Microscope cross-scale multi-modal correlation analysis method and system

Abstract

The invention discloses a microscope cross-scale multi-modal correlation analysis method and a microscope cross-scale multi-modal correlation analysis system, and belongs to the technical field of microscopic imaging. According to the method, one, two or three micron-scale positioning holes are prepared or pasted on a sample carrier to serve as reference marks; the coordinates of the positioning holes are obtained under any two kinds of microscopic imaging or analysis equipment including a scanning electron microscope, an optical microscope and a Raman microscope, a coordinate conversion model between different microscopic systems is established, and accurate positioning and correlation analysis of the same sample area under the different microscopic systems are achieved; the system for realizing the method comprises a sample carrier, a positioning hole preparation module, a coordinate acquisition module and a coordinate conversion module. According to the method, the technical problem that in the prior art, accurate correlation analysis of the same microcell is difficult to carry out among different microtechnologies is solved, accurate correspondence of cross-scale multi-modal microscopic analysis is achieved, the positioning accuracy is better than 10 micrometers, and the method is suitable for comprehensive analysis and research in the fields of material science, biology, botany and the like.

Description

Technical Field

[0001] The present invention belongs to the field of microscopic imaging technology, and specifically relates to a microscope cross-scale multimodal correlation analysis method and system. Background Art

[0002] As scientific research deepens, a single microscopy technique often fails to meet the needs of comprehensive analysis of complex samples. Different microscopy techniques have their own unique characteristics: optical microscopy (OM) enables fluorescence imaging of living samples and the identification of specific protein markers, Raman microscopy provides information on the chemical composition and molecular structure of samples, and scanning electron microscopy (SEM) provides surface topography information at nanoscale resolution. For complex biological systems such as plant samples, simultaneously obtaining information on their optical properties, chemical composition, and ultrastructure is of great scientific significance.

[0003] In existing technologies, cross-scale multimodal correlation analysis mainly has the following problems:

[0004] 1) The coordinate systems of different microscope systems vary greatly, making precise alignment difficult. For example, the grid marking method disclosed in US20090048510A1 (published on February 19, 2009) is complex and requires specially designed grid markers, making it unsuitable for routine biological sample analysis.

[0005] 2) High cost of equipment integration: Traditional correlative microscopy techniques, such as “Simultaneous Correlative Scanning Electron and High-NA Fluorescence Microscopy” published in PLOS ONE (2013, 8(2)), require special integrated equipment, which is expensive and complex to operate;

[0006] 3) Complex marker preparation and recognition technology: Existing technologies, such as “Computer-readable Image Markers for Automated Registration in Correlative Microscopy” published in Science Direct, use computer-readable markers, but the marker preparation is complex and requires specialized image recognition algorithms.

[0007] 4) Conventional correlative microscopy methods rely on natural features in the sample for positioning, which has low positioning accuracy and is difficult to automate.

[0008] Therefore, there is an urgent need to develop a simple, efficient and accurate microscope cross-scale multimodal correlation analysis method to achieve precise coordinate mapping and regional repositioning between different microscopic systems. Summary of the Invention

[0009] The purpose of the present invention is to provide a microscope cross-scale multimodal correlation analysis method and system to solve the technical problem in the prior art that it is difficult to perform accurate correlation analysis on the same micro area between different microscopic techniques.

[0010] To achieve the above objectives, the present invention provides a microscope cross-scale multimodal correlation analysis method and system, and adopts the following technical solutions:

[0011] A microscope cross-scale multimodal correlation analysis method comprises the following steps:

[0012] Step 1: Prepare or paste one, two or three micron-scale positioning holes on the sample carrier as reference marks;

[0013] Step 2: Fix the sample to be analyzed on a sample carrier containing positioning holes so that the sample and the positioning holes are in the same focal plane;

[0014] Step 3: Place the sample in the first microscope system, locate and record the coordinates of the positioning hole; and select the region of interest (POI) and record its coordinates;

[0015] Step 4: Transfer the sample to a second microscopic system, locate and record the coordinates of the positioning holes, wherein the first microscopic system and the second microscopic system are two different types of microscopic imaging or analysis equipment;

[0016] Step 5: establishing a coordinate transformation model based on the coordinates of the positioning hole in the first microscopic system and the second microscopic system;

[0017] Step 6: The coordinates of the region of interest in the first microscope system are brought into the coordinate transformation model, and the corresponding coordinates in the second microscope system are calculated to achieve precise repositioning.

[0018] Furthermore, the first microscopic system and the second microscopic system are selected from any two of microscopic imaging or analysis equipment including an optical microscope, a scanning electron microscope, and a Raman microscope.

[0019] Furthermore, when a positioning hole is used, step 3 also includes using a special fixture to fix the sample carrier, and the fixture has a fixed geometric shape, including a square, rectangle, or cut-edge circle of a specific size, and fixes the sample carrier in the same way in different microscope systems, so that the position and orientation of the sample in the two microscope systems are consistent.

[0020] Furthermore, when two positioning holes are used, the coordinate transformation model is a linear transformation model including translation and rotation.

[0021] Furthermore, when three positioning holes are used, the coordinate transformation model is an affine transformation model including translation, rotation, and scaling to calibrate the spatial scaling caused by imaging errors.

[0022] Furthermore, the diameter of the positioning hole is 5-50 μm; when two or three positioning holes are used, the distance between the holes is 5-10 mm.

[0023] Furthermore, the sample carrier is a silicon wafer, a glass slide or other flat substrate whose surface flatness meets the requirements of microscopic imaging.

[0024] Furthermore, the positioning holes are prepared by laser micromachining, etching technology or by pasting prefabricated microhole marks.

[0025] The present invention also protects a microscope cross-scale multimodal correlation analysis system for implementing the above-mentioned method, comprising a sample carrier, a positioning hole preparation module, a coordinate acquisition module and a coordinate conversion module; the sample carrier is used to carry the sample to be analyzed; the positioning hole preparation module is used to prepare or paste one, two or three micron-level positioning holes on the sample carrier; the coordinate acquisition module includes any two of the microscopic imaging or analysis equipment including an optical microscope, a scanning electron microscope, and a Raman microscope, and records the positioning hole coordinates of the sample to be tested under two different microscopic systems and the coordinates of the area of interest under one of the microscopic systems; the coordinate conversion module is used to establish a coordinate conversion model between the two different microscopic systems, and calculate the corresponding coordinates of the area of interest under the other microscopic system based on the coordinate conversion model.

[0026] Furthermore, the coordinate conversion module is computer software having the functions of coordinate input, conversion calculation and result output.

[0027] Furthermore, when one positioning hole is used, a special fixture is also included to fix the sample carrier in the same way in different microscope systems, so that the direction and position of the sample in different microscope systems are consistent.

[0028] Compared with the prior art, the present invention has the following beneficial effects:

[0029] The positioning strategy provided by the present invention includes a single positioning hole in conjunction with a fixture, a double positioning hole to establish a linear conversion model, and a three-positioning hole calibration for spatial scaling caused by imaging errors. This can realize cross-scale multimodal correlation analysis between microscopic imaging or analysis equipment including scanning electron microscopes, optical microscopes, and Raman microscopes, and achieve precise coordinate mapping between different microscopic systems with a positioning accuracy better than 10 microns. The positioning holes in the present invention can be realized by direct processing or pasting prefabricated marks, which increases the flexibility and scope of use of the method. The present invention is particularly suitable for cross-scale multimodal analysis of plant samples. The present invention does not require special integrated equipment and can be implemented using existing microscopic equipment, with low cost and easy operation. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] Figure 1 It is a schematic diagram of the process of the present invention;

[0031] Figure 2 (a), 2(b), and 2(c) are schematic diagrams of the configuration of a single-hole fitting fixture, a double-positioning hole fixture, and a triple-positioning hole fixture, respectively;

[0032] Figure 3 Schematic diagram of the coordinate transformation model principle of the present invention;

[0033] Figure 4 (a) and (b) are the corresponding images of the particulate foreign matter on the filter membrane sample in Example 1 under optical microscope and scanning electron microscope;

[0034] Explanation of the numbers in the figure: 1-sample stage, 2a, 2b-glass slides, 3-glass slide slot, 4a-40um positioning hole, 4b-20um positioning hole, 4c-25um prefabricated micropore mark, 5-silicon wafer. DETAILED DESCRIPTION

[0035] The technical solution of the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0036] Example 1

[0037] like Figures 1 to 4 As shown, the present invention provides a microscope cross-scale multimodal correlation analysis method, comprising the following steps:

[0038] Step 1: Preparation of double positioning holes

[0039] Use two prefabricated 75um diameter micro-aperture apertures and stick them diagonally to the edge of the lithium battery cleanliness test filter membrane so that they can be clearly seen under both optical microscope and scanning electron microscope;

[0040] Step 2: Filter sample loading

[0041] Place the filter membrane sample on the stage of the optical microscope, ensuring that the two microaperture diaphragms are in a diagonal relationship;

[0042] Step 3: Acquisition of optical microscope coordinates, including:

[0043] Step 3.1 Place the filter membrane sample on the stage of an Olympus BX53 optical microscope and observe using a 20x objective lens;

[0044] Step 3.2 Locate and record the center XY coordinates of the two positioning holes, which are P1_OM(x1,y1) and P2_OM(x2,y2).

[0045] Step 3.3: Move the stage to the location of the particle of interest and record the coordinates of the POI area as POI_OM (x_poi, y_poi).

[0046] Step 4: Scanning electron microscope coordinate acquisition, including:

[0047] Step 4.1 Transfer the filter membrane sample to a Phenom XL scanning electron microscope and observe it at an accelerating voltage of 15 kV;

[0048] Step 4.2: At a magnification of 500x, locate and record the center XY coordinates of the two positioning holes, P1_SEM(X1, Y1) and P1_SEM(X2, Y2).

[0049] Step 5: Coordinate transformation model calculation

[0050] like Figure 3 As shown in FIG, based on the coordinates of the two positioning holes in OM and SEM, a linear coordinate transformation model is established. The model contains two transformation parameters: translation and rotation:

[0051] Translation vector T = (X1-x1, Y1-y1)

[0052] Rotation angle θ = arctan((Y2-Y1) / (X2-X1))-arctan((y2-y1) / (x2-x1))

[0053] Based on the translation vector T and the rotation angle θ, any point in the OM coordinate system (x_OM, y_OM) is transformed to the corresponding point in the SEM coordinate system (X_SEM, Y_SEM). The coordinate transformation formula is:

[0054] X_SEM=(x_OM-x1)·cosθ-(y_OM-y1)·sinθ+X1

[0055] Y_SEM=(x_OM-x1)·sinθ+(y_OM-y1)·cosθ+Y1

[0056] Step 6: Accurately relocate the POI area

[0057] Substitute the coordinates of the POI area selected in the optical microscope, POI_OM (x_poi, y_poi), into the coordinate transformation model and calculate its corresponding coordinates in the SEM, POI_SEM (X_poi, Y_poi):

[0058] X_poi=(x_poi-x1)·cosθ-(y_poi-y1)·sinθ+X1

[0059] Y_poi=(x_poi-x1)·sinθ+(y_poi-y1)·cosθ+Y1

[0060] By moving the SEM stage to the calculated coordinate position (X_poi, Y_poi), the same region of interest as in the optical microscope can be precisely positioned.

[0061] The experimental results show that the positioning accuracy of the proposed method for coordinate transformation and area relocation is better than 10 μm, which meets the requirements of cleanliness correlation analysis; Figure 4 As shown in Figures 4(a) and 4(b), the images of metal particle foreign matter under optical microscope and scanning electron microscope can be accurately matched, realizing the correlation analysis between morphological characteristics and functional properties.

[0062] Example 2

[0063] like Figures 1 to 2 As shown, a microscope cross-scale multimodal correlation analysis method includes the following steps:

[0064] Step 1: Single positioning hole preparation

[0065] Select slide 2a as sample carrier and design special fixture; Figure 2 As shown in (a), the fixture includes four circular slots 3 located at the four corners of the slide 2a. The slots 3 are used to fix the slide 2a so that the position and orientation of the sample in the two microscope systems are consistent. A circular positioning hole 4a with a diameter of 40 μm is prepared on the slide 2a. It can be laser-drilled, mechanically drilled, or a prefabricated microaperture aperture, which serves as the coordinate origin.

[0066] Step 2: Plant sample preparation and fixation

[0067] Fix the rice leaf sample on the glass slide 2a with the positioning hole, and use transparent tape to fix the edge of the sample so that the sample and the positioning hole 4a are in the same focal plane;

[0068] Step 3: Raman microscope coordinate acquisition, including:

[0069] Step 3.1 Place the sample carrier into the card slot, and then install the card holder on the Renishaw inVia Raman microscope sample stage;

[0070] Step 3.2: Locate and record the center coordinates of the positioning hole 4a as P_Raman(x0,y0), and establish a coordinate system with this as the origin;

[0071] Step 3.3 Select the rice leaf region of interest and record its coordinates relative to the origin as POI_Raman(Δx,Δy);

[0072] Step 4: Scanning electron microscope coordinate acquisition, including:

[0073] Step 4.1 Transfer the fixture and sample carrier to a Hitachi SU8010 scanning electron microscope.

[0074] Step 4.2 Locate and record the center coordinates P_SEM (X0, Y0) of the positioning hole 4a, and use this as the origin to establish the SEM coordinate system;

[0075] Step 5: Coordinate transformation model calculation

[0076] Since the fixture ensures that the sample is oriented in the same direction in both microscope systems, the coordinate transformation only needs to consider the translation factor. The relative coordinates (Δx′, Δy′) of any point in the Raman coordinate system are transformed to the corresponding point in the SEM coordinate system (X_SEM, Y_SEM). The coordinate transformation formula is:

[0077] X_SEM=X0+Δx′·k

[0078] Y_SEM=Y0+Δy′·k

[0079] where k is the proportionality coefficient, and Determined by pre-measurement;

[0080] Step 6: Accurately relocate the POI area

[0081] The relative coordinates (Δx, Δy) of the POI selected in the Raman microscope are brought into the coordinate transformation model to calculate its corresponding coordinates in the SEM for precise repositioning.

[0082] The experimental results show that the positioning accuracy of the single positioning hole combined with the fixture method is about 15μm, which basically meets the needs of cross-scale multimodal correlation analysis of plant samples.

[0083] Example 3

[0084] like Figures 1 to 2 As shown, a microscope cross-scale multimodal correlation analysis method includes the following steps:

[0085] Step 1: Preparation of three positioning holes

[0086] A silicon wafer 5 was selected as the sample carrier. Three prefabricated microhole markers 4c with a diameter of 20 μm were attached to the wafer 5. The three positioning holes were distributed in an equilateral triangle with a side length of 10 mm to calibrate the spatial scaling and nonlinear distortion that may occur during the imaging process.

[0087] Step 2: Plant sample preparation and fixation

[0088] A corn leaf sample was fixed on a silicon wafer with three positioning holes 4c. The edges of the sample were fixed with epoxy resin glue so that the sample and the positioning holes were in the same focal plane.

[0089] Step 3: Acquisition of optical microscope coordinates, including:

[0090] Step 3.1 Place the sample carrier on the Zeiss Axio Imager optical microscope stage;

[0091] Step 3.2 Locate and record the center coordinates of the three positioning holes 4c, which are P1_OM (x1, y1), P2_OM (x2, y2), and P3_OM (x3, y3);

[0092] Step 3.3 Select the region of interest and record its coordinates as POI_OM(x_poi,y_poi);

[0093] Step 4: Scanning electron microscope coordinate acquisition, including:

[0094] Step 4.1 Transfer the sample carrier to a FEIQuanta 200 scanning electron microscope;

[0095] Step 4.2: Locate and record the center coordinates of the three positioning holes 4c, which are P1_SEM (X1, Y1), P2_SEM (X2, Y2), and P3_SEM (X3, Y3).

[0096] Step 5: Coordinate transformation model calculation

[0097] Using the coordinates of the three positioning holes, an affine transformation model including translation, rotation, and scaling is established:

[0098]

[0099] The transformation matrix and translation vectors Obtained by solving the following system of equations:

[0100] X1=a·x1+b·y1+tx

[0101] Y1=c·x1+d·y1+ty

[0102] X2=a·x2+b·y2+tx

[0103] Y2=c·x2+d·y2+ty

[0104] X3=a·x3+b·y3+tx

[0105] Y3=c·x3+d·y3+ty

[0106] Step 6: Accurately relocate the POI area

[0107] Bring the POI coordinates POI_OM (x_poi, y_poi) selected in the optical microscope into the coordinate transformation model and calculate their corresponding coordinates in the SEM:

[0108] X_poi=a·x_poi+b·y_poi+tx

[0109] Y_poi=c·x_poi+d·y_poi+ty

[0110] By moving the SEM stage to the calculated coordinates, the same region of interest as in the optical microscope can be precisely located.

[0111] Experimental results show that the three-hole positioning scheme can effectively calibrate the spatial scaling caused by imaging errors, and the positioning accuracy can reach 5μm, which is significantly better than the single-hole and double-hole schemes, and is particularly suitable for application scenarios with high requirements for positioning accuracy.

[0112] Example 4

[0113] like Figures 1 to 2 As shown, a microscope cross-scale multimodal correlation analysis method includes the following steps:

[0114] Step 1: Preparation of double positioning holes

[0115] Select a glass slide 2b as a sample carrier, and use laser micromachining technology to prepare two circular positioning holes 4b with a diameter of 25 μm and a depth of 5 μm on the glass slide 2b, with a distance of 5 mm between the holes;

[0116] Step 2: Preparation and fixation of plant samples

[0117] Fix the Arabidopsis leaf sample on the glass slide 2b with the positioning hole, and use transparent tape to fix the edge of the sample so that the sample and the positioning hole 4b are in the same focal plane;

[0118] Step 3: Acquisition of optical microscope coordinates, including:

[0119] Step 3.1 Place the sample carrier on the stage of a Nikon Eclipse Ti optical microscope and observe using a 40x objective lens;

[0120] Step 3.2: Locate and record the center coordinates of the two positioning holes 4b, which are P1_OM(x1,y1) and P2_OM(x2,y2).

[0121] Step 3.3: Select the leaf area containing a specific pigment as the region of interest and record its coordinates as POI_OM (x_poi, y_poi);

[0122] Step 4: Raman microscope coordinate acquisition, including:

[0123] Step 4.1 Transfer the sample carrier to the Horiba LabRAM HR Raman microscope;

[0124] Step 4.2: Locate and record the center coordinates of the two positioning holes 4b, which are P1_Raman(X1, Y1) and P2_Raman(X2, Y2).

[0125] Step 5: Coordinate transformation model calculation

[0126] Based on the coordinates of the two positioning holes 4b in OM and Raman, a linear coordinate transformation model is established. The model contains two transformation parameters: translation and rotation:

[0127] Translation vector T = (X1-x1, Y1-y1)

[0128] Rotation angle θ = arctan((Y2-Y1) / (X2-X1))-arctan((y2-y1) / (x2-x1))

[0129] Based on the translation vector T and the rotation angle θ, any point in the OM coordinate system (x_OM, y_OM

[0130] ) is converted to the corresponding point (X_Raman, Y_Raman) in the Raman coordinate system. The coordinate conversion formula is:

[0131] X_Raman=(x_OM-x1)·cosθ-(y_OM-y1)·sinθ+X1

[0132] Y_Raman=(x_OM-x1)·sinθ+(y_OM-y1)·cosθ+Y1

[0133] Step 6: Accurately relocate the POI area

[0134] Substitute the POI coordinates POI_OM (x_poi, y_poi) selected in the optical microscope into the coordinate transformation model and calculate its corresponding coordinates POI_Raman (X_poi, Y_poi) in Raman:

[0135] X_poi=(x_poi-x1)·cosθ-(y_poi-y1)·sinθ+X1

[0136] Y_poi=(x_poi-x1)·sinθ+(y_poi-y1)·cosθ+Y1

[0137] By moving the Raman stage to the calculated coordinate position (X_poi, Y_poi), the same region of interest as in the optical microscope can be precisely located.

[0138] Experimental results show that this method can achieve precise correlation analysis between optical microscopy and Raman microscopy, with a positioning accuracy of approximately 8μm. Through this correlation analysis, the morphological features observed under the optical microscope can be accurately matched with the molecular vibration information obtained under the Raman microscope, providing a new research method for the comprehensive analysis of plant samples.

[0139] Example 5

[0140] A microscope cross-scale multimodal correlation analysis system includes: a sample carrier, a positioning hole preparation module, a coordinate acquisition module and a coordinate conversion module; the sample carrier is a silicon wafer, a glass slide or other flat substrate, used to carry the sample to be tested; the positioning hole preparation module is used to prepare or paste one, two or three micron-level positioning holes on the sample carrier; the coordinate acquisition module includes any two of microscopic imaging or analysis equipment including an optical microscope, a scanning electron microscope, and a Raman microscope equipped with a high-precision motorized stage, and collects the positioning hole coordinates of the sample to be tested under two different microscopic systems and the coordinates of the area of interest under one of the microscopic systems; the coordinate conversion module is independently developed coordinate conversion software, which supports coordinate conversion calculations for single positioning hole, double positioning hole or triple positioning hole configurations between different microscopic systems, provides coordinate input, conversion calculation and result output interfaces, visually displays conversion results and error estimates, supports batch coordinate conversion, and realizes precise repositioning of the area of interest under another microscopic system.

[0141] The system was used to conduct cross-scale multimodal correlation analysis on rice leaf samples, and the appropriate positioning hole configuration scheme was selected according to the accuracy requirements. The experimental results showed that the system can achieve accurate correlation analysis between different microscopic imaging or analysis equipment, providing strong technical support for the comprehensive research of plant samples.

[0142] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made by any person skilled in the art within the technical scope disclosed in the present invention and based on the technical solution and inventive concept of the present invention shall be included in the scope of protection of the present invention. Therefore, the scope of protection of the present invention shall be subject to the scope of protection of the claims.

Claims

1. A microscope cross-scale multimodal correlation analysis method, characterized in that: The following steps are involved: Step 1: Prepare or paste one, two or three micron-scale positioning holes on the sample carrier as reference marks; Step 2: Fix the sample to be analyzed on a sample carrier containing positioning holes so that the sample and the positioning holes are in the same focal plane; Step 3: Place the sample in the first microscope system, locate and record the coordinates of the positioning holes; and select the region of interest and record its coordinates; Step 4: Transfer the sample to a second microscopic system, locate and record the coordinates of the positioning holes, wherein the first microscopic system and the second microscopic system are two different types of microscopic imaging or analysis equipment; Step 5: establishing a coordinate transformation model based on the coordinates of the positioning hole in the first microscopic system and the second microscopic system; Step 6: The coordinates of the region of interest in the first microscope system are brought into the coordinate transformation model, and the corresponding coordinates in the second microscope system are calculated to achieve precise repositioning.

2. A microscope cross-scale multimodal correlation analysis method according to claim 1, characterized in that: The first microscopic system and the second microscopic system are selected from any two of microscopic imaging or analysis equipment including an optical microscope, a scanning electron microscope, and a Raman microscope.

3. A microscope cross-scale multimodal correlation analysis method according to claim 1, characterized in that: When using a positioning hole, step 3 also includes using a special fixture to fix the sample carrier, which has a fixed geometric shape, including a square, rectangle, or cut-edge circle of a specific size, and fixes the sample carrier in the same way in different microscope systems so that the position and orientation of the sample in the two microscope systems are consistent.

4. A microscope cross-scale multimodal correlation analysis method according to claim 1, characterized in that: When two positioning holes are used, the coordinate transformation model is a linear transformation model including translation and rotation.

5. The microscope cross-scale multimodal correlation analysis method according to claim 1, characterized in that: When three positioning holes are used, the coordinate transformation model is an affine transformation model including translation, rotation and scaling.

6. A microscope cross-scale multimodal correlation analysis method according to claim 1, characterized in that: The diameter of the positioning hole is 5-50 μm; when two or three positioning holes are used, the distance between the holes is 5-10 mm.

7. A microscope cross-scale multimodal correlation analysis method according to claim 1, characterized in that: The sample carrier is a silicon wafer, a glass slide or other flat substrate whose surface flatness meets the requirements of microscopic imaging.

8. The microscope cross-scale multimodal correlation analysis method according to claim 1, characterized in that: The positioning holes are prepared by laser micromachining, etching technology or by pasting prefabricated microhole marks.

9. A microscope cross-scale multimodal correlation analysis system implementing the method according to any one of claims 1 to 8, characterized in that: It includes a sample carrier, a positioning hole preparation module, a coordinate acquisition module and a coordinate conversion module; the sample carrier is used to carry the sample to be analyzed; the positioning hole preparation module is used to prepare or paste one, two or three micron-level positioning holes on the sample carrier; the coordinate acquisition module is used to record the positioning hole coordinates of the sample to be tested under two different microscope systems and the coordinates of the area of interest under one of the microscope systems; the coordinate conversion module is used to establish a coordinate conversion model between different microscope systems, and calculate the corresponding coordinates of the area of interest under the other microscope system based on the coordinate conversion model.

10. The microscope cross-scale multimodal correlation analysis system according to claim 9, characterized in that: The coordinate conversion module is a computer software with the functions of coordinate input, conversion calculation and result output.

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