Holographic microscopy-based living cell imaging method and device

Abstract

The invention discloses a living cell imaging method and device based on holographic microscopy, and the method comprises the steps: placing a living cell sample on a three-dimensional micron-order displacement platform, and controlling the spatial position of the living cell sample; dividing the laser light source into a reference light beam and a sample light beam; the sample light beam is focused on a living cell sample through a microscope, then reaches a holographic detector through an optical element, and interferes with the reference light beam to generate a holographic image; reconstructing the holographic image to obtain a three-dimensional image of the living cell sample; according to the method, the optimal initial path of the sample light beam and the reference light velocity on the holographic detector is obtained based on the population algorithm, so that the optical path difference is minimized, the overall imaging quality is improved, the holographic image is reconstructed through phase recovery, and the final three-dimensional image has higher resolution and better dynamic tracking capability.

Description

Technical Field

[0001] The present invention relates to the technical field of cell imaging, and in particular to a living cell imaging method and device based on holographic microscopy. Background Art

[0002] Holographic microscopy is a high-resolution imaging technology based on the principles of interference and diffraction. It is widely used in the biomedical field to observe tiny and complex biological samples. Holographic microscopy was first proposed by physicist Dennis Gabor in the 1940s and has been subsequently developed and optimized. This technology can generate high-resolution images by recording and analyzing the interference pattern between the sample and the reference beam. It does not require physical cutting or chemical staining of the sample, thereby achieving accurate imaging without damaging the sample. The development of holographic microscopy has evolved from early optical holography to modern digital holography and computational holography.

[0003] Traditional holographic microscopy often uses a single-channel interference image recording method. Although it has significant advantages in observing the internal structure of cells, it is still limited in terms of spatial resolution and imaging depth. In order to overcome these shortcomings, researchers have gradually introduced multi-beam interference technology and digital holography technology. The advancement of these technologies has enabled holographic microscopy to achieve higher precision and deeper three-dimensional imaging. However, existing technologies still face many challenges when dealing with dynamic cell imaging, such as the difficulty of real-time imaging, and it is often difficult to achieve micron-level precise control when dealing with the three-dimensional spatial distribution of samples. Summary of the invention

[0004] In order to overcome the defects in the above-mentioned prior art, the present invention provides a living cell imaging method based on holographic microscopy, comprising: placing a living cell sample on a three-dimensional micron-level displacement platform to control the spatial position of the living cell sample; dividing a laser light source into a reference beam and a sample beam; the sample beam is focused on the living cell sample through a microscope, and then reaches a holographic detector through an optical element to interfere with the reference beam to generate a holographic image; and the holographic image is reconstructed to obtain a three-dimensional image of the living cell sample.

[0005] As a preferred solution of the living cell imaging method based on holographic microscopy described in the present invention, it includes: emitting a laser light source through a semiconductor laser, and the coherence length L of the laser light source is:

[0006] L=2FWHM / π

[0007] Where, FWHM is the full width at half maximum of the laser spectrum;

[0008] The laser light source is divided into a reference beam and a sample beam by a beam splitter, and the transmittance T and reflectance R of the beam splitter are:

[0009] T=I s / I i ;

[0010] R=I r / I i

[0011] In the formula, I s is the light intensity entering the living cell sample, I i is the total light intensity incident on the beam splitter, I r is the intensity of the light entering the reference beam.

[0012] As a preferred solution of the living cell imaging method based on holographic microscopy described in the present invention, it includes: calculating the initial paths of the sample light beam and the reference light speed on the holographic detector respectively; defining the first objective function F1 and the second objective function F2 respectively according to the initial paths; randomly generating the positions of the whale group, each position representing an optical parameter; calculating the fitness of the individual whales; updating the positions of the individual whales, calculating the fitness of the individual whales at this time, and selecting the individual with the smallest fitness as the optimal individual.

[0013] As a preferred solution of the living cell imaging method based on holographic microscopy described in the present invention, the pixel size dpixel of the holographic detector satisfies the following conditions:

[0014] dpixel≤λ / (2·NA)

[0015] Where NA is the numerical aperture.

[0016] As a preferred solution of the living cell imaging method based on holographic microscopy described in the present invention, the reconstruction includes: filtering the holographic image; weighted fusion of holographic images at different angles; multi-scale analysis of the fused holographic image, decomposing the fused holographic image into components of different scales, and processing layer by layer from low scale to high scale to capture details at each level; randomly setting the initial phase estimation, combining the amplitude information of the holographic image and the phase information of the reference beam, repeatedly iterating to optimize the phase estimation, and outputting a three-dimensional image after the iteration.

[0017] As a preferred solution of the living cell imaging device based on holographic microscopy described in the present invention, it includes: a position control module, configured to place the living cell sample on a three-dimensional micron-level displacement platform to control the spatial position of the living cell sample; a laser light source module, configured to divide the laser light source into a reference beam and a sample beam; a holographic imaging module, configured to focus the sample beam on the living cell sample through a microscope, and then reach the holographic detector through an optical element to interfere with the reference beam to generate a holographic image; an image reconstruction module, configured to reconstruct the holographic image to obtain a three-dimensional image of the living cell sample.

[0018] As a preferred solution of the living cell imaging device based on holographic microscopy described in the present invention, the laser light source module is specifically configured to execute: emitting a laser light source through a semiconductor laser, and the coherence length L of the laser light source is:

[0019] L=2FWHM / π

[0020] Where, FWHM is the full width at half maximum of the laser spectrum;

[0021] The laser light source is divided into a reference beam and a sample beam by a beam splitter, and the transmittance T and reflectance R of the beam splitter are:

[0022] T=I s / I i ;

[0023] R=I r / I i

[0024] In the formula, I s is the light intensity entering the living cell sample, I i is the total light intensity incident on the beam splitter, I r is the intensity of the light entering the reference beam.

[0025] As a preferred solution of the living cell imaging device based on holographic microscopy described in the present invention, the holographic imaging module is specifically configured to execute: respectively calculating the initial paths of the sample light beam and the reference light speed on the holographic detector; respectively defining the first objective function F1 and the second objective function F2 according to the initial paths; randomly generating the positions of the whale group, each position representing an optical parameter; calculating the fitness of the individual whales; updating the positions of the individual whales, calculating the fitness of the individual whales at this time, and selecting the individual with the smallest fitness as the optimal individual.

[0026] As a preferred solution of the living cell imaging device based on holographic microscopy described in the present invention, the holographic imaging module is specifically configured to execute: the pixel size dpixel of the holographic detector satisfies the following conditions:

[0027] dpixel≤λ / (2·NA)

[0028] Where NA is the numerical aperture.

[0029] As a preferred solution of the living cell imaging device based on holographic microscopy described in the present invention, the image reconstruction module is specifically configured to execute: filtering processing on the holographic image; weighted fusion of holographic images at different angles; multi-scale analysis processing on the fused holographic image, decomposing the fused holographic image into components of different scales, and processing layer by layer from low scale to high scale to capture details at each level; randomly setting the initial phase estimation, combining the amplitude information of the holographic image and the phase information of the reference beam, repeatedly iterating to optimize the phase estimation, and outputting a three-dimensional image after the iteration.

[0030] Beneficial effects of the present invention: The present invention obtains the optimal initial path of the sample light beam and the reference light beam on the holographic detector based on a swarm algorithm, thereby minimizing the optical path difference and improving the overall imaging quality. At the same time, the holographic image is reconstructed through phase recovery, so that the final three-dimensional image has higher resolution and better dynamic tracking capability. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative labor. Among them:

[0032] Figure 1 This is a schematic diagram of the process of the living cell imaging method based on holographic microscopy according to the first embodiment of the present invention;

[0033] Figure 2 It is a schematic diagram of the process of reconstructing a holographic image according to the first embodiment of the present invention. DETAILED DESCRIPTION

[0034] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0035] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0036] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0037] The present invention is described in detail with reference to schematic diagrams. When describing the embodiments of the present invention, for the sake of convenience, the cross-sectional diagrams showing the device structure will not be partially enlarged according to the general scale, and the schematic diagrams are only examples, which should not limit the scope of protection of the present invention. In addition, in actual production, the three-dimensional dimensions of length, width and depth should be included.

[0038] At the same time, in the description of the present invention, it should be noted that the directions or positional relationships indicated by the terms "upper, lower, inner and outer" are based on the directions or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific direction, be constructed and operated in a specific direction, and therefore cannot be understood as limiting the present invention. In addition, the terms "first, second or third" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance.

[0039] In the present invention, unless otherwise clearly specified and limited, the terms "install, connect, connect" should be understood in a broad sense, for example: it can be a fixed connection, a detachable connection or an integral connection; it can also be a mechanical connection, an electrical connection or a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0040] Example 1

[0041] Reference Figure 1-2 , which is the first embodiment of the present invention, provides a living cell imaging method based on holographic microscopy, comprising:

[0042] S1: Place the living cell sample on a three-dimensional micrometer-level displacement platform to control the spatial position of the living cell sample.

[0043] The three-dimensional micron-level displacement platform is capable of performing micron-level precise displacement in three dimensions to facilitate the precise positioning and scanning of living cell samples (such as cancer cells and bacteria).

[0044] S2: Split the laser light source into a reference beam and a sample beam.

[0045] The laser light source is emitted by a semiconductor laser, and the coherence length L of the laser light source (the distance at which the laser light source maintains coherence) is:

[0046] L=2FWHM / π

[0047] Where, FWHM is the full width at half maximum of the laser spectrum;

[0048] The laser light source is divided into a reference beam and a sample beam by a beam splitter. The transmittance T and reflectance R of the beam splitter are:

[0049] T=I s / I i ;

[0050] R=I r / I i

[0051] In the formula, I s is the light intensity entering the living cell sample, I i is the total light intensity incident on the beam splitter, I r is the light intensity entering the reference beam.

[0052] S3: The sample beam is focused on the living cell sample through a microscope, and then reaches the holographic detector through optical elements, interfering with the reference beam to generate a holographic image.

[0053] The numerical aperture NA of the microscope objective is greater than 0.8, and the resolution is:

[0054] Resolution = 1.22·λ / NA

[0055] The sample beam is focused on the living cell sample through a microscope, and then reaches the holographic detector through optical elements (lenses or mirrors), where it meets and interferes with the reference beam to generate a holographic image.

[0056] In this embodiment, the polymer photonic crystal is fixed on the surface or inside of the beam splitter lens by thin film deposition, interlayer bonding or inlay technology, so as to achieve higher imaging resolution; the lattice structure of the polymer photonic crystal is a body-centered cubic (BCC) structure, the lattice constant (a) is 600nm, each unit cell contains four spherical holes, and the aperture (r) is 200nm (the radius of the hole).

[0057] The reflector includes a high refractive index layer and a low refractive index layer, the materials of the high refractive index layer and the low refractive index layer are silicon and air respectively; the high refractive index layer and the low refractive index layer are alternately stacked, and the thickness of each layer is 1 / 6 of the wavelength of light to achieve interference-enhanced reflection of light, and the thickness of each high refractive index layer is λ / 4n, where λ is the design wavelength and n is the refractive index of silicon; the thickness of each low refractive index layer is λ / 4n; the total number of layers of the reflector is 20, and the thickness of each layer is precisely controlled to ensure complete reflection of light within the target wavelength range. Preferably, the reflector designed in this embodiment uses the interference effect of light to achieve high reflectivity at a specific wavelength, and by having each layer with a thickness of one quarter of the design wavelength, it is ensured that the reflector has a strong reflection ability within the wavelength range.

[0058] Preferably, high quality lenses and mirrors are used to direct the sample and reference beams, ensuring minimal light loss and distortion.

[0059] The pixel size dpixel of the holographic detector satisfies the following conditions:

[0060] dpixel≤λ / (2·NA)

[0061] Where NA is the numerical aperture.

[0062] Furthermore, the initial paths L1 and L2 of the sample beam and the reference beam on the holographic detector are calculated respectively, and the optimal path is obtained by combining the optimized whale algorithm to minimize the optical path difference, thereby improving the overall imaging quality. Specifically:

[0063] (1) Optimize the path of the sample beam on the holographic detector

[0064] ① Define the first objective function F1 according to the initial path L1 of the sample beam on the holographic detector:

[0065]

[0066] In the formula, NA i is the numerical aperture of the i-th optical element. The larger the numerical aperture, the better the focusing performance of the light beam, and the smaller the light scattering and diffraction loss. distance is the distance between the optical elements.

[0067] ② Randomly generate the positions of the whale group, each position represents an optical parameter, that is, the numerical aperture of the optical element.

[0068] ③ Calculate the fitness of individual whales, that is, the objective function value of individual whales.

[0069] ④ Update the position of the individual whales, calculate the fitness of the individual whales at this time, and select the one with the smallest fitness as the optimal individual.

[0070] X new =X best -C·|B·X best -X|

[0071] Where, X new is the new position, X best is the position of the current optimal solution, X is the current position of the whale, C is the scaling factor, which controls the movement range of the whale, and its value range is [0,1]. B is the coefficient that affects the movement of the whale, and its value range is [0,1].

[0072] Furthermore, the scaling factor is dynamically adjusted during the iteration process:

[0073] C(t)=C0·exp(-βt)

[0074] Where C(t) is the scaling factor in the tth iteration, C0 is the initial value of the scaling factor, and β is the parameter that controls the decay rate.

[0075] (2) Optimizing the path of the reference beam on the holographic detector

[0076] ① Define the first objective function F2 according to the initial path L1 of the sample beam on the holographic detector:

[0077]

[0078] Where (x1, y1, z1) is the starting point coordinate of the reference beam, and (x2, y2, z2) is the end point coordinate of the reference beam.

[0079] ② Randomly generate the positions of the whale group, each position represents the optical parameters, that is, the reference beam path coordinates.

[0080] ③ Calculate the fitness of individual whales, that is, the objective function value of individual whales.

[0081] ④ Update the position of the individual whales, calculate the fitness of the individual whales at this time, and select the one with the smallest fitness as the optimal individual.

[0082] X new =X best -C·|B·X best -X|

[0083] Where, X new is the new position, X bestis the position of the current optimal solution, X is the current position of the whale, C is the scaling factor, which controls the movement range of the whale, and its value range is [0,1]. B is the coefficient that affects the movement of the whale, and its value range is [0,1].

[0084] Furthermore, the scaling factor is dynamically adjusted during the iteration process:

[0085] C(t)=C0·exp(-βt)

[0086] Where C(t) is the scaling factor in the tth iteration, C0 is the initial value of the scaling factor, and β is the parameter that controls the decay rate.

[0087] Preferably, the beam path is optimized by combining an optimized whale algorithm to ensure that the optical path is the shortest and straightest to reduce the distortion of the interference pattern.

[0088] S4: Reconstruct the holographic image to obtain a three-dimensional image of the living cell sample.

[0089] Reference Figure 2 , the holographic image is filtered by an adaptive median filtering algorithm; specifically, the local statistical characteristics of the image (i.e., the noise standard deviation) are calculated, and the window size and weight of the filter are dynamically adjusted to remove unnecessary noise while retaining edge information, providing clearer input data for subsequent reconstruction;

[0090] The holographic images at different angles are weightedly fused. Specifically, the holographic images at each viewing angle are weightedly fused, and the weights are determined according to the clarity and contrast of the holographic images, thereby improving the overall quality of the image and reducing the image differences caused by different viewing angles.

[0091] The fused holographic image is subjected to multi-scale analysis and processing. Specifically, the fused holographic image is subjected to wavelet transform, and the fused holographic image is decomposed into components of different scales. The holographic image is processed layer by layer from low scale to high scale to capture the details of each level. The holographic image of each scale is filtered and preliminarily reconstructed, and finally the results of each scale are fused.

[0092] Furthermore, the initial phase estimate is randomly set (the phase can be set to zero or a uniformly distributed random phase image is generated), and the size and resolution of the holographic image are determined to ensure that it matches the actual data.

[0093] Combine the amplitude information of the holographic image and the phase information of the reference beam, iterate repeatedly to optimize the phase estimate, and output a three-dimensional image after the iteration. Specifically, apply the current phase estimate and amplitude information to the Fourier transform to obtain a frequency domain representation. In the frequency domain, use the current phase estimate to calculate the complex amplitude of the holographic image. Combine the amplitude information of the actual holographic image with the amplitude information in the frequency domain representation to keep the amplitude of the holographic image unchanged. Further, perform an inverse Fourier transform on the updated frequency domain data to obtain an updated spatial domain image. Update the phase information in the inverse Fourier transformed image to the current estimate, and the updated phase information obtained will be used to generate the input for the next round of iterations. Repeat the above Fourier transform, amplitude combination and phase update process until the algorithm reaches convergence conditions and outputs a three-dimensional image.

[0094] The convergence condition is: terminate after reaching the preset maximum number of iterations, and the maximum number of iterations is 100.

[0095] Example 2

[0096] This embodiment is different from the first embodiment in that it provides a living cell imaging device based on holographic microscopy, comprising:

[0097] A position control module is configured to place the living cell sample on a three-dimensional micrometer-level displacement platform and control the spatial position of the living cell sample;

[0098] A laser light source module is configured to perform splitting of the laser light source into a reference beam and a sample beam;

[0099] The holographic imaging module is configured to execute the sample beam to be focused on the living cell sample through a microscope, and then reach the holographic detector through an optical element, interfere with the reference beam, and generate a holographic image;

[0100] The image reconstruction module is configured to reconstruct the holographic image to obtain a three-dimensional image of the living cell sample.

[0101] The laser light source module is specifically configured to perform:

[0102] The laser light source is emitted by a semiconductor laser, and the coherence length L of the laser light source is:

[0103] L=2FWHM / π

[0104] Where, FWHM is the full width at half maximum of the laser spectrum;

[0105] The laser light source is divided into a reference beam and a sample beam by a beam splitter. The transmittance T and reflectance R of the beam splitter are:

[0106] T=I s / I i;

[0107] R=I r / I i

[0108] In the formula, I s is the light intensity entering the living cell sample, I i is the total light intensity incident on the beam splitter, I r is the intensity of the light entering the reference beam.

[0109] The holographic imaging module is specifically configured to perform:

[0110] Calculate the initial paths of the sample beam and the reference beam on the holographic detector respectively;

[0111] According to the initial path, a first objective function F1 and a second objective function F2 are defined respectively;

[0112] Randomly generate the positions of whale groups, each position represents an optical parameter;

[0113] Calculate the fitness of individual whales;

[0114] Update the position of the individual whales, calculate the fitness of the individual whales at this time, and select the one with the smallest fitness as the optimal individual.

[0115] The pixel size dpixel of the holographic detector satisfies the following conditions:

[0116] dpixel≤λ / (2·NA)

[0117] Where NA is the numerical aperture.

[0118] The image reconstruction module is specifically configured to perform:

[0119] Performing filtering on the holographic image;

[0120] Perform weighted fusion of holographic images from different angles;

[0121] Perform multi-scale analysis on the fused holographic image, decompose the fused holographic image into components of different scales, and process it layer by layer from low scale to high scale to capture details at each level;

[0122] The initial phase estimation is randomly set, and the amplitude information of the holographic image and the phase information of the reference beam are combined. The phase estimation is optimized through repeated iterations, and a three-dimensional image is output after the iterations are completed.

[0123] It should be appreciated that embodiments of the present invention may be implemented or enforced by computer hardware, a combination of hardware and software, or by computer instructions stored in a non-transitory computer-readable memory. The method may be implemented in a computer program using standard programming techniques - including a non-transitory computer-readable storage medium configured with a computer program, wherein the storage medium so configured causes the computer to operate in a specific and predefined manner - according to the methods and drawings described in the specific embodiments. Each program may be implemented in a high-level procedural or object-oriented programming language to communicate with a computer system. However, if desired, the program may be implemented in an assembly or machine language. In any case, the language may be a compiled or interpreted language. In addition, the program may be run on a programmed ASIC for this purpose.

[0124] Furthermore, the operations of the processes described herein may be performed in any suitable order unless otherwise indicated herein or otherwise clearly contradicted by context. The processes described herein (or variations and / or combinations thereof) may be performed under the control of one or more computer systems configured with executable instructions, and may be implemented as code (e.g., executable instructions, one or more computer programs, or one or more applications) that is executed collectively on one or more processors, by hardware, or a combination thereof. The computer program includes a plurality of instructions that may be executed by one or more processors.

[0125] Further, the method can be implemented in any type of computing platform that is operably connected to a suitable computer, including but not limited to a personal computer, a minicomputer, a mainframe, a workstation, a network or distributed computing environment, a separate or integrated computer platform, or in communication with a charged particle tool or other imaging device, etc. Aspects of the present invention can be implemented in machine-readable code stored on a non-transitory storage medium or device, whether removable or integrated into a computing platform, such as a hard disk, an optical read and / or write storage medium, a RAM, a ROM, etc., so that it can be read by a programmable computer, and when the storage medium or device is read by the computer, it can be used to configure and operate the computer to perform the process described herein. In addition, the machine-readable code, or part thereof, can be transmitted via a wired or wireless network. When such media includes instructions or programs that implement the steps described above in conjunction with a microprocessor or other data processor, the invention described herein includes these and other different types of non-transitory computer-readable storage media. When programmed according to the methods and techniques described in the present invention, the present invention also includes the computer itself. The computer program can be applied to input data to perform the functions described herein, thereby converting the input data to generate output data stored in a non-volatile memory. The output information can also be applied to one or more output devices such as a display. In a preferred embodiment of the present invention, the converted data represents a physical and tangible object, including a specific visual depiction of the physical and tangible object produced on a display.

[0126] As used in this application, the terms "component", "module", "system", etc. are intended to refer to a computer-related entity, which can be hardware, firmware, a combination of hardware and software, software, or software in operation. For example, a component can be, but is not limited to: a process running on a processor, a processor, an object, an executable file, a thread in execution, a program, and / or a computer. As an example, an application running on a computing device and the computing device can both be components. One or more components can exist in a process and / or thread in execution, and a component can be located in a computer and / or distributed between two or more computers. In addition, these components can be executed from various computer-readable media having various data structures thereon. These components can communicate in a local and / or remote process manner, such as according to a signal having one or more data packets (e.g., data from a component that interacts with another component in a local system, a distributed system, and / or interacts with other systems in a signal manner through a network such as the Internet).

[0127] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A method for live cell imaging based on holographic microscopy, It is characterized in that include: Place the living cell sample on a three-dimensional micrometer-level displacement platform to control the spatial position of the living cell sample; Splitting a laser light source into a reference beam and a sample beam; The sample beam is focused on the living cell sample through a microscope, and then reaches the holographic detector through an optical element, interfering with the reference beam to generate a holographic image; The holographic image is reconstructed to obtain a three-dimensional image of the living cell sample.

2. The method for live cell imaging based on holographic microscopy according to claim 1, It is characterized in that include: The laser light source is emitted by a semiconductor laser, and the coherence length L of the laser light source is: L=2FWHM / π Where, FWHM is the full width at half maximum of the laser spectrum; The laser light source is divided into a reference beam and a sample beam by a beam splitter, and the transmittance T and reflectance R of the beam splitter are: T=I s / I i ; R=I r / I i In the formula, I s is the light intensity entering the living cell sample, I i is the total light intensity incident on the beam splitter, I r is the intensity of the light entering the reference beam.

3. The method for living cell imaging based on holographic microscopy as claimed in claim 2, It is characterized in that include: Calculate the initial paths of the sample beam and the reference beam on the holographic detector respectively; Defining a first objective function F1 and a second objective function F2 respectively according to the initial path; Randomly generate the positions of whale groups, each position represents an optical parameter; Calculate the fitness of individual whales; Update the position of the individual whales, calculate the fitness of the individual whales at this time, and select the one with the smallest fitness as the optimal individual.

4. The method for living cell imaging based on holographic microscopy as claimed in claim 3, It is characterized in that include: The pixel size dpixel of the holographic detector satisfies the following conditions: dpixel≤λ / (2·NA) Where NA is the numerical aperture.

5. The method for living cell imaging based on holographic microscopy as claimed in claim 4, It is characterized in that The reconstruction includes: Performing filtering on the holographic image; Perform weighted fusion of holographic images from different angles; Perform multi-scale analysis on the fused holographic image, decompose the fused holographic image into components of different scales, and process it layer by layer from low scale to high scale to capture details at each level; The initial phase estimation is randomly set, and the amplitude information of the holographic image and the phase information of the reference beam are combined. The phase estimation is optimized through repeated iterations, and a three-dimensional image is output after the iterations are completed.

6. A living cell imaging device based on holographic microscopy, It is characterized in that include: A position control module is configured to place the living cell sample on a three-dimensional micrometer-level displacement platform and control the spatial position of the living cell sample; A laser light source module is configured to perform splitting of the laser light source into a reference beam and a sample beam; A holographic imaging module is configured to execute the sample beam to focus on the living cell sample through a microscope, and then reach the holographic detector through an optical element to interfere with the reference beam to generate a holographic image; The image reconstruction module is configured to reconstruct the holographic image to obtain a three-dimensional image of the living cell sample.

7. The living cell imaging device based on holographic microscopy according to claim 6, It is characterized in that The laser light source module is specifically configured to perform: The laser light source is emitted by a semiconductor laser, and the coherence length L of the laser light source is: L=2FWHM / π Where, FWHM is the full width at half maximum of the laser spectrum; The laser light source is divided into a reference beam and a sample beam by a beam splitter, and the transmittance T and reflectance R of the beam splitter are: T=I s / I i ; R=I r / I i In the formula, I s is the light intensity entering the living cell sample, I i is the total light intensity incident on the beam splitter, I r is the intensity of the light entering the reference beam.

8. The living cell imaging device based on holographic microscopy as claimed in claim 7, It is characterized in that The holographic imaging module is specifically configured to perform: Calculate the initial paths of the sample beam and the reference beam on the holographic detector respectively; Defining a first objective function F1 and a second objective function F2 respectively according to the initial path; Randomly generate the positions of whale groups, each position represents an optical parameter; Calculate the fitness of individual whales; Update the position of the individual whales, calculate the fitness of the individual whales at this time, and select the one with the smallest fitness as the optimal individual.

9. The living cell imaging device based on holographic microscopy as claimed in claim 8, It is characterized in that The holographic imaging module is specifically configured to perform: The pixel size dpixel of the holographic detector satisfies the following conditions: dpixel≤λ / (2·NA) Where NA is the numerical aperture.

10. The living cell imaging device based on holographic microscopy according to claim 9, It is characterized in that The image reconstruction module is specifically configured to perform: Performing filtering on the holographic image; Perform weighted fusion of holographic images from different angles; Perform multi-scale analysis on the fused holographic image, decompose the fused holographic image into components of different scales, and process it layer by layer from low scale to high scale to capture details at each level; The initial phase estimation is randomly set, and the amplitude information of the holographic image and the phase information of the reference beam are combined. The phase estimation is optimized through repeated iterations, and a three-dimensional image is output after the iterations are completed.

Images