CN114897843A - Overlapping chromosome segmentation method - Google Patents

Abstract

The invention provides a method for segmenting overlapping chromosomes, which comprises the following steps of S100, carrying out edge extraction on an overlapping chromosome image, obtaining edge outlines of all overlapping chromosomes, and adding all edge outline points into a set of cutting points to be selected; step S200, extracting a skeleton, a skeleton end point and a skeleton intersection point of the overlapped chromosome image; step S300, determining the cutting points of the overlapped chromosomes according to the edge contour of the overlapped chromosomes obtained in the step S100 and the chromosome skeleton, the skeleton end points and the intersection points obtained in the step S200; and S400, automatically segmenting the overlapped chromosomes according to the cutting points. According to the contour and skeleton-based overlapped chromosome segmentation method, all contour points are regarded as cut points and used as candidate sets by combining the relation between the contour and the skeleton of the chromosome by utilizing the overlapped features of the overlapped chromosomes, a series of complex processes of curvature calculation are omitted, and the optimal cut points are accurately positioned by combining Euclidean distance with the skeleton of the chromosome.

Description

Overlapping chromosome segmentation method

Technical Field

The invention relates to the technical field of chromosome karyotype image analysis, in particular to an overlapped chromosome segmentation method.

Background

Chromosomes are carriers of life genetic materials and exist in cell nucleuses in a filamentous or rod-shaped form, the number and morphological structure characteristics of the chromosomes can be observed through staining film making and microscopic imaging in the mitotic metaphase of cells, the chromosome abnormality can cause hereditary diseases, neonatal defects and other diseases, the chromosome karyotype analysis is to find out the abnormal conditions such as chromosome phenotype number and structure abnormality, such as number inconsistency, segment abnormity (repetition, deletion, translocation, inversion and the like), morphological abnormity (the chromosome length or the satellite size is inconsistent with the normal chromosome) and the like, and doctors make accurate diagnosis and treatment for patients through the chromosome karyotype analysis.

Chromosomes in the chromosome karyotype image have unpredictability and are characterized by easy adhesion, fuzzy edges, multiple overlapping nestings and the like, the existing chromosome karyotype image processing algorithm has poor effects of segmenting, counting and eliminating redundancies of the chromosomes, the precision needs to be improved, meanwhile, the whole process of manual work needs to be involved in the chromosome karyotype analysis process, the automation degree is low, the chromosome karyotype analysis work efficiency is low, the labor intensity is high, the culture period of professional talents is long, the problems of chromosome counting, segmentation, classification and the like are solved by using a digital image processing technology, the analysis efficiency of workers can be improved, the labor intensity is reduced, and the culture period of the professional talents is reduced.

Disclosure of Invention

In order to overcome the defects in the background art, the invention discloses an overlapped chromosome segmentation method, which effectively improves the accuracy and the high efficiency of the detection and analysis of the chromosome karyotype.

In order to realize the purpose, the invention adopts the following technical scheme:

a method for segmenting overlapping chromosomes specifically comprises the following steps:

step S100, carrying out edge extraction on the overlapped chromosome image, obtaining edge outlines of all overlapped chromosomes, and adding all edge outline points into a set of cutting points to be selected;

step S200, extracting a skeleton, a skeleton end point and a skeleton intersection point of the overlapped chromosome image;

step S300, determining the cutting points of the overlapped chromosomes according to the edge contour of the overlapped chromosomes obtained in the step S100 and the chromosome skeleton, the skeleton end points and the intersection points obtained in the step S200;

and S400, automatically segmenting the overlapped chromosomes through an automatic segmentation method according to the segmentation points in the step S300.

The step S200 specifically includes the following steps:

step S201, a thinning algorithm is adopted to thin the overlapped chromosome image into a chromosome skeleton with only one pixel point, and the overlapped chromosome skeleton is extracted;

step S202, positioning skeleton endpoints and intersections according to the number of adjacent pixel points;

the step S300 specifically includes the following steps:

s301, calculating the Euclidean distance from the cutting point to be selected to the central point by taking the skeleton intersection point as the center according to the chromosome skeleton and the skeleton intersection point in the step S200, setting the distance, and removing all contour points which are greater than the distance in the cutting point set to be selected;

and S302, according to the calculation result of S301, subdividing the to-be-selected set points into 3 or 4 subsets according to a clustering algorithm, counting the set number of the to-be-selected cut points, calculating the Euclidean distance from the central point in the step S301 in each subset, selecting the to-be-selected cut point with the minimum distance, determining the to-be-selected cut point as the optimal cut point of the overlapped chromosomes, and counting the to-be-selected cut point into a cut point set.

S303, judging whether the number of the optimal cutting points is 4 or not according to the calculation result of the S302, if so, carrying out S304, and if not, carrying out S305;

s304, connecting the 4 connecting points pairwise, wherein 3 connecting modes are provided, sequentially judging whether the connecting lines of the 4 cutting points are crossed, and if not, respectively cutting the overlapped chromosome images sequentially through the 2 connecting modes.

S305, respectively calculating curvatures of the 3 cutting points, taking two points with smaller curvatures as candidate cutting points A, B, and selecting a cutting point C with larger curvature to be connected with the central point O in the S301 to form a line segment OC;

s306, according to the line segment OC in the step S403, calculating the slope of the line segment OC, drawing a parallel line L1 parallel to the OC, making L1 pass through a candidate cut point A to intersect with the chromosome contour at a point D1, drawing a parallel line L2 parallel to the OC, making L2 pass through a candidate cut point B to intersect with the chromosome contour at a point D2, and taking D1 and D2 as candidate cut points.

S307, according to the method in the step S306, the obtained 4 candidate cutting points are A, B, D1 and D2 respectively, and the step S303 is returned to.

S400, automatically segmenting the overlapped chromosomes according to the segmentation points in the step S300 by an automatic segmentation method.

Due to the adoption of the technical scheme, the invention has the following beneficial effects:

the invention relates to an overlapped chromosome segmentation method, which comprises the following steps of S100, carrying out edge extraction on an overlapped chromosome image, obtaining edge outlines of all overlapped chromosomes, and adding all edge outline points into a set of cutting points to be selected; step S200, extracting a skeleton, a skeleton end point and a skeleton intersection point of the overlapped chromosome image; step S300, determining the cutting points of the overlapped chromosomes according to the edge contour of the overlapped chromosomes obtained in the step S100 and the chromosome skeleton, the skeleton end points and the intersection points obtained in the step S200; and S400, automatically segmenting the overlapped chromosomes according to the cutting points. According to the contour and skeleton-based overlapped chromosome segmentation method, all contour points are regarded as cut points and used as candidate sets by combining the relation between the contour and the skeleton of the chromosome by utilizing the overlapped features of the overlapped chromosomes, a series of complex processes of curvature calculation are omitted, and the optimal cut points are accurately positioned by combining Euclidean distance with the skeleton of the chromosome.

Drawings

FIG. 1 is a flow chart of a method for segmenting an image of an overlapping chromosome karyotype based on a contour and a skeleton according to the present invention;

FIG. 2 is a graph showing the edge detection effect of the overlapping chromosome edge detection method used in the present invention;

FIG. 3 is a flowchart of a "+" shaped overlapping chromosome segmentation effect and a chromosome automatic segmentation method according to an embodiment of the present invention;

FIG. 4 is a diagram of the segmentation effect of the T-shaped overlapped chromosomes and a flowchart of the automatic chromosome segmentation method in accordance with embodiment 2 of the present invention.

Detailed Description

The present invention will be explained in detail by the following examples, which are disclosed for the purpose of protecting all technical improvements within the scope of the present invention.

The method for segmenting the overlapped chromosomes, which is described in conjunction with the accompanying drawings 1-4, is an overlapped chromosome karyotype image segmentation method based on a contour and a skeleton, and the segmentation method specifically comprises the following steps:

step S100, carrying out edge extraction on the overlapped chromosome image, obtaining edge outlines of all overlapped chromosomes, and adding all edge outline points into a set of cutting points to be selected;

step S200, extracting a skeleton, a skeleton end point and a skeleton intersection point of the overlapped chromosome image;

step S300, determining the cutting points of the overlapped chromosomes according to the edge contour of the overlapped chromosomes obtained in the step S100 and the chromosome skeleton, the skeleton end points and the intersection points obtained in the step S200;

and S400, automatically segmenting the overlapped chromosomes through an automatic segmentation method according to the segmentation points in the step S300.

The detailed steps of the method for automatically segmenting overlapping chromosomes according to the present invention are described below by two specific examples.

Example 1:

although the forms of the overlapped chromosomes are different, they basically belong to two types including a "+" type and a "T" type or a superposition of the two types, so the following steps will apply the automatic segmentation method according to the present invention based on the "+" type overlapped chromosomes by way of illustration.

The invention provides an overlapped chromosome segmentation algorithm, which is an overlapped chromosome karyotype image segmentation method based on a contour and a skeleton, and the segmentation method specifically comprises the following steps:

step 1, before performing the edge contour extraction in step S100, preprocessing an overlapping chromosome map, first performing noise reduction on an image by smooth filtering to remove noise influence, then performing image enhancement on the image by histogram equalization to improve the contrast between a chromosome image and a background, next performing binarization operation, separating a foreground of a chromosome karyotype image from the background by using a threshold value, removing most of irrelevant areas to obtain a preprocessed overlapping chromosome karyotype map, next performing the specific steps in step S100, and performing the edge contour extraction by using the preprocessed overlapping chromosome karyotype map, wherein the specific steps specifically include the following specific steps:

step 1.1, firstly, carrying out convolution operation on the operator and the original image by adopting a Gaussian filtering algorithm, and carrying out smooth filtering on the original image to obtain an output image with Gaussian noise eliminated.

And step 1.2, performing convolution operation on the output image in the step 1.1 and a gradient operator, and obtaining a gradient amplitude and a gradient direction through calculation.

Step 1.3, then carrying out non-maximum value suppression treatment, taking pixels in the image as an origin, respectively making bidirectional dividing lines passing through the origin at 45 degrees and 135 degrees, comparing the pixel value of the origin with pixel values of two adjacent pixels along the dividing lines, and if the pixel value of the origin is larger, keeping the original; otherwise, return to zero.

Step 1.4, finally, performing double-threshold hysteresis threshold processing, setting high and low (Th and Tl) threshold calculation factors, setting the points which are higher than Th as strong edge points, setting the points which are lower than Tl as 0, setting the points which are between the high and low thresholds and are not connected with the strong edge points as 0, finally obtaining overlapped chromosomes to obtain edge contours, and recording all the contour points into a candidate cut point set P, wherein the attached figure 1 is a chromosome karyotype graph edge detection effect graph.

Step 2, extracting a chromosome skeleton according to the overlapped chromosome karyotype image preprocessed in the step 1 by using the following method, wherein the method specifically comprises the following steps: the method comprises the steps of firstly, calculating step by step according to a thinning algorithm, thinning a chromosome image into a chromosome skeleton, then, positioning skeleton endpoints of the chromosome according to the connection relation of pixel points, recording in an endpoint set according to a division standard that no pixel value exists on three sides of the endpoints, then, extracting the positions of skeleton intersections according to a pixel point discrimination method, and recording in an intersection set of the skeleton.

And 3, screening the segmentation points by combining the chromosome binary image edge contour and the skeleton intersection point, and obtaining accurate overlapped chromosome segmentation points through screening, wherein the method specifically comprises the following steps:

and 3.1, calculating the Euclidean distance from the cutting point to be selected to the central point by taking the skeleton intersection point as the center according to the chromosome skeleton and the skeleton intersection point in the step 1 and the step 2, setting the distance, removing all contour points which are greater than the distance in the cutting point set to be selected, and obtaining the cutting point to be selected after screening, wherein the cutting point to be selected is a schematic diagram of the cutting point to be selected after being segmented according to the step 3.1, as shown in the picture 4 in the attached figure 2.

And 3.2, according to the calculation result of the step 3.1, subdividing the to-be-selected set points into 4 subsets according to a clustering algorithm, counting the set number of the to-be-selected cut points, calculating the Euclidean distance from the central point in the step S301 in each subset, selecting the to-be-selected cut point with the minimum distance, determining the to-be-selected cut point as the optimal cut point of the overlapped chromosomes, and counting the to-be-selected cut point into a cut point set, as shown in the 5 th picture in the attached figure 2, the to-be-selected set point is the optimal cut point schematic diagram obtained according to the step 3.2.

And 3.3, judging whether the optimal cutting points are 4, and if the optimal cutting points to be selected are 4, executing the step 3.4.

And 3.4, connecting the 4 connecting points pairwise, wherein 3 connecting modes are provided, sequentially judging whether the connecting lines of the 4 cutting points are crossed, and if not, respectively cutting the overlapped chromosome images sequentially through the 2 connecting modes.

And 4, automatically segmenting the overlapped chromosomes by an automatic segmentation method according to the optimal segmentation points in the step 3.3.

Example 2:

in the following embodiment 2 showing the chromosome based on the "T" font overlap, the specific steps in the process of applying the chromosome karyotype image automatic segmentation method described in the present invention include the following:

step 1, the overlapped chromosome map is also required to be preprocessed before the edge contour extraction in step S100. Firstly, carrying out noise reduction on an image through smooth filtering, removing noise influence, then carrying out image enhancement on the image through histogram equalization, improving the contrast ratio of a chromosome image and a background, then carrying out binarization operation, separating the foreground of a chromosome karyotype image from the background by using a threshold value, removing most irrelevant areas, obtaining a preprocessed overlapped chromosome karyotype image, then carrying out the specific steps of the step S100, and carrying out edge contour extraction by using the preprocessed overlapped chromosome karyotype image, wherein the specific steps comprise the following specific steps:

step 1.1, firstly, carrying out convolution operation on the operator and the original image by adopting a Gaussian filtering algorithm, and carrying out smooth filtering on the original image to obtain an output image with Gaussian noise eliminated.

And step 1.2, performing convolution operation on the output image in the step 1.1 and a gradient operator, and obtaining a gradient amplitude and a gradient direction through calculation.

Step 1.3, then carrying out non-maximum value suppression treatment, taking pixels in the image as an origin, respectively making bidirectional dividing lines passing through the origin at 45 degrees and 135 degrees, comparing the pixel value of the origin with pixel values of two adjacent pixels along the dividing lines, and if the pixel value of the origin is larger, keeping the original; otherwise, return to zero.

Step 1.4, finally, performing double-threshold hysteresis threshold processing, setting high and low (Th and Tl) threshold calculation factors, setting the points which are higher than Th as strong edge points, setting the points which are lower than Tl as 0, setting the points which are between the high and low thresholds and are not connected with the strong edge points as 0, finally obtaining overlapped chromosomes to obtain edge contours, and recording all the contour points into a candidate cut point set P, wherein the attached figure 1 is a chromosome karyotype graph edge detection effect graph.

Step 2, extracting a chromosome skeleton according to the overlapped chromosome karyotype image preprocessed in the step 1 by using the following method, wherein the method specifically comprises the following steps: the method comprises the steps of firstly, calculating step by step according to a thinning algorithm, thinning a chromosome image into a chromosome skeleton, then, positioning skeleton endpoints of the chromosome according to the connection relation of pixel points, recording in an endpoint set according to a division standard that no pixel value exists on three sides of the endpoints, then, extracting the positions of skeleton intersections according to a pixel point discrimination method, and recording in an intersection set of the skeleton.

And 3, screening the segmentation points by combining the chromosome binary image edge contour and the skeleton intersection point, and obtaining accurate overlapped chromosome segmentation points through screening, wherein the method specifically comprises the following steps:

and 3.1, calculating the Euclidean distance from the cutting point to be selected to the central point by taking the skeleton intersection point as the center according to the chromosome skeleton and the skeleton intersection point in the step 1 and the step 2, setting the distance, removing all contour points which are greater than the distance in the cutting point set to be selected, and obtaining the cutting point to be selected after screening, wherein the contour points are shown as the picture 4 in the picture 3 and are schematic diagrams of the cutting point to be selected after screening according to the step 3.1.

And 3.2, according to the calculation result of the step 3.1, subdividing the to-be-selected set points into 3 subsets according to a clustering algorithm, counting the set number of the to-be-selected cut points, calculating the Euclidean distance from the central point in the step S301 in each subset, selecting the to-be-selected cut point with the minimum distance, determining the to-be-selected cut point as the optimal cut point of the overlapped chromosomes, and counting the to-be-selected cut point into a cut point set, as shown in the 5 th picture in the attached figure 3, the to-be-selected set point is the optimal cut point schematic diagram obtained according to the step 3.2.

And 3.3, judging whether the optimal cutting points are 4, if the optimal cutting points to be selected are 4, executing the step 3.4, and according to the embodiment 2, only 3 optimal cutting points can be obtained in the step 3.2, so that the step 3.5 is executed.

And 3.4, connecting the 4 connecting points pairwise, wherein 3 connecting modes are provided, sequentially judging whether the connecting lines of the 4 cutting points are crossed, if not, respectively cutting the overlapped chromosome images sequentially through the 2 connecting modes, and executing the step 4.

Step 3.5, respectively calculating the curvatures of the 3 cutting points, taking two points with smaller curvatures as candidate cutting points A, B, and selecting a cutting point C with larger curvature to be connected with the central point O obtained in the step 2 to form a line segment OC;

and 3.6, calculating the slope of the line segment OC according to the line segment OC obtained in the step 3.5, drawing a parallel line L1 parallel to the OC, drawing a parallel line L2 parallel to the OC after the L1 passes through the candidate cut point A and intersects with the chromosome contour at a point D1, drawing a parallel line L2 parallel to the OC after the L2 passes through the candidate cut point B and intersects with the chromosome contour at a point D2, taking D1 and D2 as candidate cut points, and returning to the step 3.4.

And 4, automatically segmenting the overlapped chromosomes by an automatic segmentation method according to the optimal cutting point connection method in the step 3.4.

While the invention has been particularly shown and described with reference to a preferred embodiment, it will be understood by those skilled in the art that various changes in form and detail may be made therein without departing from the spirit and scope of the invention as defined by the appended claims.

Claims (7)

1. A method for segmentation of overlapping chromosome karyotypes, characterized in that automatic segmentation is performed on overlapping chromosomes, said segmentation method comprising the steps of:

step S100, carrying out edge extraction on the overlapped chromosome image, obtaining edge outlines of all overlapped chromosomes, and adding all edge outline points into a set of cutting points to be selected;

step S200, extracting a skeleton, a skeleton end point and a skeleton intersection point of the overlapped chromosome image;

step S300, determining the cutting points of the overlapped chromosomes according to the edge contour of the overlapped chromosomes obtained in the step S100 and the chromosome skeleton, the skeleton end points and the intersection points obtained in the step S200;

and S400, automatically segmenting the overlapped chromosomes through an automatic segmentation method according to the segmentation points in the step S300.

2. The method of overlapping chromosome segmentation as set forth in claim 1, wherein: the method used in the overlapping chromosome edge contour extraction method in step S100 is a contour extraction method based on the Canny operator.

3. The method of overlapping chromosome segmentation as set forth in claim 1, wherein: the above-mentioned

The method comprises the following steps of extracting a skeleton, skeleton endpoints and skeleton intersections of overlapped chromosome images, wherein the step S200 specifically comprises the following steps:

step S201, a thinning algorithm is adopted to thin the overlapped chromosome image into a chromosome skeleton with only one pixel point, and the overlapped chromosome skeleton is extracted;

step S202, positioning the skeleton endpoint, namely the number of pixels in the neighborhood is 1 according to the number of the refined adjacent pixels;

step S203, positioning the framework cross point according to the number of the neighborhood pixel points.

4. The method of overlapping chromosome segmentation as set forth in claim 1, wherein: the automatic segmentation method of the overlapped chromosomes is in a shape of a plus sign and a T or the superposition of the two types.

5. The method of overlapping chromosome segmentation according to claim 4, wherein: the method for determining the overlapped chromosome cutting point by using the overlapped chromosome edge contour method obtained in the step S100 and the chromosome skeleton, the skeleton end points and the intersection points obtained in the step S200 specifically includes the following steps:

s301, calculating the Euclidean distance from the cutting point to be selected to the central point by taking the skeleton intersection point as the center according to the chromosome skeleton and the skeleton intersection point in the step S200, setting the distance, and removing all contour points which are greater than the distance in the cutting point set to be selected;

s302, according to the calculation result of S301, subdividing the to-be-selected set points into 3 or 4 subsets according to a clustering algorithm, counting the set number of the to-be-selected cut points, calculating Euclidean distances between the to-be-selected cut points and the central point in the step S301 in each subset, selecting the to-be-selected cut point with the minimum distance, determining the to-be-selected cut point as the optimal cut point of the overlapped chromosomes, and counting the to-be-selected cut point into a cut point set;

s303, judging whether the number of the optimal cutting points is 4 or not according to the calculation result of the S302, if so, carrying out S304, and if not, carrying out S305;

s304, connecting the 4 connecting points pairwise, wherein 3 connecting modes are provided, sequentially judging whether the connecting lines of the 4 cutting points are crossed, and if not, respectively cutting the overlapped chromosome images sequentially through the 2 connecting modes;

s305, respectively calculating curvatures of the 3 cutting points, taking two points with smaller curvatures as candidate cutting points A, B, and selecting a cutting point C with larger curvature to be connected with the central point O in the S301 to form a line segment OC;

s306, according to the line segment OC in the step S403, calculating the slope of the line segment OC, drawing a parallel line L1 parallel to the OC, making L1 pass through a candidate cut point A to intersect with the chromosome contour at a point D1, drawing a parallel line L2 parallel to the OC, making L2 pass through a candidate cut point B to intersect with the chromosome contour at a point D2, and taking D1 and D2 as candidate cut points;

s307, according to the method in the step S306, acquiring that the 4 candidate cutting points are A, B, D1 and D2 respectively, and returning to the step S303;

s400, automatically segmenting the overlapped chromosomes according to the segmentation points in the step S300 by an automatic segmentation method.

6. The method of overlapping chromosome segmentation as set forth in claim 5, wherein: the automatic segmentation method based on the application of the '+' font overlapped chromosome, namely the overlapped chromosome karyotype image segmentation method based on the contour and the skeleton, specifically comprises the following steps:

step 1, before performing the edge contour extraction in step S100, preprocessing an overlapping chromosome map, first performing noise reduction on an image by smooth filtering to remove noise influence, then performing image enhancement on the image by histogram equalization to improve the contrast between a chromosome image and a background, next performing binarization operation, separating a foreground of a chromosome karyotype image from the background by using a threshold value, removing most of irrelevant areas to obtain a preprocessed overlapping chromosome karyotype map, next performing the specific steps in step S100, and performing the edge contour extraction by using the preprocessed overlapping chromosome karyotype map, wherein the specific steps specifically include the following specific steps:

step 1.1, firstly, carrying out convolution operation on an operator and an original image by adopting a Gaussian filtering algorithm, and carrying out smooth filtering on the original image to obtain an output image with Gaussian noise eliminated;

step 1.2, performing convolution operation on the output image in the step 1.1 and a gradient operator, and obtaining a gradient amplitude and a gradient direction through calculation;

step 1.3, then carrying out non-maximum value suppression treatment, taking pixels in the image as an origin, respectively making bidirectional dividing lines passing through the origin at 45 degrees and 135 degrees, comparing the pixel value of the origin with pixel values of two adjacent pixels along the dividing lines, and if the pixel value of the origin is larger, keeping the original; otherwise, returning to zero;

step 1.4, finally, carrying out double-threshold hysteresis threshold processing, setting high and low (Th and Tl) threshold calculation factors, marking the points higher than Th as strong edge points, setting the points smaller than Tl as 0, setting the points between the high and low thresholds and the points which are not connected with the strong edge points as 0, finally obtaining overlapped chromosomes to obtain edge contours, and recording all contour points into a candidate cut point set P;

step 2, extracting a chromosome skeleton according to the overlapping chromosome karyotype image preprocessed in the step 1.1-1.4 by using the following method, wherein the method specifically comprises the following steps: firstly, gradually calculating according to a thinning algorithm, thinning a chromosome image into a chromosome skeleton, then positioning skeleton endpoints of the chromosome according to the connection relation of pixel points, recording in an endpoint set according to a division standard that no pixel value exists on three sides of the endpoints, then extracting the positions of skeleton intersections according to a pixel point discrimination method, and recording in an intersection set of the skeleton;

and 3, screening the segmentation points by combining the chromosome binary image edge contour and the skeleton intersection point, and obtaining accurate overlapped chromosome segmentation points through screening, wherein the method specifically comprises the following steps:

step 3.1, calculating the Euclidean distance from the cutting point to be selected to the central point by taking the skeleton intersection point as the center according to the chromosome skeleton and the skeleton intersection point in the steps 1.1-1.4 and 2, setting the Euclidean distance for the distance, removing all contour points which are greater than the distance in the cutting point set to be selected, and obtaining the screened cutting point to be selected;

step 3.2, according to the calculation result of the step 3.1, the set points to be selected are divided into 4 subsets again according to a clustering algorithm, the set number of the cutting points to be selected is counted, the Euclidean distance from the central point in the step S301 in each subset is calculated, the cutting point to be selected with the minimum distance is selected to be determined as the optimal cutting point of the overlapped chromosomes, and the optimal cutting point is counted into a cutting point set;

step 3.3, judging whether the optimal cutting points are 4, and if the optimal cutting points to be selected are 4, executing the step 3.4;

step 3.4, connecting the 4 connecting points pairwise, wherein 3 connecting modes are provided, sequentially judging whether the connecting lines of the 4 cutting points are crossed, and if not, respectively cutting the overlapped chromosome images sequentially through the 2 connecting modes;

and 4, automatically segmenting the overlapped chromosomes by an automatic segmentation method according to the optimal segmentation points in the step 3.3.

7. The method of overlapping chromosome segmentation as set forth in claim 5, wherein: the application based on the T-shaped overlapping chromosome in the automatic segmentation method process of the chromosome karyotype image comprises the following specific steps:

step 1, before performing the edge contour extraction in step S100, preprocessing an overlapping chromosome map, first performing noise reduction on an image by smooth filtering to remove noise influence, then performing image enhancement on the image by histogram equalization to improve the contrast between a chromosome image and a background, next performing binarization operation, separating a foreground of a chromosome karyotype image from the background by using a threshold value, removing most of irrelevant areas to obtain a preprocessed overlapping chromosome karyotype map, next performing the specific steps in step S100, and performing the edge contour extraction by using the preprocessed overlapping chromosome karyotype map, wherein the specific steps specifically include the following specific steps:

step 1.1, firstly, carrying out convolution operation on an operator and an original image by adopting a Gaussian filtering algorithm, and carrying out smooth filtering on the original image to obtain an output image with Gaussian noise eliminated;

step 1.2, performing convolution operation on the output image in the step 1.1 and a gradient operator, and obtaining a gradient amplitude and a gradient direction through calculation;

step 1.3, then carrying out non-maximum value suppression treatment, taking pixels in the image as an origin, respectively making bidirectional dividing lines passing through the origin at 45 degrees and 135 degrees, comparing the pixel value of the origin with pixel values of two adjacent pixels along the dividing lines, and if the pixel value of the origin is larger, keeping the original; otherwise, returning to zero;

step 1.4, finally, carrying out double-threshold hysteresis threshold processing, setting high and low (Th and Tl) threshold calculation factors, marking the points higher than Th as strong edge points, setting the points smaller than Tl as 0, setting the points between the high and low thresholds and the points which are not connected with the strong edge points as 0, finally obtaining overlapped chromosomes to obtain edge contours, and recording all contour points into a candidate cut point set P;

step 2, extracting a chromosome skeleton according to the overlapping chromosome karyotype image preprocessed in the step 1.1-1.4 by using the following method, wherein the method specifically comprises the following steps: firstly, gradually calculating according to a thinning algorithm, thinning a chromosome image into a chromosome skeleton, then positioning skeleton endpoints of the chromosome according to the connection relation of pixel points, recording in an endpoint set according to a division standard that no pixel value exists on three sides of the endpoints, then extracting the positions of skeleton intersections according to a pixel point discrimination method, and recording in an intersection set of the skeleton;

and 3, screening the segmentation points by combining the chromosome binary image edge contour and the skeleton intersection point, and obtaining accurate overlapped chromosome segmentation points through screening, wherein the method specifically comprises the following steps:

step 3.1, calculating the Euclidean distance from the cutting point to be selected to the central point by taking the skeleton intersection point as the center according to the chromosome skeleton and the skeleton intersection point in the steps 1.1-1.4 and 2, setting the Euclidean distance for the distance, removing all contour points which are greater than the distance in the cutting point set to be selected, and obtaining the screened cutting point to be selected;

step 3.2, according to the calculation result of the step 3.1, the set points to be selected are divided into 3 subsets again according to a clustering algorithm, the set number of the cutting points to be selected is counted, the Euclidean distance between the set points to be selected and the central point in the step S301 in each subset is calculated, the cutting point to be selected with the minimum distance is selected to be determined as the optimal cutting point of the overlapped chromosomes, and the optimal cutting point is counted into a cutting point set;

step 3.3, judging whether the optimal cutting points are 4, if the optimal cutting points to be selected are 4, executing step 3.4, and according to the embodiment 2, only 3 optimal cutting points can be obtained in the step 3.2, so that the step 3.5 is executed;

step 3.4, connecting the 4 connecting points pairwise, wherein 3 connecting modes are provided, sequentially judging whether the connecting lines of the 4 cutting points are crossed, if not, respectively cutting the overlapped chromosome images sequentially through the 2 connecting modes, and executing the step 4; step 3.5, respectively calculating the curvatures of the 3 cutting points, taking two points with smaller curvatures as candidate cutting points A, B, and selecting a cutting point C with larger curvature to be connected with the central point O obtained in the step 2 to form a line segment OC;

step 3.6, according to the line segment OC obtained in step 3.5, calculating the slope of the line segment OC, drawing a parallel line L1 parallel to OC, wherein L1 crosses the chromosome contour through the candidate cut point a at a point D1, drawing a parallel line L2 parallel to OC, wherein L2 crosses the chromosome contour through the candidate cut point B at a point D2, taking D1 and D2 as candidate cut points, and returning to step 3.4;

and 4, automatically segmenting the overlapped chromosomes by an automatic segmentation method according to the optimal cutting point connection method in the step 3.4.

Images