CN115598822B - Intelligent multi-dimensional microscopic image acquisition and processing method - Google Patents
Intelligent multi-dimensional microscopic image acquisition and processing method Download PDFInfo
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- CN115598822B CN115598822B CN202211609146.7A CN202211609146A CN115598822B CN 115598822 B CN115598822 B CN 115598822B CN 202211609146 A CN202211609146 A CN 202211609146A CN 115598822 B CN115598822 B CN 115598822B
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- G—PHYSICS
- G02—OPTICS
- G02B—OPTICAL ELEMENTS, SYSTEMS OR APPARATUS
- G02B21/00—Microscopes
- G02B21/36—Microscopes arranged for photographic purposes or projection purposes or digital imaging or video purposes including associated control and data processing arrangements
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- G—PHYSICS
- G02—OPTICS
- G02B—OPTICAL ELEMENTS, SYSTEMS OR APPARATUS
- G02B21/00—Microscopes
- G02B21/34—Microscope slides, e.g. mounting specimens on microscope slides
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- G—PHYSICS
- G02—OPTICS
- G02B—OPTICAL ELEMENTS, SYSTEMS OR APPARATUS
- G02B21/00—Microscopes
- G02B21/36—Microscopes arranged for photographic purposes or projection purposes or digital imaging or video purposes including associated control and data processing arrangements
- G02B21/361—Optical details, e.g. image relay to the camera or image sensor
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- G—PHYSICS
- G02—OPTICS
- G02B—OPTICAL ELEMENTS, SYSTEMS OR APPARATUS
- G02B21/00—Microscopes
- G02B21/36—Microscopes arranged for photographic purposes or projection purposes or digital imaging or video purposes including associated control and data processing arrangements
- G02B21/362—Mechanical details, e.g. mountings for the camera or image sensor, housings
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- G—PHYSICS
- G02—OPTICS
- G02B—OPTICAL ELEMENTS, SYSTEMS OR APPARATUS
- G02B21/00—Microscopes
- G02B21/36—Microscopes arranged for photographic purposes or projection purposes or digital imaging or video purposes including associated control and data processing arrangements
- G02B21/365—Control or image processing arrangements for digital or video microscopes
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- G—PHYSICS
- G02—OPTICS
- G02B—OPTICAL ELEMENTS, SYSTEMS OR APPARATUS
- G02B21/00—Microscopes
- G02B21/36—Microscopes arranged for photographic purposes or projection purposes or digital imaging or video purposes including associated control and data processing arrangements
- G02B21/365—Control or image processing arrangements for digital or video microscopes
- G02B21/367—Control or image processing arrangements for digital or video microscopes providing an output produced by processing a plurality of individual source images, e.g. image tiling, montage, composite images, depth sectioning, image comparison
Abstract
The invention provides an intelligent multi-dimensional microscopic image acquisition and processing method, which comprises the steps of driving a sample to move in the Z direction through an objective table, so that light source light rays are focused at different positions in the thickness direction of the sample, facilitating the primary shooting and screening of the thickness direction of the interior of the sample by a microscope, dividing the interior of the sample into a plurality of horizontal sections along the thickness direction of the sample, carrying out horizontal two-dimensional scanning and shooting on each horizontal section to obtain a global image of each horizontal section, splicing the global images of all the horizontal sections to obtain a spatial three-dimensional microscopic image of the sample, and carrying out image acquisition and splicing on different spatial layers in the sample to realize the microscopic imaging of different dimensions in the sample, improve the image acquisition comprehensiveness and the multi-dimensional property of the microscopic imaging and provide sufficient image data for the subsequent diagnosis of a target object.
Description
Technical Field
The invention relates to the technical field of medical image processing, in particular to an intelligent multi-dimensional microscopic image acquisition and processing method.
Background
In the medical diagnosis process, a biological sample from a patient is usually observed under a microscope to obtain the tissue structure information in the biological sample, so as to determine whether a lesion exists in the biological sample, thereby performing corresponding disease identification on the patient. The observation of the existing microscope on the biological sample is only limited to the microscopic imaging of the surface area of the biological sample, but the microscope cannot carry out the microscopic imaging of the structure condition of the internal area of the biological sample, so that the focus distribution condition of the biological sample cannot be comprehensively and sufficiently represented by the image obtained by the microscopic imaging. The current microscope imaging can only carry out image acquisition on the peripheral surface of a biological sample, and cannot go deep into different levels in the biological sample to carry out multi-dimensional image acquisition, so that the comprehensiveness and the multi-dimensional property of image acquisition of the microscope imaging are reduced, and sufficient data cannot be provided for the investigation of a focus area.
Disclosure of Invention
Aiming at the defects in the prior art, the invention provides an intelligent multi-dimensional microscopic image acquisition and processing method, wherein a sample is placed on a three-dimensional movable microscope objective table, the objective table is indicated to drive the sample to move in the Z direction, and a light source of the microscope is indicated to irradiate light rays to the sample, so that the sample structure characteristic information of a horizontal section image at each position in the thickness direction of the sample is obtained, and a horizontal section shooting reference point corresponding to each position is determined; taking the shooting reference point as a reference, indicating the objective table to drive the sample to horizontally move in two dimensions, and shooting to obtain a plurality of horizontal section subarea images of different subareas of the horizontal section at each position in the thickness direction of the sample; the method comprises the steps of splicing all horizontal section sub-area images corresponding to horizontal sections at the same position to form a horizontal section global image based on image characteristic information of each horizontal section sub-area image, splicing all horizontal section global images to obtain a spatial three-dimensional microscopic image related to a sample, driving the sample to move in the Z direction through an objective table to focus light source light at different positions in the thickness direction of the sample, facilitating a microscope to preliminarily shoot and screen the interior of the sample in the thickness direction, dividing the interior of the sample into a plurality of horizontal sections in the thickness direction of the sample, horizontally scanning and shooting each horizontal section in a two-dimensional manner to obtain a global image of each horizontal section, splicing all horizontal section global images to obtain a spatial three-dimensional microscopic image of the sample, collecting and splicing the images of different spatial layers in the sample to realize microscopic imaging of different dimensions in the sample, improving the image collecting comprehensiveness and multidimensional property of microscopic imaging, and providing sufficient image data for subsequent target object diagnosis.
The invention provides an intelligent multi-dimensional microscopic image acquisition and processing method, which comprises the following steps:
step S1, a light source of an instruction microscope irradiates illumination light to a sample, and an objective table of the instruction microscope drives the sample to move in a Z direction, so that focusing illumination areas are formed at different positions in the thickness direction of the sample; acquiring a horizontal section image corresponding to each position in the thickness direction of the sample, and performing identification processing on each horizontal section image;
s2, identifying each horizontal section image to obtain sample structure characteristic information on the horizontal section corresponding to each position in the thickness direction of the sample; determining a shooting reference point of a horizontal section corresponding to each position according to the sample structure characteristic information;
s3, when the light source forms a focusing illumination area at each position in the thickness direction of the sample, the objective table is indicated to drive the sample to horizontally move in two dimensions according to the shooting reference point, and a plurality of horizontal section sub-area images of different sub-areas of the horizontal section at each position in the thickness direction of the sample are shot and obtained; identifying each horizontal section subregion image to obtain image characteristic information of each horizontal section subregion image;
s4, according to the image characteristic information, splicing all horizontal section sub-area images corresponding to the horizontal section at the same position to obtain a horizontal section global image; and then splicing the horizontal section global images corresponding to all the horizontal sections to obtain a spatial three-dimensional microscopic image of the sample.
In an embodiment disclosed in the present application, in step S1, the light source of the instruction microscope irradiates illumination light to the sample, and the stage of the instruction microscope drives the sample to move in the Z direction, so as to form a focused illumination area at different positions in the thickness direction of the sample, specifically including:
determining the reference region area of a focused illumination region formed on the sample by a focused illumination spot generated by a light source according to the minimum cross-sectional area of the sample;
according to the area of the reference region, adjusting the condensation degree of a focusing optical element in the light source on the light beam emitted by the light source so as to enable the spot area of a focusing illumination spot generated by the light source to be equal to the area of the reference region;
indicating an objective table of the microscope to drive the sample to move at preset step intervals in the Z direction so that a focusing illumination spot generated by the light source enters the sample, and respectively forming focusing illumination areas at different positions in the thickness direction of the sample; wherein the Z direction is a direction perpendicular to the plane of the object stage.
In an embodiment disclosed in the present application, in step S1, determining a reference area of a focused illumination area formed on the sample by the focused illumination spot generated by the light source according to the minimum cross-sectional area of the sample specifically includes:
the method comprises the steps of obtaining the minimum cross section area of a sample along the thickness direction of the sample, and determining that the area of a reference area of a focusing illumination area formed on the sample by a focusing illumination spot generated by a light source is equal to half of the minimum cross section area;
in the step S1, adjusting a condensing degree of a light beam emitted by the light source by a focusing optical element inside the light source according to the area of the reference region, so that a spot area of a focused illumination spot generated by the light source is equal to the area of the reference region, specifically including:
and adjusting the beam reduction ratio of a focusing optical element in the light source to the beam area of the light beam emitted by the light source according to the area of the reference region, so that the spot area of the focused illumination spot generated by the light source is equal to the area of the reference region.
In an embodiment disclosed in the present application, in step S1, acquiring a horizontal cross-sectional image corresponding to each position in the thickness direction of the sample, and performing identification processing on each horizontal cross-sectional image specifically includes:
when an objective table of the microscope drives a sample to move in the Z direction for a preset step interval, a zoom objective of the microscope is instructed to carry out focusing shooting on a focusing illumination area formed by a focusing illumination spot generated by a light source in the sample, so that a horizontal section image corresponding to the position of the current focusing illumination area in the thickness direction of the sample is obtained;
and performing identification processing on the position of each horizontal sectional image in the thickness direction of the sample so that each horizontal sectional image corresponds to the position of each sample in the thickness direction in a one-to-one mode.
In an embodiment disclosed in the present application, in step S2, performing identification processing on each horizontal cross-sectional image to obtain sample structure feature information on a horizontal cross-section corresponding to each position in the thickness direction of the sample, specifically includes:
carrying out shape recognition processing on each horizontal section image to obtain the sample section shape structure feature information on the horizontal section corresponding to each position in the thickness direction of the sample; the sample profile topographic structure characteristic information comprises sample profile undulating structure distribution position information and sample profile undulating structure size information.
In an embodiment disclosed in the present application, in the step S2, determining, according to the sample structure feature information, a shooting reference point of a horizontal section corresponding to each position specifically includes:
extracting and obtaining distribution position information corresponding to the first three convex structures with the maximum curvature radius or distribution position information corresponding to the first three concave structures with the maximum curvature radius on the horizontal section corresponding to each position in the thickness direction of the sample from the sample structure characteristic information;
determining the central point of a triangle formed by the highest convex points of the first three convex structures with the maximum curvature radius according to the distribution position information corresponding to the first three convex structures with the maximum curvature radius; or determining the central point of a triangle formed by the lowest concave points of the first three concave structures with the maximum curvature radius according to the distribution position information corresponding to the first three concave structures with the maximum curvature radius;
and determining the central point as a shooting reference corresponding to each position in the thickness direction of the sample.
In an embodiment disclosed in the present application, in the step S3, when the light source forms a focused illumination area at each position in the thickness direction of the sample, the stage is instructed to drive the sample to perform horizontal two-dimensional movement according to the reference point, so as to obtain a plurality of horizontal cross-section sub-area images of different sub-areas of the horizontal cross section at each position in the thickness direction of the sample, specifically including:
when the light source forms a focusing illumination area on a horizontal section corresponding to each position in the thickness direction of the sample, instructing a zoom objective lens of a microscope to perform zooming and zooming operations by taking a shooting reference point corresponding to each position as a reference so as to enable the center of the current shooting field of view of the zoom objective lens to coincide with the shooting reference point, and instructing the zoom objective lens to perform first shooting in a fixed shooting field range;
when the zoom objective lens finishes the first shooting, the objective table is indicated to respectively move at preset step intervals along the X direction and the Y direction of a horizontal plane so as to drive the sample to horizontally move in two dimensions;
and when the objective table finishes moving for a preset step interval along the X direction and the Y direction of a horizontal plane, the zoom objective lens is instructed to shoot the current focusing illumination area of the horizontal section corresponding to each position in the thickness direction of the sample, so that a plurality of horizontal section subarea images of different subareas of the horizontal section at each position in the thickness direction of the sample are obtained.
In an embodiment disclosed in the present application, in step S3, performing identification processing on each horizontal cross-section sub-area image to obtain image feature information of each horizontal cross-section sub-area image, specifically including:
and carrying out image boundary identification processing on each horizontal section subregion image to obtain image texture feature information of the image boundary area of each horizontal section subregion image.
In an embodiment disclosed in the present application, in the step S4, according to the image feature information, performing a stitching process on all horizontal section sub-region images corresponding to a horizontal section at the same position to obtain a horizontal section global image, specifically including:
and determining all horizontal cross section sub-region images adjacent to the periphery of each horizontal cross section sub-region image corresponding to the horizontal cross section at the same position according to the image texture feature information, and splicing each horizontal cross section sub-region image and all horizontal cross section sub-region images adjacent to the periphery of the horizontal cross section sub-region image to obtain a horizontal cross section global image.
In an embodiment disclosed in the present application, in the step S4, the stitching processing is performed on the global images of the horizontal cross sections corresponding to all the horizontal cross sections to obtain a spatial three-dimensional microscopic image of the sample, and specifically includes:
splicing the horizontal section global images corresponding to all the horizontal sections according to the sequence from low to high of the corresponding positions of all the horizontal sections in the Z direction, so as to obtain a three-dimensional spliced sample image;
and carrying out pixel sharpening processing and image magnification unification processing on the three-dimensional spliced sample image so as to obtain a spatial three-dimensional microscopic image of the sample.
Compared with the prior art, the intelligent multi-dimensional microscopic image acquisition and processing method has the advantages that the sample is placed on the three-dimensional movable microscope objective table, the objective table is indicated to drive the sample to move in the Z direction, and the light source of the microscope is indicated to irradiate light rays to the sample, so that the sample structure characteristic information of the horizontal section image of each position in the thickness direction of the sample is obtained, and the horizontal section shooting reference point corresponding to each position is determined; taking the shooting reference point as a reference, indicating the objective table to drive the sample to horizontally move in two dimensions, and shooting to obtain a plurality of horizontal section subarea images of different subareas of the horizontal section at each position in the thickness direction of the sample; the method comprises the steps of splicing all horizontal section sub-area images corresponding to horizontal sections at the same position to form a horizontal section global image based on image characteristic information of each horizontal section sub-area image, splicing all horizontal section global images to obtain a spatial three-dimensional microscopic image related to a sample, driving the sample to move in the Z direction through an objective table to focus light source light at different positions in the thickness direction of the sample, facilitating a microscope to preliminarily shoot and screen the interior of the sample in the thickness direction, dividing the interior of the sample into a plurality of horizontal sections in the thickness direction of the sample, horizontally scanning and shooting each horizontal section in a two-dimensional manner to obtain a global image of each horizontal section, splicing all horizontal section global images to obtain a spatial three-dimensional microscopic image of the sample, collecting and splicing the images of different spatial layers in the sample to realize microscopic imaging of different dimensions in the sample, improving the image collecting comprehensiveness and multidimensional property of microscopic imaging, and providing sufficient image data for subsequent target object diagnosis.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
The technical solution of the present invention is further described in detail by the accompanying drawings and embodiments.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
Fig. 1 is a schematic flow diagram of an intelligent multi-dimensional microscopic image acquisition and processing method provided by the invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, fig. 1 is a schematic flow chart of an intelligent multi-dimensional microscopic image acquisition and processing method according to an embodiment of the present invention. The intelligent multi-dimensional microscopic image acquisition and processing method comprises the following steps:
step S1, a light source of an indicating microscope irradiates illumination light to a sample, and an objective table of the indicating microscope drives the sample to move in the Z direction, so that focusing illumination areas are formed at different positions in the thickness direction of the sample; acquiring a horizontal section image corresponding to each position in the thickness direction of the sample, and performing identification processing on each horizontal section image;
s2, identifying each horizontal section image to obtain sample structure characteristic information on the horizontal section corresponding to each position in the thickness direction of the sample; determining a shooting reference point of a horizontal section corresponding to each position according to the structural feature information of the sample;
s3, when the light source forms a focusing illumination area at each position in the thickness direction of the sample, the objective table is indicated to drive the sample to horizontally move in two dimensions according to the shooting reference point, and a plurality of horizontal section subarea images of different subareas of the horizontal section at each position in the thickness direction of the sample are shot; identifying each horizontal section subregion image to obtain image characteristic information of each horizontal section subregion image;
s4, according to the image characteristic information, splicing all horizontal section sub-area images corresponding to the horizontal section at the same position to obtain a horizontal section global image; and then splicing the horizontal section global images corresponding to all the horizontal sections to obtain a spatial three-dimensional microscopic image of the sample.
The beneficial effects of the above technical scheme are: this intelligent multi-dimensional microscopic image acquisition and processing method drives the sample through the objective table earlier and carries out the Z direction removal, so that light source light focuses on the different positions of sample self thickness direction, be convenient for the microscope to examine the inside preliminary shooting that carries out the thickness direction of sample, divide into a plurality of horizontal sections with this along sample thickness direction with the sample inside, carry out horizontal two-dimensional scanning to every horizontal section and shoot, obtain the universe image of every horizontal section, and splice the universe image of all horizontal sections, obtain the space three-dimensional microscopic image of sample, it is through carrying out image acquisition and concatenation to the inside different space aspect of sample, realize the microscopic imaging to the inside different dimensions of sample, improve the image acquisition comprehensiveness and the multidimension nature of microscopic imaging, provide sufficient image data for follow-up to the target object diagnosis.
Preferably, in step S1, the light source of the instruction microscope irradiates illumination light to the sample, and the stage of the instruction microscope drives the sample to move in the Z direction, so as to form focused illumination regions at different positions in the thickness direction of the sample, specifically including:
determining the reference area of a focused illumination area formed on the sample by a focused illumination spot generated by a light source according to the minimum cross-sectional area of the sample;
adjusting the condensation degree of a focusing optical element in the light source on the light beam emitted by the light source according to the area of the reference region, so that the area of a light spot of a focusing illumination light spot generated by the light source is equal to the area of the reference region;
an objective table of the microscope is instructed to drive a sample to move at preset step intervals in the Z direction so that a focusing illumination light spot generated by the light source enters the sample, and focusing illumination areas are formed at different positions in the thickness direction of the sample; wherein the Z direction is a direction perpendicular to the plane of the stage.
The beneficial effects of the above technical scheme are: in actual operation, a biological sample obtained from a target object can be pretreated to ensure that the biological sample has certain light transmittance, and light from a microscope light source can be irradiated into the biological sample. And determining the reference area of a focused illumination area formed on the sample by the focused illumination spot generated by the light source by taking the minimum cross-sectional area of the biological sample in the thickness direction of the biological sample as a reference, so that the focused illumination spot generated by the light source can form a sufficiently large illumination area on the sample. The objective table of the microscope is used for driving the sample to move in the Z direction at a preset step interval, when the sample moves at a preset step interval, the focusing illumination light spots generated by the light source can form corresponding focusing illumination areas on the horizontal section corresponding to a certain position in the thickness direction of the sample, so that the microscope can carry out initial shooting on the formed focusing illumination areas, and the initial analysis of structural characteristics is conveniently carried out on each horizontal section.
Preferably, in step S1, determining a reference area of a focused illumination area formed on the sample by the focused illumination spot generated by the light source according to the minimum cross-sectional area of the sample, specifically including:
the method comprises the steps of obtaining the minimum cross section area of a sample along the thickness direction of the sample, and determining that the area of a reference area of a focusing illumination area formed on the sample by a focusing illumination spot generated by a light source is equal to half of the minimum cross section area;
in step S1, adjusting a condensing degree of a light beam emitted by a light source by a focusing optical element inside the light source according to the area of the reference region, so that a spot area of a focused illumination spot generated by the light source is equal to the area of the reference region specifically includes:
and adjusting the beam shrinking ratio of a focusing optical element in the light source to the light beam area of the light beam emitted by the light source according to the area of the reference area, so that the light spot area of a focusing illumination light spot generated by the light source is equal to the area of the reference area.
The beneficial effects of the above technical scheme are: the area of a reference area of a focusing illumination area formed on the sample by a focusing illumination spot generated by the light source is set to be equal to half of the minimum cross-sectional area of the sample, so that the focusing illumination spot can form a large enough illumination area and sufficient illumination brightness on each horizontal section of the sample, and a microscope can clearly acquire structural details of the sample on the horizontal section. In addition, in practical application, different types of 4f optical systems such as a Galilean telescope optical system and the like can be arranged in the light source to serve as focusing optical elements, so that beam reduction processing with different proportions can be carried out on the cross section area of the light beam emitted by the light source, the cross section area of the light beam is increased or reduced, and the area of a focusing illumination spot generated by the light source is always equal to the area of the reference area.
Preferably, in step S1, acquiring a horizontal cross-sectional image corresponding to each position in the thickness direction of the sample, and performing identification processing on each horizontal cross-sectional image, specifically including:
when an objective table of the microscope drives a sample to move in the Z direction for a preset step interval, a zoom objective of the microscope is instructed to carry out focusing shooting on a focusing illumination area formed by a focusing illumination spot generated by the light source in the sample, so that a horizontal section image corresponding to the position of the current focusing illumination area in the thickness direction of the sample is obtained;
and performing identification processing on the position of each horizontal sectional image in the thickness direction of the sample so that each horizontal sectional image corresponds to the position of each sample in the thickness direction in a one-to-one mode.
The beneficial effects of the above technical scheme are: when the object stage of the microscope drives the sample to move in the Z direction by a preset step interval, the light source forms a corresponding focusing illumination area on a horizontal section corresponding to the corresponding position in the thickness direction of the sample, and at the moment, the zoom objective of the microscope can find and position the horizontal section where the current focusing illumination area is located, and focus and shoot the focusing illumination area in the positioned horizontal section to obtain a horizontal section image corresponding to the position of the current focusing illumination area in the thickness direction of the sample. Each horizontal section image corresponds to a specific position in the thickness direction of the sample, and identification processing about the position of the horizontal section image in the thickness direction of the sample is performed on each horizontal section image, so that sequential splicing and combination can be performed on all horizontal section universe images conveniently.
Preferably, in step S2, the identifying process is performed on each horizontal cross-sectional image to obtain the sample structural feature information on the horizontal cross-section corresponding to each position in the thickness direction of the sample, and the identifying process specifically includes:
carrying out shape recognition processing on each horizontal section image to obtain the sample section shape structure characteristic information on the horizontal section corresponding to each position in the thickness direction of the sample; the sample profile topographic structure characteristic information comprises sample profile undulating structure distribution position information and sample profile undulating structure size information.
The beneficial effects of the above technical scheme are: the topographic structure feature recognition processing is carried out on each horizontal section image, the distribution and size features of the fluctuation structure of each horizontal section can be obtained, the shooting datum points which are obvious in structure can be conveniently and accurately positioned on each horizontal section in the follow-up process, and therefore comprehensive scanning shooting of each horizontal section is achieved.
Preferably, in step S2, determining a reference point of the horizontal section corresponding to each position according to the sample structure feature information includes:
extracting and obtaining distribution position information corresponding to the first three convex structures with the maximum curvature radius or distribution position information corresponding to the first three concave structures with the maximum curvature radius on the horizontal section corresponding to each position in the thickness direction of the sample from the sample structure characteristic information;
determining the central point of a triangle formed by the highest convex points of the first three convex structures with the maximum curvature radius according to the distribution position information corresponding to the first three convex structures with the maximum curvature radius; or determining the central point of a triangle formed by the lowest concave points of the first three concave structures with the maximum curvature radius according to the distribution position information corresponding to the first three concave structures with the maximum curvature radius;
and determining the central point as a shooting reference point corresponding to each position in the thickness direction of the sample.
The beneficial effects of the above technical scheme are: through the mode, the shooting reference points corresponding to each position (namely each horizontal section) in the thickness direction of the sample are determined by taking the first three maximum curvature radiuses of the convex structures or the concave structures in the horizontal section as the reference, so that the object stage is indicated to drive the sample to move front and back, left and right in the X direction and the Y direction of the horizontal plane by taking each shooting reference point as the reference, and therefore comprehensive scanning micro-shooting of each horizontal section is achieved.
Preferably, in step S3, when the light source forms a focused illumination area at each position in the thickness direction of the sample, the stage is instructed to drive the sample to horizontally move in two dimensions according to the reference point, so as to obtain several horizontal cross-section sub-area images of different sub-areas of the horizontal cross section at each position in the thickness direction of the sample, which specifically includes:
when the light source forms a focusing illumination area on a horizontal section corresponding to each position in the thickness direction of the sample, instructing a zoom objective lens of a microscope to perform zooming and zooming operations by taking a shooting reference point corresponding to each position as a reference so as to enable the center of the current shooting field of view of the zoom objective lens to coincide with the shooting reference point, and instructing the zoom objective lens to perform first shooting in a fixed shooting field range;
after the zoom objective lens finishes the first shooting, the objective table is indicated to respectively move at preset step intervals along the X direction and the Y direction of a horizontal plane so as to drive the sample to horizontally move in two dimensions;
and when the objective table finishes moving for a preset step interval along the X direction and the Y direction of a horizontal plane, the zoom objective lens is instructed to shoot the current focusing illumination area of the horizontal section corresponding to each position in the thickness direction of the sample, so that a plurality of horizontal section subarea images of different subareas of the horizontal section at each position in the thickness direction of the sample are obtained.
The beneficial effects of the above technical scheme are: by the mode, the zoom objective of the microscope can be guaranteed to carry out comprehensive seamless scanning shooting on each horizontal section, and a plurality of horizontal section subarea images of different subareas of each horizontal section are obtained, so that the integral visual representation of each horizontal section is realized.
Preferably, in step S3, the identifying process is performed on each horizontal cross-section sub-area image to obtain image feature information of each horizontal cross-section sub-area image, and the identifying process specifically includes:
and carrying out image boundary identification processing on each horizontal section subregion image to obtain image texture feature information of the image boundary area of each horizontal section subregion image.
The beneficial effects of the above technical scheme are: and performing image boundary identification processing on each horizontal section subarea image to obtain image texture feature information of an image boundary area of each horizontal section subarea image, so that other horizontal section subarea images connected around each horizontal section subarea image can be determined by taking the image texture feature information as a reference, and the splicing correctness of the horizontal section subarea images is ensured.
Preferably, in step S4, according to the image feature information, the image splicing process is performed on all horizontal section sub-region images corresponding to the horizontal section at the same position to obtain a horizontal section global image, which specifically includes:
and determining all horizontal cross section sub-region images adjacent to the periphery of each horizontal cross section sub-region image corresponding to the horizontal cross section at the same position according to the image texture feature information, and splicing each horizontal cross section sub-region image and all horizontal cross section sub-region images adjacent to the periphery of the horizontal cross section sub-region image to obtain a horizontal cross section global image.
The beneficial effects of the above technical scheme are: by the method, all horizontal section sub-region images which belong to the same position in the thickness direction of the same sample can be correctly spliced, and the spliced horizontal section global image is ensured to be consistent with the corresponding horizontal section.
Preferably, in step S4, the stitching processing is performed on the horizontal cross section global images corresponding to all the horizontal cross sections to obtain a spatial three-dimensional microscopic image of the sample, and the method specifically includes:
splicing the horizontal section global images corresponding to all the horizontal sections according to the sequence from low to high of the corresponding positions of all the horizontal sections in the Z direction, so as to obtain a three-dimensional spliced sample image;
and carrying out pixel sharpening processing and image magnification uniformization processing on the three-dimensional spliced sample image so as to obtain a spatial three-dimensional microscopic image of the sample.
The beneficial effects of the above technical scheme are: by means of the mode, the horizontal section global images corresponding to all the horizontal sections are spliced according to the sequence from low to high of the positions of all the horizontal sections corresponding to the Z direction, and therefore the sample can be subjected to image representation in the three-dimensional X direction, the Y direction and the Z direction. In addition, pixel sharpening processing and image magnification uniformization processing are carried out on the three-dimensional spliced sample image, so that the image detail consistency of each horizontal section global image contained in the three-dimensional spliced sample image can be ensured, and the condition that the image distortion is caused due to the fact that the magnifications of different horizontal section global images in the three-dimensional spliced sample image are different is avoided.
According to the content of the embodiment, the intelligent multi-dimensional microscopic image collecting and processing method drives the sample to move in the Z direction through the objective table, so that light source light is focused at different positions in the thickness direction of the sample, a microscope is convenient to preliminarily shoot and discriminate the inside of the sample in the thickness direction, the inside of the sample is divided into a plurality of horizontal sections along the thickness direction of the sample, horizontal two-dimensional scanning and shooting are carried out on each horizontal section, the global image of each horizontal section is obtained, the global images of all the horizontal sections are spliced, the space three-dimensional microscopic image of the sample is obtained, image collecting and splicing are carried out on different space layers in the sample, microscopic imaging of different dimensions in the sample is realized, the image collecting comprehensiveness and the multi-dimensional performance of the microscopic imaging are improved, and sufficient image data are provided for subsequent target object diagnosis.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.
Claims (10)
1. The intelligent multi-dimensional microscopic image acquisition and processing method is characterized by comprising the following steps:
step S1, a light source of an indicating microscope irradiates illumination light to a sample, and an objective table of the indicating microscope drives the sample to move in the Z direction, so that focusing illumination areas are formed at different positions in the thickness direction of the sample; acquiring a horizontal section image corresponding to each position in the thickness direction of the sample, and performing identification processing on each horizontal section image;
s2, identifying each horizontal section image to obtain sample structure characteristic information on the horizontal section corresponding to each position in the thickness direction of the sample; determining a shooting reference point of a horizontal section corresponding to each position according to the sample structure characteristic information;
s3, when the light source forms a focusing illumination area at each position in the thickness direction of the sample, the objective table is indicated to drive the sample to horizontally move in two dimensions according to the shooting reference point, and a plurality of horizontal section subarea images of different subareas of the horizontal section at each position in the thickness direction of the sample are shot; identifying each horizontal section subarea image to obtain image characteristic information of each horizontal section subarea image;
s4, according to the image characteristic information, splicing all horizontal section sub-area images corresponding to the horizontal section at the same position to obtain a horizontal section global image; and then splicing the horizontal section global images corresponding to all the horizontal sections to obtain a spatial three-dimensional microscopic image of the sample.
2. The intelligent multi-dimensional microscopic image acquisition and processing method of claim 1, wherein:
in step S1, the light source of the instruction microscope irradiates illumination light to the sample, and the stage of the instruction microscope drives the sample to move in the Z direction, so as to form a focused illumination area at different positions in the thickness direction of the sample, specifically including:
determining the reference region area of a focused illumination region formed on the sample by a focused illumination spot generated by a light source according to the minimum cross-sectional area of the sample;
according to the area of the reference region, adjusting the condensation degree of a focusing optical element in the light source on the light beam emitted by the light source so as to enable the spot area of a focusing illumination spot generated by the light source to be equal to the area of the reference region;
indicating an objective table of the microscope to drive the sample to move at preset step intervals in the Z direction so that a focusing illumination spot generated by the light source enters the sample, and respectively forming focusing illumination areas at different positions in the thickness direction of the sample; wherein the Z direction is a direction perpendicular to the plane of the object stage.
3. The intelligent multi-dimensional microscopic image acquisition and processing method of claim 2, wherein:
in step S1, determining a reference area of a focused illumination area formed on the sample by the focused illumination spot generated by the light source according to the minimum cross-sectional area of the sample, specifically including:
the method comprises the steps of obtaining the minimum cross section area of a sample along the thickness direction of the sample, and determining that the area of a reference area of a focusing illumination area formed on the sample by a focusing illumination spot generated by a light source is equal to half of the minimum cross section area;
in step S1, adjusting a condensing degree of a light beam emitted by a light source by a focusing optical element inside the light source according to the area of the reference region, so that a spot area of a focused illumination spot generated by the light source is equal to the area of the reference region, specifically including:
and adjusting the beam reduction ratio of a focusing optical element in the light source to the light beam area of the light beam emitted by the light source according to the area of the reference region, so that the spot area of a focusing illumination spot generated by the light source is equal to the area of the reference region.
4. The intelligent multi-dimensional microscopic image acquisition and processing method of claim 3, wherein:
in step S1, acquiring a horizontal cross-sectional image corresponding to each position in the thickness direction of the sample, and performing identification processing on each horizontal cross-sectional image, specifically including:
when an objective table of the microscope drives a sample to move in the Z direction for a preset step interval, a zoom objective of the microscope is instructed to carry out focusing shooting on a focusing illumination area formed by a focusing illumination spot generated by a light source in the sample, so that a horizontal section image corresponding to the position of the current focusing illumination area in the thickness direction of the sample is obtained;
and performing identification processing on the position of each horizontal sectional image in the thickness direction of the sample so that each horizontal sectional image corresponds to the position of each sample in the thickness direction in a one-to-one mode.
5. The intelligent multi-dimensional microscopic image acquisition and processing method of claim 4, wherein:
in step S2, performing identification processing on each horizontal cross-sectional image to obtain sample structural feature information on a horizontal cross-section corresponding to each position in the sample thickness direction, specifically including:
carrying out shape recognition processing on each horizontal section image to obtain the sample section shape structure feature information on the horizontal section corresponding to each position in the thickness direction of the sample; the sample profile topographic structure characteristic information comprises sample profile undulating structure distribution position information and sample profile undulating structure size information.
6. The intelligent multi-dimensional microscopic image acquisition and processing method of claim 5, wherein:
in step S2, determining a reference point of the horizontal section corresponding to each position according to the sample structure feature information, specifically including:
extracting and obtaining distribution position information corresponding to the first three convex structures with the maximum curvature radius or distribution position information corresponding to the first three concave structures with the maximum curvature radius on the horizontal section corresponding to each position in the thickness direction of the sample from the sample structure characteristic information;
determining the central point of a triangle formed by the highest convex points of the first three convex structures with the maximum curvature radius according to the distribution position information corresponding to the first three convex structures with the maximum curvature radius; or determining the central point of a triangle formed by the lowest concave points of the first three concave structures with the maximum curvature radius according to the distribution position information corresponding to the first three concave structures with the maximum curvature radius;
and determining the central point as a shooting reference point corresponding to each position in the thickness direction of the sample.
7. The intelligent multi-dimensional microscopic image acquisition and processing method according to claim 6, characterized in that:
in the step S3, when the light source forms a focused illumination area at each position in the thickness direction of the sample, the stage is instructed to drive the sample to perform horizontal two-dimensional movement according to the reference point, so as to obtain a plurality of horizontal cross-section sub-area images of different sub-areas of the horizontal cross section at each position in the thickness direction of the sample by shooting, which specifically includes:
when the light source forms a focusing illumination area on a horizontal section corresponding to each position in the thickness direction of the sample, instructing a zoom objective lens of the microscope to perform zooming and zooming operations by taking a shooting reference point corresponding to each position as a reference so as to enable the current shooting field center of the zoom objective lens to coincide with the shooting reference point, and instructing the zoom objective lens to perform first shooting in a fixed shooting field range;
after the zoom objective lens finishes the first shooting, the objective table is indicated to respectively move at preset step intervals along the X direction and the Y direction of a horizontal plane so as to drive the sample to horizontally move in two dimensions;
when the objective table finishes moving for a preset step interval along the X direction and the Y direction of a horizontal plane, the zoom objective lens is instructed to shoot the current focusing illumination area of the horizontal section corresponding to each position in the thickness direction of the sample, so that a plurality of horizontal section sub-area images of different sub-areas of the horizontal section at each position in the thickness direction of the sample are obtained.
8. The intelligent multi-dimensional microscopic image acquisition and processing method of claim 7, wherein:
in step S3, performing identification processing on each horizontal cross section sub-area image to obtain image feature information of each horizontal cross section sub-area image, which specifically includes:
and carrying out image boundary identification processing on each horizontal section subregion image to obtain image texture feature information of the image boundary area of each horizontal section subregion image.
9. The intelligent multi-dimensional microscopic image acquisition and processing method of claim 8, wherein:
in step S4, according to the image feature information, performing a stitching process on all the horizontal section sub-region images corresponding to the horizontal section at the same position to obtain a horizontal section global image, which specifically includes:
and determining all horizontal section sub-region images adjacent to the periphery of each horizontal section sub-region image corresponding to the horizontal section at the same position according to the image texture feature information, and splicing each horizontal section sub-region image and all horizontal section sub-region images adjacent to the periphery of the horizontal section sub-region image to obtain a horizontal section global image.
10. The intelligent multi-dimensional microscopic image acquisition and processing method according to claim 9, characterized in that:
in step S4, the stitching processing is performed on the horizontal section global images corresponding to all the horizontal sections to obtain a spatial three-dimensional microscopic image of the sample, and the stitching processing specifically includes:
splicing the horizontal section global images corresponding to all the horizontal sections according to the sequence from low to high of the corresponding positions of all the horizontal sections in the Z direction, so as to obtain a three-dimensional spliced sample image;
and carrying out pixel sharpening processing and image magnification uniformization processing on the three-dimensional spliced sample image so as to obtain a spatial three-dimensional microscopic image of the sample.
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