irradiated onto the surface of the sample cell component, thereby forming a light field; The sample cell assembly contains a solution, and the solution contains the particles to be tested; and, An imaging module is used to acquire a microscopic image of the particle that can be displayed, the microscopic image of the particle being processed using the differential dynamic microscopic image processing method based on phase spectrum as described in any one of claims 1 to 3.

Images