CN110619640B - Granulocyte detection method and system based on bone marrow cell image - Google Patents
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- 210000003714 granulocyte Anatomy 0.000 title claims abstract description 48
- 210000002798 bone marrow cell Anatomy 0.000 title claims abstract description 37
- 238000001514 detection method Methods 0.000 title description 18
- 238000000034 method Methods 0.000 claims abstract description 20
- 238000001914 filtration Methods 0.000 claims abstract description 19
- 238000004891 communication Methods 0.000 claims abstract description 15
- 238000004590 computer program Methods 0.000 claims description 6
- 238000003709 image segmentation Methods 0.000 claims description 4
- 238000003064 k means clustering Methods 0.000 claims 1
- 210000004027 cell Anatomy 0.000 description 22
- 210000004940 nucleus Anatomy 0.000 description 10
- 210000003855 cell nucleus Anatomy 0.000 description 7
- 238000012986 modification Methods 0.000 description 3
- 230000004048 modification Effects 0.000 description 3
- 230000000877 morphologic effect Effects 0.000 description 3
- 238000004458 analytical method Methods 0.000 description 2
- 230000001575 pathological effect Effects 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 239000012535 impurity Substances 0.000 description 1
- 210000000265 leukocyte Anatomy 0.000 description 1
- 210000000066 myeloid cell Anatomy 0.000 description 1
- 239000002245 particle Substances 0.000 description 1
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Abstract
The invention discloses a method for detecting granulocytes in a bone marrow cell image, which comprises the following steps: receiving a bone marrow cell image, segmenting the bone marrow cell image, and marking a communication area; filtering the connected region according to the size of the connected region; and identifying the candidate lobular nucleus region according to the size and shape characteristics of the connected region, thereby determining the granulocyte region. The invention can rapidly detect the granulocytes of the obtained bone marrow cell image.
Description
Technical Field
The invention relates to the technical field of medical image processing, in particular to a granulocyte detection method and a granulocyte detection system based on a bone marrow cell image.
Background
The statements in this section merely provide background information related to the present disclosure and may not necessarily constitute prior art.
The background structure of the bone marrow cell image shot by a microscope is complex and contains various artifacts and noises, and the image contains a large number of cells, wherein the granulocytes account for 50% -70% of the cells. Granulocytes have various forms and multiple leaves, one leaf in one granulocyte is easy to detect as one cell when cell detection is carried out, the detection accuracy is reduced, and the performance of the method for detecting granulocytes in a bone marrow cell image needs to be further improved.
To the inventor's knowledge, there are cell detection and counting methods for digital pathological images, such as patent 201110427703.9, which uses hough transform to detect cells; patent 201410369635.9 discloses detecting leukocytes by using their appearance and internal characteristics; the patent 201810480756.9 effectively removes the influence of noise to the analysis and processing of the cell layer, thus improving the accuracy of cell detection and counting; the target detection counting algorithm is only suitable for cell detection with simple image background and sparse cell distribution, and the detection rate of granulocytes, especially the granulocytes in leaves is low.
Disclosure of Invention
In order to overcome the defects of the prior art, the invention provides a method and a system for detecting granulocytes in a marrow cell image, which are used for detecting the cells of the marrow cell image according to morphological characteristics of the cells, and judging and combining the leaf cores of an initial mark communication area, so that the efficiency and the accuracy of granulocyte detection can be improved.
In order to achieve the above object, one or more embodiments of the present invention provide the following technical solutions:
a method for detecting granulocytes in a bone marrow cell image comprises the following steps:
receiving a bone marrow cell image, segmenting the bone marrow cell image, and marking a communication area;
filtering the connected region according to the size of the connected region;
and identifying the candidate lobular nucleus region according to the size and shape characteristics of the connected region, thereby determining the granulocyte region.
One or more embodiments provide a system for detecting granulocytes in an image of bone marrow cells, comprising:
the image segmentation module receives a bone marrow cell image, segments the bone marrow cell image and marks a communication area;
the garbage filtering module is used for filtering the communicated area according to the size of the communicated area;
and the granulocyte identification module is used for identifying the candidate lobular nucleus region according to the size and shape characteristics of the connected region so as to determine the granulocyte region.
One or more embodiments provide an electronic device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the processor implements the method for detecting granulocytes in an image of bone marrow cells when executing the program.
One or more embodiments provide a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, performs the method for detecting granulocytes in an image of bone marrow cells.
The above one or more technical solutions have the following beneficial effects:
the granulocyte detection method provided by the invention is based on the morphological characteristics of the granulocyte, filters and screens the connected domain obtained by image segmentation, is low in computational complexity, and can realize rapid detection of the granulocyte. And for multiple targets, the cell image with the segmented cells and the complex background is obtained, and the granulocyte detection accuracy is high.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, are included to provide a further understanding of the invention, and are incorporated in and constitute a part of this specification, illustrate exemplary embodiments of the invention and together with the description serve to explain the invention and not to limit the invention.
FIG. 1 is a schematic flow chart of a granulocyte detection method based on a myeloid cell image according to an embodiment of the present invention.
Detailed Description
It is to be understood that the following detailed description is exemplary and is intended to provide further explanation of the invention as claimed. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of exemplary embodiments according to the invention. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, and it should be understood that when the terms "comprises" and/or "comprising" are used in this specification, they specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof, unless the context clearly indicates otherwise.
The embodiments and features of the embodiments of the present invention may be combined with each other without conflict.
Example one
This example discloses a method for detecting granulocytes in a bone marrow cell image, as shown in FIG. 1,
the method comprises the following steps:
step S1: and segmenting the image to be processed into cell nucleuses, and utilizing the connected region analysis to mark the region with connectivity.
According to the characteristic that cell nucleuses in a cell image have better regional connectivity, connected domain marking is carried out, and the method specifically comprises the following steps:
step S11: segmenting the image to be processed converted into the Lab color space by using k-means to obtain a segmented cell nucleus pixel point set;
step S12: and converting the divided cell nucleuses into binary images to analyze the connected regions, and marking the connected regions.
Step S2: and according to the connected region marked in the step S1, performing garbage filtration on the connected region according to the garbage filtration rule, and removing the connected region with impurity noise.
Step S21: setting an area threshold and a diameter threshold of garbage filtering parameters;
step S22: calculating the area and the diameter of each mark communication area, judging whether the area and the diameter of each mark communication area are both in a set threshold range, and if so, judging that the area is a garbage area; if not, continuing to judge the next area
Step S23: and filtering the connected areas which are judged as the garbage areas, and reserving the remaining connected areas.
In step S22, the following formula is used to determine the garbage area:
wherein, A is adoptediDenotes the ith connected region, i denotes any positive integer between 1 and P,dithe diameter, s, of a circle (or ellipse) representing a region similar to this communicating regioniThe area of this connected region is shown,
a threshold value of the diameter is indicated,
representing the area threshold. Diameter of area
Area of area
And judging that the area is a garbage area.
The area after the rubbish is filtered is:
R＝A-Garb (2)
wherein R is a filtered connected region set,
w is the number of connected regions.
Step S3: and (4) performing the division of the nucleus pulposus region and the combination of the division of the nucleus pulposus region on the connected region after the garbage filtration in the step (S2) by utilizing the pathological features of the granulocytes.
Step S31: judging whether the area is a lobulated nucleus area or not by utilizing the cell nucleus area threshold and the eccentricity threshold,
denotes the area of the connected region, eiDenotes the eccentricity of the connected region, i denotes any positive integer between 1 and W,
and
representing the area threshold, the leaf core region is determined as follows:
wherein R islobuleExpressed as the nucleus lobular region, Rnon-lobuleOther regions represented as non-leaf nuclei.
Step S32: taking any two as RlobuleAnd recording the label;
step S33: the center-to-center distance between the two regions is calculated:
wherein (x)i，yi，hi，wi) And (x)j，yj，hj，wj) Respectively representing connected regions
And
the position coordinates of the circumscribed rectangle in the image and the area size parameter.
Step S34: judging whether the center distance is smaller than the maximum value of the diameters of the two areas, namely judging the center distance D and
(ii) the magnitude relation of (h)i，wi) And (h)j，wj) Respectively representing connected regions
And the communication area
The length and width of the circumscribed rectangle of (1). If it is
Proceed to step S35; if not, then,proceed to step S32;
step S35: merging two connected regions
Denoted as merging regions, the parameters of the smaller region are updated and the parameters of the other region merged in are deleted.
In step S35, the regions are merged as follows
Wherein D is a connected region
And the communication area
The center-to-center distance of (a),
eirespectively represent the ith connected region
The average area and the eccentricity are calculated,
ejrespectively represent the jth connected region
Area and eccentricity of.
Is a merged region, (h)i，wi) And (h)j，wj) Respectively representing connected regions
And the communication area
Both circumscribe the length and width of the rectangle.
The parameters are updated after the region is merged as follows:
wherein (x)i，yi，hi，wi) And (x)j，yj，hj，wj) Respectively representing connected regions
And the communication area
The position coordinates of the circumscribed rectangle in the image and the area size parameter.
Step S36: deleting the merged another region parameter; step 32 continues until all regions have been traversed.
Step S4: judging whether all the connected areas are processed, if yes, turning to the step S2; and if all the connected regions are processed, obtaining a complete granulocyte region, and finishing the algorithm.
Example two
The present embodiment aims to provide a system for detecting granulocytes in a bone marrow cell image.
In order to achieve the above object, the present embodiment provides a system for detecting granulocytes in a bone marrow cell image, comprising:
the image segmentation module receives a bone marrow cell image, segments the bone marrow cell image and marks a communication area;
the garbage filtering module is used for filtering the communicated area according to the size of the communicated area;
and the granulocyte identification module is used for identifying the candidate lobular nucleus region according to the size and shape characteristics of the connected region so as to determine the granulocyte region.
EXAMPLE III
The embodiment aims at providing an electronic device.
An electronic device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, the processor implementing the following steps when executing the program, comprising:
receiving a bone marrow cell image, segmenting the bone marrow cell image, and marking a communication area;
filtering the connected region according to the size of the connected region;
and identifying the candidate lobular nucleus region according to the size and shape characteristics of the connected region, thereby determining the granulocyte region.
Example four
An object of the present embodiment is to provide a computer-readable storage medium.
A computer-readable storage medium, on which a computer program is stored which, when executed by a processor, performs the steps of:
receiving a bone marrow cell image, segmenting the bone marrow cell image, and marking a communication area;
filtering the connected region according to the size of the connected region;
and identifying the candidate lobular nucleus region according to the size and shape characteristics of the connected region, thereby determining the granulocyte region.
The steps involved in the above second, third and fourth embodiments correspond to the method embodiments, and the detailed description can be found in the relevant description of the first embodiment. The term "computer-readable storage medium" should be taken to include a single medium or multiple media containing one or more sets of instructions; it should also be understood to include any medium that is capable of storing, encoding or carrying a set of instructions for execution by a processor and that cause the processor to perform any of the methods of the present invention.
One or more of the above embodiments have the following technical effects:
the invention uses the area and the diameter of the target area as threshold values according to the morphological characteristics of the cells,
and filtering the garbage area to screen a target area which is possibly a cell nucleus, so that the interference of most non-cell nucleus particle areas is avoided.
According to the invention, the over-segmented cells are judged and combined according to the numerical values such as the area and the eccentricity in the connected domain, so that the detection of the segmented granulocytes is improved.
The invention has wide application range and high cell detection accuracy for multiple targets, and has the advantages of leafing cells and cell images with complex backgrounds.
Those skilled in the art will appreciate that the modules or steps of the present invention described above can be implemented using general purpose computer means, or alternatively, they can be implemented using program code that is executable by computing means, such that they are stored in memory means for execution by the computing means, or they are separately fabricated into individual integrated circuit modules, or multiple modules or steps of them are fabricated into a single integrated circuit module. The present invention is not limited to any specific combination of hardware and software.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Although the embodiments of the present invention have been described with reference to the accompanying drawings, it is not intended to limit the scope of the present invention, and it should be understood by those skilled in the art that various modifications and variations can be made without inventive efforts by those skilled in the art based on the technical solution of the present invention.
Claims (6)
1. A method for detecting granulocytes in a bone marrow cell image, comprising the steps of:
receiving a bone marrow cell image, segmenting the bone marrow cell image, and marking a communication area;
filtering the connected region according to the size of the connected region;
the rule adopted by the filtering is as follows:
if the area and the diameter of a certain communicated region are smaller than the corresponding set threshold, judging that the communicated region is a communicated region to be filtered;
identifying a candidate lobular nucleus region according to the size and shape characteristics of the connected region, thereby determining a granulocyte region;
the method for determining the granulocyte area comprises the following steps:
identifying candidate leaf nucleus areas according to the areas and the eccentricity of the connected areas;
and taking any two candidate connected regions and calculating the distance between the two candidate connected regions, merging the two candidate connected regions which meet the conditions, and updating the parameters of the connected regions to obtain the granulocyte region.
2. The method according to claim 1, wherein the segmenting the bone marrow cell image comprises:
converting the bone marrow cell image to a Lab color space;
and (4) segmenting the bone marrow cell image based on a K-means clustering method.
3. The method of claim 1, wherein the merging candidate segmented nucleus regions comprises:
for any two candidate leaf-nucleus regions;
and calculating the center distance between the two areas, judging whether the center distance is smaller than the maximum value of the diameters of the two areas, and if so, combining the two areas.
4. A system for detecting granulocytes in an image of bone marrow cells, comprising:
the image segmentation module receives a bone marrow cell image, segments the bone marrow cell image and marks a communication area;
the garbage filtering module is used for filtering the communicated area according to the size of the communicated area;
the rule adopted by the filtering is as follows:
if the area and the diameter of a certain communicated region are smaller than the corresponding set threshold, judging that the communicated region is a communicated region to be filtered;
the granulocyte identifying module is used for identifying the candidate lobular nucleus region according to the size and shape characteristics of the connected region so as to determine a granulocyte region;
the method for determining the granulocyte area comprises the following steps:
identifying candidate leaf nucleus areas according to the areas and the eccentricity of the connected areas;
and taking any two candidate connected regions and calculating the distance between the two candidate connected regions, merging the two candidate connected regions which meet the conditions, and updating the parameters of the connected regions to obtain the granulocyte region.
5. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the method for detecting granulocytes in an image of bone marrow cells according to any one of claims 1-3 when executing the program.
6. A computer-readable storage medium on which a computer program is stored, which, when being executed by a processor, performs the method for detecting granulocytes in an image of bone marrow cells according to any one of claims 1 to 3.
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| CN102044069A (en) * | 2010-12-01 | 2011-05-04 | 华中科技大学 | A white blood cell image segmentation method |
| CN104392460A (en) * | 2014-12-12 | 2015-03-04 | 山东大学 | Adherent white blood cell segmentation method based on nucleus-marked watershed transformation |
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