CN111583175B - Erythrocyte image detection method, erythrocyte image detection equipment and erythrocyte image detection medium - Google Patents
Erythrocyte image detection method, erythrocyte image detection equipment and erythrocyte image detection medium Download PDFInfo
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Abstract
The embodiment of the application provides a method, equipment and medium for detecting a red blood cell image, which are used for acquiring a corresponding red blood cell image and acquiring a corresponding red blood cell gray-scale image according to the red blood cell image; performing edge detection on the red blood cell gray-scale image to obtain a corresponding red blood cell edge information image; based on expansion operation, processing the erythrocyte edge information image to obtain a corresponding erythrocyte expansion fusion image; performing closed operation treatment on the erythrocyte expansion fusion image to obtain an erythrocyte segmentation image; determining a plurality of connected domains in the red blood cell segmentation image; and counting the number of the red blood cells in the red blood cell image according to the plurality of connected domains in the red blood cell segmentation image. Through the scheme, the erythrocyte detection efficiency can be improved to a great extent, the accuracy of erythrocyte quantity statistics is improved, and the influence of the detection environment is reduced.
Description
Technical Field
The application relates to the technical field of biological detection, in particular to a red blood cell image detection method, a red blood cell image detection device and a red blood cell image detection medium.
Background
Red blood cells are transport carriers of oxygen molecules of human bodies, the content and morphological characteristics of the red blood cells are main parameters of human health, and red blood cell detection is an important content of clinical pathological change detection.
At present, the main mode of erythrocyte detection is an electrical impedance-based quantitative erythrocyte detection method for counting the number of erythrocytes, but the method is greatly influenced by environment, has low accuracy, has low statistical accuracy of the number of erythrocytes, and cannot effectively acquire the morphological structure of erythrocytes.
Based on this, how to improve the accuracy of red blood cell detection and the accuracy of red blood cell count statistics is an important technical problem.
Disclosure of Invention
The embodiment of the specification provides a red blood cell image detection method, equipment and medium, which are used for solving the following technical problems in the prior art: the erythrocyte detection accuracy is low, the influence of the environment is large, and the accuracy of the erythrocyte quantity statistics is low.
The embodiment of the specification adopts the following technical scheme:
a method of erythrocyte image detection, the method comprising:
acquiring a corresponding red blood cell image, and acquiring a corresponding red blood cell graying image according to the red blood cell image;
performing edge detection on the red blood cell gray-scale image to obtain a corresponding red blood cell edge information image;
based on expansion operation, processing the erythrocyte edge information image to obtain a corresponding erythrocyte expansion fusion image;
performing closed operation treatment on the erythrocyte expansion fusion image to obtain an erythrocyte segmentation image;
determining a plurality of connected domains in the red blood cell segmentation image;
and counting the number of the red blood cells in the red blood cell image according to the plurality of connected domains in the red blood cell segmentation image.
In one possible implementation manner, the obtaining a corresponding erythrocyte grayscale image according to the erythrocyte image specifically includes:
decomposing the red blood cell image into a green single-channel image;
and carrying out gray processing on the green single-channel image to obtain a corresponding red blood cell gray image.
In one possible implementation, before obtaining the corresponding red blood cell edge information image, the method further includes:
and filtering the erythrocyte grayscale image to eliminate salt and pepper noise of the erythrocyte grayscale image.
In one possible implementation, before obtaining the corresponding erythrocyte expansion fusion image, the method further comprises:
according to a preset threshold value, performing threshold segmentation on the erythrocyte grayscale image to obtain an erythrocyte grayscale image with reserved erythrocyte bodies; or alternatively
And according to a preset threshold, performing threshold segmentation on the erythrocyte edge information image to obtain an erythrocyte edge information image of reserved erythrocyte bodies.
In one possible implementation, before obtaining the red blood cell segmentation image, the method further comprises:
performing corresponding calculation according to the erythrocyte expansion fusion image, and determining a plurality of connected domains in the erythrocyte expansion fusion image;
determining whether the area of each connected domain is smaller than a corresponding preset threshold value;
and filling the communication domain under the condition that the area of the communication domain is smaller than a corresponding preset threshold value.
In one possible implementation, the red blood cells include normal state red blood cells, abnormal state red blood cells;
counting the number of red blood cells in the red blood cell image according to the plurality of connected domains in the red blood cell segmentation image, wherein the method specifically comprises the following steps:
calculating the circularity of each connected domain in the red blood cell segmentation image;
determining that the connected domain is an abnormal state red blood cell and accumulating the number of the abnormal state red blood cells under the condition that the circularity of the connected domain is smaller than a preset threshold value;
and under the condition that the circularity of the communicating domain is larger than or equal to a preset threshold value, determining that the communicating domain is a normal state red blood cell, and accumulating the number of the normal state red blood cells.
In one possible implementation, the abnormal state red blood cells include at least one of: and (3) fragmenting erythrocytes and mutated erythrocytes.
In one possible implementation manner, performing edge detection on the erythrocyte grayscale image to obtain a corresponding erythrocyte edge information image, which specifically includes:
and carrying out edge detection on the red blood cell gray-scale image based on a preset direction controllable filter to obtain a corresponding red blood cell edge information image.
An erythrocyte image detection device, the device comprising:
at least one processor; and
a memory communicatively coupled to the at least one processor;
wherein the memory stores instructions executable by the at least one processor to enable the at least one processor to:
acquiring a corresponding red blood cell image, and acquiring a corresponding red blood cell graying image according to the red blood cell image;
performing edge detection on the red blood cell gray-scale image to obtain a corresponding red blood cell edge information image;
based on expansion operation, processing the erythrocyte edge information image to obtain a corresponding erythrocyte expansion fusion image;
performing closed operation treatment on the erythrocyte expansion fusion image to obtain an erythrocyte segmentation image;
determining a plurality of connected domains in the red blood cell segmentation image;
and counting the number of the red blood cells in the red blood cell image according to the plurality of connected domains in the red blood cell segmentation image.
A non-transitory computer storage medium storing computer-executable instructions for erythrocyte image detection, the computer-executable instructions configured to:
acquiring a corresponding red blood cell image, and acquiring a corresponding red blood cell graying image according to the red blood cell image;
performing edge detection on the red blood cell gray-scale image to obtain a corresponding red blood cell edge information image;
based on expansion operation, processing the erythrocyte edge information image to obtain a corresponding erythrocyte expansion fusion image;
performing closed operation treatment on the erythrocyte expansion fusion image to obtain an erythrocyte segmentation image;
determining a plurality of connected domains in the red blood cell segmentation image;
and counting the number of the red blood cells in the red blood cell image according to the plurality of connected domains in the red blood cell segmentation image.
The above-mentioned at least one technical scheme that this description embodiment adopted can reach following beneficial effect: the red blood cell image is sequentially subjected to treatments such as graying, edge detection, expansion operation, closing operation and the like to obtain a red blood cell segmentation image, a plurality of connected domains in the red blood cell segmentation image are determined, and the number of red blood cells in the red blood cell image is counted according to the connected domains. Compared with the existing erythrocyte image detection method, the method is not limited to a specific detection environment, has strong adaptability to the detection environment and is not easily influenced by the environment; on the other hand, the technical scheme provided by the embodiment of the application has the advantages of high statistical precision and high accuracy of the number of the red blood cells, and compared with the existing red blood cell detection technology, the method is simpler and more convenient, so that the red blood cell detection efficiency is improved, and the use experience of a user is enhanced.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiments of the application and together with the description serve to explain the application and do not constitute an undue limitation to the application. In the drawings:
FIG. 1 is a flow chart of a method for detecting red blood cell images according to an embodiment of the present disclosure;
FIG. 2 is a schematic diagram of structural elements provided in an embodiment of the present application;
fig. 3 is a schematic structural diagram of an image detection apparatus for red blood cells according to an embodiment of the present disclosure.
Detailed Description
For the purposes of making the objects, technical solutions and advantages of the present specification more apparent, the technical solutions of the present application will be clearly and completely described below with reference to specific embodiments of the present specification and corresponding drawings. It will be apparent that the described embodiments are only some, but not all, of the embodiments of the present application. All other embodiments, which can be made by one of ordinary skill in the art without undue burden from the disclosure, are intended to be within the scope of the present application based on the embodiments described herein.
The following describes in detail the technical solutions provided by the embodiments of the present application with reference to the accompanying drawings.
Erythrocyte detection is an important item in clinical lesion examination, and is also an important item for the detection of the number of erythrocytes. The number of erythrocytes exceeding the normal level can be regarded as an increase in erythrocyte content, and of course, the number or range of numbers corresponding to the normal level is different for people of different ages and sexes. When the number of erythrocytes is lower than the normal level, erythropenia may be considered, and symptoms such as leukemia and dyssynthesis may occur.
Fig. 1 is a flowchart of a method for detecting an image of a red blood cell according to an embodiment of the present application. As shown in fig. 1, the method comprises the steps of:
s101, acquiring corresponding red blood cell images.
The red blood cell image referred to herein may be a microscope image containing red blood cells.
As will be appreciated by those skilled in the art, the composition of blood includes plasma and blood cells, which include erythrocytes, leukocytes and platelets. In general, when detecting red blood cells, it is necessary to collect corresponding blood, then make a blood smear, observe the smear with a microscope, and collect an image to obtain the image of the red blood cells. The red blood cell image may be an image in RGB color mode or an image in HSV color mode, and in the embodiment of the present application, the color mode of the red blood cell image is not limited.
S102, obtaining a corresponding red blood cell gray-scale image according to the red blood cell image.
The above-mentioned red cell image may be a color image in an RGB color mode in which various colors are obtained by changing three color channels of red (R), green (G), blue (B) and overlapping them with each other. That is, the red blood cell image may be composed according to three color channels of red, green and blue.
Thus, in some embodiments of the present application, the above-described red blood cell image may be obtained by: the red cell image can be decomposed into a green single-channel image, and then the green single-channel image is subjected to gray-scale treatment to obtain a corresponding single-channel gray-scale image, namely the red cell gray-scale image.
Since the red cells are red in color in the red cell image, the green channel has the greatest contrast with red relative to the red and blue channels. Therefore, the red blood cell image is decomposed into a green single-channel image, and then the gray processing is carried out, so that red blood cells in the image can be highlighted more, and the image error after gray processing is smaller, thereby reducing the error of red blood cell quantity statistics in the later detection of the red blood cells and improving the accuracy.
In the embodiment of the present application, the red cell image may be decomposed into a red single-channel image or a blue single-channel image, but the contrast is smaller and the error is larger than that of the red single-channel image. If the red blood cell image is the red blood cell image in the HSV color mode or another color mode, the red blood cell image in the other color mode may be converted into the red blood cell image in the RGB color mode by the corresponding algorithm, and then the step S102 is performed.
S103, filtering the erythrocyte grayscale image to eliminate salt and pepper noise of the erythrocyte grayscale image.
Salt and pepper noise is an image noise that is often seen in an image, is a random occurrence of white and black spots, may be black pixels in bright areas or white pixels in dark areas, or both. Therefore, in order to avoid the interference of salt and pepper noise in the red blood cell grayscale image, the red blood cell grayscale image may be subjected to a filter process to denoise the red blood cell grayscale image. Through step S103, the influence of salt and pepper noise on the detection of the red blood cells can be reduced, and the accuracy of the detection of the red blood cells is further improved.
The filtering process may be performed on the red blood cell grayscale image by using, for example, a 5*5 mean filter. Other methods of eliminating salt and pepper noise may also be used, as will be appreciated by those skilled in the art. In the embodiment of the present application, the technical means used for filtering the red blood cell grayscale image is not limited, as long as the function of eliminating salt and pepper noise can be achieved.
S104, carrying out edge detection on the red blood cell gray-scale image to obtain a corresponding red blood cell edge information image.
The red blood cell grayscale image in step S104 may be the red blood cell image from which the salt and pepper noise was removed in step S103, or the red blood cell grayscale image in step S102.
Specifically, the edge detection can be performed on the red blood cell image based on a preset direction controllable filter, so as to obtain a corresponding red blood cell edge image. The direction controllable filter is composed of a plurality of basic filters, the basic filters can form any direction of the direction controllable filter, the direction controllable filter is adopted to carry out filtering enhancement on the gray level image, and the red cell edge information can be effectively segmented, so that a red cell edge information image is obtained.
Other edge detection algorithms, such as Canny operator-based edge detection algorithms, log operator-based edge detection algorithms, may also be employed in the present specification. The specific mode of edge detection of the erythrocyte grayscale image is not limited in the present specification.
Through step S104, the boundaries of the erythrocytes in the image, that is to say the outlines of the erythrocytes, can be detected.
S105, performing threshold segmentation on the erythrocyte edge information image according to a preset threshold value to obtain an erythrocyte edge information image of reserved erythrocyte bodies.
Threshold segmentation is carried out through a corresponding preset threshold erythrocyte edge information image so as to remove other noises except erythrocyte bodies in the erythrocyte edge information image, and an erythrocyte edge information image retaining the erythrocyte bodies is obtained.
Other boundaries than the red blood cell boundary may exist in the red blood cell boundary information image, which may interfere with red blood cell detection. In general, the pixel values of the other boundaries are significantly different from those of the red blood cell boundaries, and therefore, the red blood cell edge information image can be segmented by setting corresponding thresholds. The interference can be eliminated through the step S105, so that the accuracy of red blood cell detection is further improved.
In the embodiment of the application, the global threshold method may be used to perform threshold segmentation on the red cell edge information image, that is, only one fixed threshold T is selected for the red cell edge information image to perform threshold segmentation, and typically, the threshold segmentation is performed by an Ostu method, a maximum entropy generation method, a gray level expected value method, and the like.
In some embodiments of the present application, the threshold segmentation may be performed on the red blood cell edge information image except that step S105 may be performed after step S104; the red blood cell grayscale image filtered in step S103 may be thresholded before step S104.
S106, processing the erythrocyte edge information image based on an expansion algorithm to obtain a corresponding erythrocyte expansion fusion image.
Specifically, the structural elements (shown in fig. 2) are adopted to perform expansion operation on the erythrocyte edge information image, and if the pixel points of the structural elements are overlapped with the erythrocyte edge information image during the expansion operation, the structural elements are reserved, and the erythrocyte expansion fusion image is obtained through circulation traversal.
Through step S106, some voids in the erythrocytes in the erythrocyte edge information image can be filled up, and small particle noise can be eliminated, so that the morphology of the erythrocytes in the erythrocyte edge information image is more real, the difference between the erythrocytes and the real erythrocytes is further reduced, and the use experience of a user is improved.
The red blood cell edge information image mentioned here may be obtained after step S105 is performed, or may be obtained after step S104 is performed, and is not limited to the red blood cell edge image subjected to the threshold segmentation process.
S107, performing closed operation processing on the erythrocyte expansion fusion image to obtain an erythrocyte segmentation image.
Because the erythrocyte expansion fusion image has the burr noise, the burr noise needs to be removed according to the morphological characteristics of the actual erythrocyte, and therefore, the erythrocyte expansion fusion image is subjected to closed operation, and the erythrocyte segmentation map with the burr noise removed is obtained.
As will be appreciated by those skilled in the art, the morphology of red blood cells is a biconvex, concave-in-center pie, i.e., the red blood cell center is concave. Therefore, some erythrocytes in the erythrocyte expansion fusion image obtained after step S106 may appear to be ring-shaped, and the actual morphological characteristics of the erythrocytes cannot be effectively displayed.
Therefore, in some embodiments of the present application, corresponding calculation may be performed according to the above-mentioned erythrocyte expansion fusion image, so as to determine a plurality of connected domains in the erythrocyte expansion fusion image. Determining whether the region editing of each connected domain is smaller than a corresponding preset threshold value, and filling the connected domain under the condition that the region area of the connected domain is smaller than the corresponding preset threshold value.
Through the scheme, the red blood cells in the red blood cell expansion fusion image can be in the annular shape in the figure, so that the real morphological characteristics of the red blood cells can be effectively displayed.
S108, processing the red blood cell segmentation image to determine a plurality of connected domains in the red blood cell segmentation image.
And calculating connected domains in the red blood cell segmentation image, and counting the number of the connected domains.
S109, counting the number of the red blood cells in the red blood cell image according to the plurality of connected domains in the red blood cell segmentation image.
In the present specification, it can be considered that one connected domain corresponds to one red blood cell, and the number of connected domains in the red blood cell segmentation image is counted, i.e., the number of red blood cells in the red blood cell image can be counted
Further, in addition to normal state erythrocytes, abnormal state erythrocytes, such as disintegrated erythrocytes, mutated erythrocytes, etc., may be present in erythrocytes. The abnormal state red blood cells mentioned herein include at least one of the following: and (3) fragmenting erythrocytes and mutated erythrocytes. Abnormal red blood cells such as the number of disintegrated red blood cells and the number of mutated red blood cells are also important contents for clinical lesion examination.
Thus, in some embodiments of the present application, the number of normal state erythrocytes, abnormal state erythrocytes, can be further detected by:
calculating the circularity of each connected domain in the red blood cell segmentation image;
under the condition that the circularity of the connected domain is smaller than a preset threshold value, determining that the connected domain is an abnormal state red blood cell, and accumulating the number of the abnormal state red blood cells;
and under the condition that the circularity of the communicating domain is larger than or equal to a preset threshold value, determining that the communicating domain is normal state red blood cells, and accumulating the number of the long state red blood cells.
Since the broken red blood cells generally refer to red blood cell fragments or incomplete red blood cells, the red blood cells have different sizes and irregular shapes, and various forms such as spines, helmets, triangles and the like are available. Variant erythrocytes may refer to erythrocytes that are variant in shape. That is, the normal state red blood cells are greatly different from the abnormal state red blood cells in shape, and therefore, the circularity of each of the communicating regions can be calculated, and compared with the circularities of the communicating regions according to the corresponding preset threshold values, thereby determining whether the communicating region is an abnormal state red blood cell or a normal state red blood cell.
The embodiment of the application provides a red blood cell image detection method, which comprises the steps of sequentially carrying out treatments such as graying, edge detection, expansion operation, closing operation and the like on a red blood cell image to obtain a red blood cell segmentation image, determining a plurality of connected domains in the red blood cell segmentation image, and counting the number of red blood cells in the red blood cell image according to the connected domains. Compared with the existing erythrocyte image detection method, the method is not limited to a specific detection environment, has strong adaptability to the detection environment and is not easily influenced by the environment; on the other hand, the erythrocyte image detection method provided by the embodiment of the application has the advantages of high statistical precision and high accuracy of the number of the erythrocytes, and is simpler and more convenient than the method adopted by the prior art, so that the erythrocyte detection efficiency is improved, and the use experience of a user is enhanced.
Fig. 3 is a schematic structural diagram of an apparatus for detecting red blood cell image according to an embodiment of the present application, as shown in fig. 3, the apparatus includes:
at least one processor; and
a memory communicatively coupled to the at least one processor;
wherein the memory stores instructions executable by the at least one processor to enable the at least one processor to:
acquiring a corresponding red blood cell image, and acquiring a corresponding red blood cell graying image according to the red blood cell image;
performing edge detection on the red blood cell gray-scale image to obtain a corresponding red blood cell edge information image;
based on expansion operation, processing the erythrocyte edge information image to obtain a corresponding erythrocyte expansion fusion image;
performing closed operation treatment on the erythrocyte expansion fusion image to obtain an erythrocyte segmentation image;
determining a plurality of connected domains in the red blood cell segmentation image;
and counting the number of the red blood cells in the red blood cell image according to the plurality of connected domains in the red blood cell segmentation image.
The embodiments of the present application also provide a non-volatile computer storage medium for erythrocyte image detection, storing computer executable instructions configured to:
acquiring a corresponding red blood cell image, and acquiring a corresponding red blood cell graying image according to the red blood cell image;
performing edge detection on the red blood cell gray-scale image to obtain a corresponding red blood cell edge information image;
based on expansion operation, processing the erythrocyte edge information image to obtain a corresponding erythrocyte expansion fusion image;
performing closed operation treatment on the erythrocyte expansion fusion image to obtain an erythrocyte segmentation image;
determining a plurality of connected domains in the red blood cell segmentation image;
and counting the number of the red blood cells in the red blood cell image according to the plurality of connected domains in the red blood cell segmentation image.
All embodiments in the application are described in a progressive manner, and identical and similar parts of all embodiments are mutually referred, so that each embodiment mainly describes differences from other embodiments. In particular, for the apparatus and medium embodiments, the description is relatively simple, as it is substantially similar to the method embodiments, with reference to the section of the method embodiments being relevant.
The devices and media provided in the embodiments of the present application are in one-to-one correspondence with the methods, so that the devices and media also have similar beneficial technical effects as the corresponding methods, and since the beneficial technical effects of the methods have been described in detail above, the beneficial technical effects of the devices and media are not described in detail herein.
It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
In one typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include volatile memory in a computer-readable medium, random Access Memory (RAM) and/or nonvolatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of computer-readable media.
Computer readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of storage media for a computer include, but are not limited to, phase change memory (PRAM), static Random Access Memory (SRAM), dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), read Only Memory (ROM), electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium, which can be used to store information that can be accessed by a computing device. Computer-readable media, as defined herein, does not include transitory computer-readable media (transmission media), such as modulated data signals and carrier waves.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article or apparatus that comprises the element.
The foregoing is merely exemplary of the present application and is not intended to limit the present application. Various modifications and changes may be made to the present application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc. which are within the spirit and principles of the present application are intended to be included within the scope of the claims of the present application.
Claims (9)
1. A method for detecting an image of red blood cells, the method comprising:
acquiring a corresponding red blood cell image, and acquiring a corresponding red blood cell graying image according to the red blood cell image;
performing edge detection on the red blood cell gray-scale image to obtain a corresponding red blood cell edge information image;
based on expansion operation, processing the erythrocyte edge information image to obtain a corresponding erythrocyte expansion fusion image;
performing closed operation treatment on the erythrocyte expansion fusion image to obtain an erythrocyte segmentation image;
determining a plurality of connected domains in the red blood cell segmentation image;
counting the number of red blood cells in the red blood cell image according to the plurality of connected domains in the red blood cell segmentation image;
the red blood cells comprise normal state red blood cells and abnormal state red blood cells;
counting the number of red blood cells in the red blood cell image according to the plurality of connected domains in the red blood cell segmentation image, wherein the method specifically comprises the following steps:
calculating the circularity of each connected domain in the red blood cell segmentation image;
determining that the connected domain is an abnormal state red blood cell and accumulating the number of the abnormal state red blood cells under the condition that the circularity of the connected domain is smaller than a preset threshold value;
and under the condition that the circularity of the communicating domain is larger than or equal to a preset threshold value, determining that the communicating domain is a normal state red blood cell, and accumulating the number of the normal state red blood cells.
2. The method according to claim 1, wherein obtaining a corresponding red blood cell gray scale image from the red blood cell image comprises:
decomposing the red blood cell image into a green single-channel image;
and carrying out gray processing on the green single-channel image to obtain a corresponding red blood cell gray image.
3. The method of claim 1, wherein prior to obtaining the corresponding image of red blood cell edge information, the method further comprises:
and filtering the erythrocyte grayscale image to eliminate salt and pepper noise of the erythrocyte grayscale image.
4. The method of claim 1, wherein prior to obtaining the corresponding erythrocyte expansion fusion image, the method further comprises:
according to a preset threshold value, performing threshold segmentation on the erythrocyte grayscale image to obtain an erythrocyte grayscale image with reserved erythrocyte bodies; or alternatively
And according to a preset threshold, performing threshold segmentation on the erythrocyte edge information image to obtain an erythrocyte edge information image of reserved erythrocyte bodies.
5. The method of claim 1, wherein prior to obtaining the red blood cell segmentation image, the method further comprises:
performing corresponding calculation according to the erythrocyte expansion fusion image, and determining a plurality of connected domains in the erythrocyte expansion fusion image;
determining whether the area of each connected domain is smaller than a corresponding preset threshold value;
and filling the communication domain under the condition that the area of the communication domain is smaller than a corresponding preset threshold value.
6. The method of claim 1, wherein the abnormal state red blood cells comprise at least one of: and (3) fragmenting erythrocytes and mutated erythrocytes.
7. The method according to claim 1, wherein the edge detection is performed on the red blood cell grayscale image to obtain a corresponding red blood cell edge information image, and specifically comprises:
and carrying out edge detection on the red blood cell gray-scale image based on a preset direction controllable filter to obtain a corresponding red blood cell edge information image.
8. An erythrocyte image detection device, the device comprising:
at least one processor; and
a memory communicatively coupled to the at least one processor;
wherein the memory stores instructions executable by the at least one processor to enable the at least one processor to:
acquiring a corresponding red blood cell image, and acquiring a corresponding red blood cell graying image according to the red blood cell image;
performing edge detection on the red blood cell gray-scale image to obtain a corresponding red blood cell edge information image;
based on expansion operation, processing the erythrocyte edge information image to obtain a corresponding erythrocyte expansion fusion image;
performing closed operation treatment on the erythrocyte expansion fusion image to obtain an erythrocyte segmentation image;
determining a plurality of connected domains in the red blood cell segmentation image;
counting the number of red blood cells in the red blood cell image according to the plurality of connected domains in the red blood cell segmentation image;
the red blood cells comprise normal state red blood cells and abnormal state red blood cells;
counting the number of red blood cells in the red blood cell image according to the plurality of connected domains in the red blood cell segmentation image, wherein the method specifically comprises the following steps:
calculating the circularity of each connected domain in the red blood cell segmentation image;
determining that the connected domain is an abnormal state red blood cell and accumulating the number of the abnormal state red blood cells under the condition that the circularity of the connected domain is smaller than a preset threshold value;
and under the condition that the circularity of the communicating domain is larger than or equal to a preset threshold value, determining that the communicating domain is a normal state red blood cell, and accumulating the number of the normal state red blood cells.
9. A non-transitory computer storage medium storing computer-executable instructions for erythrocyte image detection, the computer-executable instructions configured to:
acquiring a corresponding red blood cell image, and acquiring a corresponding red blood cell graying image according to the red blood cell image;
performing edge detection on the red blood cell gray-scale image to obtain a corresponding red blood cell edge information image;
based on expansion operation, processing the erythrocyte edge information image to obtain a corresponding erythrocyte expansion fusion image;
performing closed operation treatment on the erythrocyte expansion fusion image to obtain an erythrocyte segmentation image;
determining a plurality of connected domains in the red blood cell segmentation image;
counting the number of red blood cells in the red blood cell image according to the plurality of connected domains in the red blood cell segmentation image;
the red blood cells comprise normal state red blood cells and abnormal state red blood cells;
counting the number of red blood cells in the red blood cell image according to the plurality of connected domains in the red blood cell segmentation image, wherein the method specifically comprises the following steps:
calculating the circularity of each connected domain in the red blood cell segmentation image;
determining that the connected domain is an abnormal state red blood cell and accumulating the number of the abnormal state red blood cells under the condition that the circularity of the connected domain is smaller than a preset threshold value;
and under the condition that the circularity of the communicating domain is larger than or equal to a preset threshold value, determining that the communicating domain is a normal state red blood cell, and accumulating the number of the normal state red blood cells.
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