CN110706206A - Fluorescent cell counting method, fluorescent cell counting device, terminal equipment and storage medium - Google Patents
Fluorescent cell counting method, fluorescent cell counting device, terminal equipment and storage medium Download PDFInfo
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Abstract
The embodiment of the application is applicable to the technical field of computers, and discloses a fluorescent cell counting method, a fluorescent cell counting device, terminal equipment and a computer-readable storage medium, wherein the method comprises the following steps: acquiring a fluorescence image to be counted, wherein the fluorescence image comprises at least one cell subjected to immunofluorescence staining; carrying out binarization processing on the fluorescence image to obtain a binarized image; identifying a cell area in the binary image according to a preset cell area parameter; the number of fluorescent cells in the fluorescence image was counted based on the cell area. The embodiment of the application automatically identifies the cell area in the binary image by directly converting the fluorescent image into the binary image, and then counts the number of the fluorescent cells based on the cell area, thereby reducing the counting steps, automatically identifying and counting the cell area, improving the counting efficiency and the counting accuracy, and being simple and convenient to operate.
Description
Technical Field
The present application belongs to the field of computer technologies, and in particular, to a fluorescent cell counting method, apparatus, terminal device, and computer-readable storage medium.
Background
Immunofluorescence staining can stain specific types of cells, show fluorescence under laser irradiation, form color difference with background, and perform fluorescence cell counting based on the fluorescence cell staining.
Currently, there are few methods for counting the number of fluorescent cells, and there are great disadvantages in the efficiency and accuracy of counting. That is, the conventional fluorescent cell counting method has a problem that it is not possible to automatically count fluorescent cells at a high speed, and it is necessary for an experimenter to perform a plurality of operations to count cells, thereby wasting time. In addition, in the prior art, the method is integrated in a software system, the operation is complex, each picture to be counted needs to be completed by multiple continuous operations, and the method is tedious and tedious.
Disclosure of Invention
The embodiment of the application provides a fluorescent cell counting method, a fluorescent cell counting device, terminal equipment and a computer readable storage medium, and aims to solve the problems of low counting efficiency and accuracy and complex operation of the existing fluorescent cell counting method.
In a first aspect, embodiments of the present application provide a fluorescence cell counting method, including:
acquiring a fluorescence image to be counted, wherein the fluorescence image comprises at least one cell subjected to immunofluorescence staining;
carrying out binarization processing on the fluorescence image to obtain a binarized image;
identifying a cell area in the binary image according to a preset cell area parameter;
counting the number of fluorescent cells in the fluorescent image based on the cell region.
With reference to the first aspect, in a possible implementation manner, the grayscale value of the fluorescent cells in the binarized image is a first value, and the grayscale value of the background color is a second value;
the identifying the cell area in the binary image according to the preset cell area parameter comprises the following steps:
reading the gray value of each pixel point in the binary image;
connecting adjacent pixel points with the gray values as first numerical values to form a to-be-selected area;
respectively calculating the area of each region to be selected;
and screening target regions with areas meeting the preset cell area parameters from the regions to be selected, and taking the target regions as the cell regions.
With reference to the first aspect, in a possible implementation manner, the screening out, from each candidate region, a target region having an area that meets the preset cell area parameter includes:
and taking the area of the candidate area which is larger than 30 pixels and smaller than 1000 pixels as the target area.
With reference to the first aspect, in a possible implementation manner, the counting the number of fluorescent cells in the fluorescent image based on the cell region includes:
marking each cell area in the fluorescence image by using a preset mark to obtain a marked fluorescence image;
and counting the number of the marks in the marked fluorescence image to obtain the number of the fluorescence cells in the fluorescence image.
With reference to the first aspect, in a possible implementation manner, the counting the number of fluorescent cells in the fluorescent image based on the cell region includes:
and counting the number of the cell areas in the binary image to obtain the number of the fluorescent cells in the fluorescent image.
With reference to the first aspect, in a possible implementation manner, after the counting the number of fluorescent cells in the fluorescent image based on the cell region, the method further includes:
calculating the picture size of the fluorescence image;
and calculating the actual area of the slice tissue corresponding to the fluorescence image according to the size of the fluorescence image.
In a second aspect, embodiments of the present application provide a fluorescent cell counting apparatus, including:
the device comprises an image acquisition module, a counting module and a counting module, wherein the image acquisition module is used for acquiring a fluorescence image to be counted, and the fluorescence image comprises at least one cell subjected to immunofluorescence staining;
the binarization module is used for carrying out binarization processing on the fluorescent image to obtain a binarization image;
the cell identification module is used for identifying a cell area in the binary image according to a preset cell area parameter;
and the counting module is used for counting the number of the fluorescent cells in the fluorescent image based on the cell region.
With reference to the second aspect, in a possible implementation manner, the grayscale value of the fluorescent cells in the binarized image is a first value, and the grayscale value of the background color is a second value;
the cell recognition module is specifically configured to:
reading the gray value of each pixel point in the binary image;
connecting adjacent pixel points with the gray values as first numerical values to form a to-be-selected area;
respectively calculating the area of each region to be selected;
and screening target regions with areas meeting the preset cell area parameters from the regions to be selected, and taking the target regions as the cell regions.
With reference to the second aspect, in one possible implementation manner, the cell identification module is specifically configured to:
and taking the area of the candidate area which is larger than 30 pixels and smaller than 1000 pixels as the target area.
With reference to the second aspect, in a possible implementation manner, the statistics module is specifically configured to:
marking each cell area in the fluorescence image by using a preset mark to obtain a marked fluorescence image;
and counting the number of the marks in the marked fluorescence image to obtain the number of the fluorescence cells in the fluorescence image.
With reference to the second aspect, in a possible implementation manner, the statistics module is specifically configured to:
and counting the number of the cell areas in the binary image to obtain the number of the fluorescent cells in the fluorescent image.
With reference to the second aspect, in a possible implementation manner, the method further includes:
the picture size calculation module is used for calculating the picture size of the fluorescent image;
and the slice area calculation module is used for calculating the actual area of the slice tissue corresponding to the fluorescence image according to the picture size of the fluorescence image.
In a third aspect, an embodiment of the present application provides a terminal device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor, when executing the computer program, implements the method according to any one of the above first aspects.
In a fourth aspect, embodiments of the present application provide a computer-readable storage medium, which stores a computer program, and when the computer program is executed by a processor, the computer program implements the method according to any one of the above first aspects.
In a fifth aspect, the present application provides a computer program product, which when run on a terminal device, causes the terminal device to execute the method of any one of the above first aspects.
The embodiment of the application automatically identifies the cell area in the binary image by directly converting the fluorescent image into the binary image, and then counts the number of the fluorescent cells based on the cell area, thereby reducing the counting steps, automatically identifying and counting the cell area, improving the counting efficiency and the counting accuracy and being simple and convenient to operate.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the embodiments or the prior art descriptions will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without inventive exercise.
FIG. 1 is a schematic block diagram of a flow chart of a fluorescence cell counting method according to an embodiment of the present disclosure;
fig. 2 is a schematic diagram of a binarized image of a rat brain tissue section provided in an embodiment of the present application;
fig. 3 is a schematic block diagram of a specific flow of step S103 according to an embodiment of the present disclosure;
FIG. 4 is a block diagram schematically illustrating the structure of a fluorescent cell counting apparatus according to an embodiment of the present disclosure;
fig. 5 is a schematic structural diagram of a terminal device according to an embodiment of the present application.
Detailed Description
In the following description, for purposes of explanation and not limitation, specific details are set forth, such as particular system structures, techniques, etc. in order to provide a thorough understanding of the embodiments of the present application.
It will be understood that the terms "comprises" and/or "comprising," when used in this specification and the appended claims, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
It should also be understood that the term "and/or" as used in this specification and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.
As used in this specification and the appended claims, the term "if" may be interpreted contextually as "when", "upon" or "in response to" determining "or" in response to detecting ". Similarly, the phrase "if it is determined" or "if a [ described condition or event ] is detected" may be interpreted contextually to mean "upon determining" or "in response to determining" or "upon detecting [ described condition or event ]" or "in response to detecting [ described condition or event ]".
Furthermore, in the description of the present application and the appended claims, the terms "first," "second," "third," and the like are used for distinguishing between descriptions and not necessarily for describing or implying relative importance.
Reference throughout this specification to "one embodiment" or "some embodiments," or the like, means that a particular feature, structure, or characteristic described in connection with the embodiment is included in one or more embodiments of the present application. Thus, appearances of the phrases "in one embodiment," "in some embodiments," "in other embodiments," or the like, in various places throughout this specification are not necessarily all referring to the same embodiment, but rather "one or more but not all embodiments" unless specifically stated otherwise. The terms "comprising," "including," "having," and variations thereof mean "including, but not limited to," unless expressly specified otherwise.
The fluorescent cell counting scheme provided by the embodiment of the application can be applied to cell counting of brain tissue slices, and the types of the brain tissue slices can be arbitrary, for example, brain tissue slices of rats and mice. Of course, the method can also be applied to other tissue slices, and is not limited herein.
In a specific application, the fluorescent cell counting protocol may be applied to a terminal device, which may be of any type, for example, a computer. And the implementation manner of the fluorescent cell counting scheme may also be arbitrary, for example, in the embodiment of the present application, the fluorescent cell counting scheme may be implemented by Matlab, that is, each step of the fluorescent cell counting scheme is implemented by one Matlab file.
The technical solutions provided in the embodiments of the present application will be described below with specific embodiments.
Referring to fig. 1, a schematic flow chart of a fluorescence cell counting method according to an embodiment of the present disclosure is provided, which may include the following steps:
step S101, acquiring a fluorescence image to be counted, wherein the fluorescence image comprises at least one cell subjected to immunofluorescence staining.
It is understood that the fluorescence image refers to an immunofluorescent-stained tissue section image, which may be a tissue section imaged under a microscope. After immunofluorescence staining, specific cells in the tissue section are stained, and the stained cells show fluorescence under laser irradiation and form color difference with an image background.
It is noted that the tissue slice image may be an image of any tissue slice, for example, a rat brain tissue slice image.
And S102, carrying out binarization processing on the fluorescence image to obtain a binarized image.
The method of the binarization processing may be any conventional method, and is not limited herein. Specifically, a corresponding gray level threshold value is set, and then binarization operation is performed according to the gray level threshold value so as to convert the fluorescent image into a binarized image. The gray threshold may be specifically set according to experimental requirements and application requirements, and is not limited herein.
The binary image comprises pixel points with the gray value of 1 and the gray value of 0. In general, the grayscale value of the background region is 1, the grayscale value of the fluorescence-labeled cell is 1, that is, the black region in the binarized image is the background region, and the white region is the fluorescence-labeled cell region. Specifically, referring to fig. 2, which is a schematic diagram of a binarized image of a brain tissue slice of a rat and a mouse, the black areas in fig. 2 are all the backgrounds of the brain tissue slice of the rat and the white areas are cells labeled with fluorescence.
Of course, in some other embodiments, the grayscale value of the fluorescent cell may be set to 0, and the grayscale value of the background region may be set to 1, in which case, the black region in the binarized image is the fluorescent cell and the white region is the background region.
And S103, identifying a cell area in the binary image according to a preset cell area parameter.
The preset cell area parameter is a parameter for defining which regions in the binarized image are cells. The preset cell area parameter can be adjusted according to the difference of the counted cell volumes, the larger the counted cell volume is, the larger the preset cell area parameter is, and on the contrary, the smaller the counted cell volume is, the smaller the preset cell area parameter is. For example, the predetermined cell area parameter is greater than 30 pixels and less than 1000 pixels.
Identifying the cell region in the binarized image may refer to determining or judging which region in the binarized image is the cell region. Specifically, a region with an area meeting the requirement can be screened out according to a preset cell area parameter, and the region can be defined as a cell region. Typically, one cellular region corresponds to one cell.
For example, the preset cell area parameter is greater than 30 pixels and less than 1000 pixels, the black area in the binarized image is a background area, the white area is a fluorescent cell area, at this time, the area of each white area is calculated, and the white area with the area greater than 30 pixels and less than 1000 pixels is defined as a cell area, so that the cell area in the binarized image is automatically identified.
After automatically identifying the cell region in the binarized image according to the preset cell area parameter, fluorescent cell counting may be performed based on the cell region.
And step S104, counting the number of fluorescent cells in the fluorescent image based on the cell area.
In specific application, after the cell area in the binary image is determined, fluorescent cells can be directly counted based on the binary image, namely the number of the cell area in the binary image is counted, and the number of the cell area is the number of the fluorescent cells in the fluorescent image; or labeling each cell in the fluorescent image by using a preset label based on the cell area in the binary image, wherein each label corresponds to one cell, so that the number of the fluorescent cells can be obtained by the number of the labels in the fluorescent image.
That is, in some embodiments, the above-mentioned specific process of counting the number of fluorescent cells in the fluorescent image based on the cell region may include: marking each cell area in the fluorescence image by using a preset mark to obtain a marked fluorescence image; and counting the number of the marks in the marked fluorescence image to obtain the number of the fluorescence cells in the fluorescence image.
It should be noted that the preset mark may be, but is not limited to, a red circle, that is, each cell region is circled by a red circle in the fluorescence image. Therefore, besides convenient cell counting, cells in a fluorescence image can be observed more intuitively, especially, a certain area is provided with a plurality of cells, the distance between the plurality of cells is very short, if a preset mark is not used, the area can not be seen intuitively to have a plurality of cells in total, and after the preset mark is used for marking, the area can be seen intuitively to have a plurality of cells.
After labeling, since one label corresponds to one cell, the number of labeled cells can be counted to obtain the number of fluorescent cells in the fluorescence image.
Of course, in other embodiments, the above-mentioned specific process of counting the number of fluorescent cells in the fluorescent image based on the cell region may include: and counting the number of the cell areas in the binary image to obtain the number of the fluorescent cells in the fluorescent image. Directly counting the number of cell areas in the binary image, wherein the number of the cell areas is the number of the fluorescent cells.
In addition, in order to observe the cells in the binarized image more intuitively, each cell region in the binarized image may also be labeled with a preset label.
It can be seen that the cell area in the binary image is automatically identified by directly converting the fluorescent image into the binary image, and then the number of the fluorescent cells is counted based on the self-cell area, so that the identification and counting of the cells are completed in one step, step-by-step operation is not needed, the steps are reduced, the cell area can be automatically identified and counted, the counting efficiency and the counting accuracy are improved, and the operation is simple and convenient.
In some embodiments, referring to the specific flow schematic block diagram of step S103 shown in fig. 3, the grayscale value of the fluorescent cells in the binarized image is a first value, and the grayscale value of the background color is a second value. The first value may be 1, and correspondingly, the second value is 0. Of course, the first value may also be 0 and the second value is correspondingly 1.
At this time, the specific process of identifying the cell region in the binarized image according to the preset cell area parameter may include:
and S301, reading the gray value of each pixel point in the binary image.
Step S302, connecting the adjacent pixel points with the gray values as the first numerical values to form a candidate area.
Specifically, the gray values of all pixel points in the binary image are obtained, and the gray values of all the pixel points are distinguished. And connecting the pixel points with the gray values as the second numerical values to form a background area of the picture, and connecting the adjacent pixel points with the gray values as the first numerical values to form each to-be-selected area with a certain area size.
For example, when the first value is 0 and the second value is 1, an image as shown in fig. 2 can be obtained after pixel point connection is performed according to the gray value, where the white area is the above-mentioned candidate area.
And step S303, calculating the area of each region to be selected respectively.
And S304, screening target areas with areas meeting preset cell area parameters from the areas to be selected, and taking the target areas as cell areas.
Specifically, the area of each region to be selected is calculated respectively, a target region meeting the area parameter requirement is screened from each region to be selected according to the area, and the screened target region is defined as a cell region.
For the related introduction of the preset cell parameters, please refer to the above corresponding contents, which are not described herein again.
Specifically, the process of screening the target region having an area meeting the preset cell area parameter from each candidate region may include: and taking the area of the candidate area which is larger than 30 pixels and smaller than 1000 pixels as a target area.
After the cell region in the binarized image is automatically identified and the number of cells is counted, the size of the fluorescence image can be further calculated, and then the actual area of the actual slice assembly is calculated according to the fluorescence image. That is, after counting the number of fluorescent cells in the fluorescent image based on the cell region, the method may further include: calculating the size of the fluorescent image; and calculating the actual area of the slice tissue corresponding to the fluorescence image according to the size of the fluorescence image.
In a specific application, the actual area of the tissue slice can be automatically calculated according to the actual area of the slice, i.e. pixel/resolution.
In the embodiments of the present application, the fluorescent cell counting protocol can be realized by a Matlab program file. The method specifically comprises the following steps: after inputting a fluorescent picture storage path and a picture name, automatically reading a required fluorescent picture; adjusting a gray threshold value according to actual needs, converting the read fluorescent image into a binary image, and displaying the binary image; reading gray values of all pixel points in the binary image, and connecting adjacent pixel points with the gray value of 1 to form a plurality of areas; calculating the area of a region formed by connecting all adjacent pixel points with the gray value of 1; then screening out the area with the area larger than 30 pixel points and smaller than 1000 pixel points, and defining the area as a cell area; according to the determined cell area, the red circle is used for circling the cells in the fluorescence image, and the marked original fluorescence image is displayed; automatically counting the number of fluorescent cells in the fluorescent image; and finally, calculating the actual area of the tissue section according to the size of the read fluorescence image.
It should be understood that, the sequence numbers of the steps in the foregoing embodiments do not imply an execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation to the implementation process of the embodiments of the present application.
Fig. 4 is a block diagram showing a schematic structure of a fluorescent cell counting apparatus provided in an embodiment of the present application, corresponding to the fluorescent cell counting method described in the above embodiment.
Referring to fig. 4, the fluorescent cell counting apparatus may include:
an image acquisition module 41, configured to acquire a fluorescence image to be counted, where the fluorescence image includes at least one cell stained by immunofluorescence;
a binarization module 42, configured to perform binarization processing on the fluorescent image to obtain a binarized image;
a cell identification module 43, configured to identify a cell region in the binarized image according to a preset cell area parameter;
and a counting module 44 for counting the number of fluorescent cells in the fluorescent image based on the cell region.
In one possible implementation, the gray value of the fluorescent cells in the binary image is a first value, and the gray value of the background color is a second value; the cell recognition module may be specifically configured to:
reading the gray value of each pixel point in the binary image;
connecting adjacent pixel points with the gray values as first numerical values to form a to-be-selected area;
respectively calculating the area of each region to be selected;
and screening target regions with areas meeting preset cell area parameters from the regions to be selected, and taking the target regions as cell regions.
In a possible implementation manner, the cell identification module may be specifically configured to:
and taking the area of the candidate area which is larger than 30 pixels and smaller than 1000 pixels as a target area.
In a possible implementation manner, the statistical module may be specifically configured to:
marking each cell area in the fluorescence image by using a preset mark to obtain a marked fluorescence image;
and counting the number of the marks in the marked fluorescence image to obtain the number of the fluorescence cells in the fluorescence image.
In a possible implementation manner, the statistical module may be specifically configured to:
and counting the number of the cell areas in the binary image to obtain the number of the fluorescent cells in the fluorescent image.
In a possible implementation manner, the apparatus may further include:
the picture size calculation module is used for calculating the picture size of the fluorescent image;
and the slice area calculation module is used for calculating the actual area of the slice tissue corresponding to the fluorescence image according to the picture size of the fluorescence image.
It should be noted that, the above fluorescent cell counting device and the above fluorescent cell counting method correspond to each other, and the same or similar parts can be referred to the above corresponding contents, and are not described herein again.
It should be noted that, for the content of information interaction, execution process, and the like between the above-mentioned devices or modules, the specific functions and technical effects thereof are based on the same concept as those of the embodiment of the method of the present application, and specific reference may be made to the part of the embodiment of the method, and details are not described here.
Fig. 5 is a schematic structural diagram of a terminal device according to an embodiment of the present application. As shown in fig. 5, the terminal device 5 of this embodiment includes: at least one processor 50, a memory 51, and a computer program 52 stored in the memory 51 and executable on the at least one processor 50, the processor 50 implementing the steps in any of the various fluorescence cell counting method embodiments described above when executing the computer program 52.
The terminal device 5 may be a desktop computer, a notebook, a palm computer, a cloud server, or other computing devices. The terminal device may include, but is not limited to, a processor 50, a memory 51. Those skilled in the art will appreciate that fig. 5 is only an example of the terminal device 5, and does not constitute a limitation to the terminal device 5, and may include more or less components than those shown, or combine some components, or different components, such as an input-output device, a network access device, and the like.
The Processor 50 may be a Central Processing Unit (CPU), and the Processor 50 may be other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic device, discrete hardware component, or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The memory 51 may in some embodiments be an internal storage unit of the terminal device 5, such as a hard disk or a memory of the terminal device 5. The memory 51 may also be an external storage device of the terminal device 5 in other embodiments, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like, which are provided on the terminal device 5. Further, the memory 51 may also include both an internal storage unit and an external storage device of the terminal device 5. The memory 51 is used for storing an operating system, an application program, a BootLoader (BootLoader), data, and other programs, such as program codes of the computer program. The memory 51 may also be used to temporarily store data that has been output or is to be output.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-mentioned division of the functional units and modules is illustrated, and in practical applications, the above-mentioned function distribution may be performed by different functional units and modules according to needs, that is, the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-mentioned functions. Each functional unit and module in the embodiments may be integrated in one processing unit, or each unit may exist alone physically, or two or more units are integrated in one unit, and the integrated unit may be implemented in a form of hardware, or in a form of software functional unit. In addition, specific names of the functional units and modules are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present application. The specific working processes of the units and modules in the system may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
The present application further provides a computer-readable storage medium, which stores a computer program, and when the computer program is executed by a processor, the computer program can implement the steps in the above-mentioned embodiments of the fluorescence cell counting method.
The embodiments of the present application provide a computer program product, which when executed on a terminal device, enables the terminal device to implement the steps in the foregoing respective embodiments of the fluorescence cell counting method.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, all or part of the processes in the methods of the embodiments described above can be implemented by a computer program, which can be stored in a computer-readable storage medium and can implement the steps of the embodiments of the methods described above when the computer program is executed by a processor. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer readable medium may include at least: any entity or device capable of carrying computer program code to a photographing apparatus/terminal apparatus, a recording medium, computer Memory, Read-Only Memory (ROM), random-access Memory (RAM), an electrical carrier signal, a telecommunications signal, and a software distribution medium. Such as a usb-disk, a removable hard disk, a magnetic or optical disk, etc. In certain jurisdictions, computer-readable media may not be an electrical carrier signal or a telecommunications signal in accordance with legislative and patent practice.
In the above embodiments, the descriptions of the respective embodiments have respective emphasis, and reference may be made to the related descriptions of other embodiments for parts that are not described or illustrated in a certain embodiment.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus/network device and method may be implemented in other ways. For example, the above-described apparatus/network device embodiments are merely illustrative, and for example, the division of the modules or units is only one logical division, and there may be other divisions when actually implementing, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not implemented. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
The above-mentioned embodiments are only used for illustrating the technical solutions of the present application, and not for limiting the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not substantially depart from the spirit and scope of the embodiments of the present application and are intended to be included within the scope of the present application.
Claims (10)
1. A method of fluorescent cell counting, comprising:
acquiring a fluorescence image to be counted, wherein the fluorescence image comprises at least one cell subjected to immunofluorescence staining;
carrying out binarization processing on the fluorescence image to obtain a binarized image;
identifying a cell area in the binary image according to a preset cell area parameter;
counting the number of fluorescent cells in the fluorescent image based on the cell region.
2. The fluorescent cell counting method according to claim 1, wherein the fluorescent cell gray value in the binarized image is a first value, and the background color gray value is a second value;
the identifying the cell area in the binary image according to the preset cell area parameter comprises the following steps:
reading the gray value of each pixel point in the binary image;
connecting adjacent pixel points with the gray values as first numerical values to form a to-be-selected area;
respectively calculating the area of each region to be selected;
and screening target regions with areas meeting the preset cell area parameters from the regions to be selected, and taking the target regions as the cell regions.
3. The fluorescent cell counting method according to claim 2, wherein the step of screening the target region with an area meeting the preset cell area parameter from each of the candidate regions comprises:
and taking the area of the candidate area which is larger than 30 pixels and smaller than 1000 pixels as the target area.
4. The fluorescent cell counting method of claim 1, wherein the counting the number of fluorescent cells in the fluorescent image based on the cell region comprises:
marking each cell area in the fluorescence image by using a preset mark to obtain a marked fluorescence image;
and counting the number of the marks in the marked fluorescence image to obtain the number of the fluorescence cells in the fluorescence image.
5. The fluorescent cell counting method of claim 1, wherein the counting the number of fluorescent cells in the fluorescent image based on the cell region comprises:
and counting the number of the cell areas in the binary image to obtain the number of the fluorescent cells in the fluorescent image.
6. The fluorescent cell counting method according to any one of claims 1 to 5, further comprising, after the counting the number of fluorescent cells in the fluorescent image based on the cell region:
calculating the picture size of the fluorescence image;
and calculating the actual area of the slice tissue corresponding to the fluorescence image according to the size of the fluorescence image.
7. A fluorescent cell counting device, comprising:
the device comprises an image acquisition module, a counting module and a counting module, wherein the image acquisition module is used for acquiring a fluorescence image to be counted, and the fluorescence image comprises at least one cell subjected to immunofluorescence staining;
the binarization module is used for carrying out binarization processing on the fluorescent image to obtain a binarization image;
the cell identification module is used for identifying a cell area in the binary image according to a preset cell area parameter;
and the counting module is used for counting the number of the fluorescent cells in the fluorescent image based on the cell region.
8. The fluorescent cell counting device according to claim 7, wherein the fluorescent cell gray scale value in the binarized image is a first value, and the background color gray scale value is a second value;
the cell recognition module is specifically configured to:
reading the gray value of each pixel point in the binary image;
connecting adjacent pixel points with the gray values as first numerical values to form a to-be-selected area;
respectively calculating the area of each region to be selected;
and screening target regions with areas meeting the preset cell area parameters from the regions to be selected, and taking the target regions as the cell regions.
9. A terminal device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that the processor implements the method according to any of claims 1 to 6 when executing the computer program.
10. A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the method according to any one of claims 1 to 6.
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