CN111595758B - Oval cell detection device and detection method based on lens-free imaging - Google Patents
Oval cell detection device and detection method based on lens-free imaging Download PDFInfo
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Abstract
The invention discloses an elliptical cell detection device based on lens-free imaging, which comprises a lamp light box and a circuit board protection box which are arranged up and down, wherein an LED light source, a convex lens and a CMOS image sensor are arranged in the lamp light box. The invention relates to a detection method of elliptic cells, which is used for detecting elliptic cells by using the elliptic cell detection device based on lens-free imaging, and comprises the steps of manufacturing and fixing an elliptic cell sample to be detected, starting an LED light source, collecting image data by a CMOS image sensor, processing the image data, and judging whether the elliptic cells are normal elliptic cells according to the difference between the major axis and the minor axis of the elliptic cells.
Description
Technical Field
The invention belongs to the technical field of medical image analysis, and relates to an elliptic cell detection device based on lens-free imaging and a detection method of elliptic cells.
Background
Blood cell morphology parameters are very valuable data for disease diagnosis, health monitoring, and new drug development. The usual way to acquire this data is to acquire an image of the cells for analysis. Optical microscope is used for collecting equipment. In order to ensure imaging quality, the optical microscope has to employ complex multi-lens groups. The problem of miniaturizing optical microscopes has been limited by the lens group. In the application scenes facing emergency situations such as sudden epidemic situations or immediate detection such as acquisition site detection, the higher professional requirements and the manufacturing cost become elbows, which are unfavorable for quick deployment, low-cost large-scale deployment and immediate detection.
In 2006, the Yang changhuei research group of university of California, U.S. first proposed the concept of a lens-free optofluidic microchip. The advantage of this device is that the use of an image sensor not only reduces the manufacturing and use costs of the device, but also increases portability. The method has more advantages in application scenes facing rapid deployment, low-cost large-scale deployment and instant detection.
There are two problems with a lensless device that need to be addressed: 1. because the pixel size of the commercial image sensor is very close to that of blood cells, the resolution of the cell image acquired by the lens-free imaging system is low; 2. contact imaging with less diffraction interference requires that the imaging sample must be reduced to several visible wavelengths from the image sensor, which is difficult to achieve with commercial sensors and has to be done with diffraction imaging with interference. Therefore, how to obtain accurate cell morphology parameters becomes a difficulty in research in the case of using a commercial sensor.
Disclosure of Invention
The invention aims to provide an elliptical cell detection device based on lens-free imaging, which can accurately detect elliptical cells under the conditions of low resolution and serious diffraction interference when a lens-free imaging system collects cell images.
It is another object of the present invention to provide a method for detecting elliptic cells, which can accurately detect elliptic cells.
The invention adopts a first technical scheme that the elliptic cell detection device based on lens-free imaging comprises a lamp light box and a circuit board protection box which are arranged up and down, wherein an LED light source, a convex lens and a CMOS image sensor which are positioned on the same axis are sequentially arranged in the lamp light box from top to bottom, the CMOS image sensor is positioned on the circuit board protection box, and a CMOS image sensor circuit connected with the CMOS image sensor is arranged in the circuit board protection box.
The first technical solution of the invention is also characterized in that,
the lamp light box is rotationally connected with the circuit board protection box, the lamp light box can rotate on the circuit board protection box, the side wall of the lamp light box is provided with an opening, and a light shielding plate matched with the opening of the lamp light box is fixed on the circuit board protection box.
The CMOS image sensor is provided with a sample pad at its periphery.
The sample pad is provided with a sample clamping groove.
The invention relates to a detection method of elliptic cells, which is applied to the detection of elliptic cells based on lens-free imaging and is implemented according to the following steps:
step 1, preparing an elliptic cell sample to be tested;
step 4, opening the CMOS image sensor, and exporting the acquired image data to a processing module of the CMOS image sensor circuit through a data interface;
Step 10, the diameter of the diffraction ring is represented by the sum of two radiuses, namely, the matching radius is used for obtaining the angle alpha of the diffraction ring 1 ,α 2 ,…,α i The diameter length at i is a natural number other than 0:
in the formula (10), D 1 (α 1 ),D 2 (α 2 ),…,D i (α i ) Is the diffraction ring at angle alpha 1 ,α 2 ,…,α i Diameter length at the location;
define set a to represent these data:
A＝{D 1 (α 1 ),D 2 (α 2 )，…，D i (α i )} (11)；
step 11, carrying out matching identification of elliptic cells, wherein the shadow length of the elliptic long axis position is expressed as:
D maj (α maj )＝min(A) (12)
let pi/4 < alpha maj < 3pi/4, definition set B is expressed as
B＝{D 1 (β 1 ),D 2 (β 2 )，…，D i (β i )} (13)
The length of the shadow at the location of the minor axis of the ellipse can be expressed as:
D min (α min )＝min(B)
the definition parameter M represents the difference between the major and minor axes of elliptic cells:
M＝|D maj (α maj )-D min (α min )|
defining a threshold M T If M > M T Then the judgment isNormal oval cells, otherwise other cells.
The second technical proposal of the invention is also characterized in that,
obtaining a curve of the distance from the strongest light intensity point of the diffraction bright ring to the center of the cell diffraction ring according to the radial super-resolution and the circumferential super-resolution: the radial super-resolution is to find the fastest rising point and the fastest falling point of the peak corresponding to the diffraction bright ring, and correct the position of the peak maximum value point by the intersection point of the slopes of the two points; circumferential super-resolution is reduced in noise through Gaussian smoothing, and further, the characterization position of the diffraction bright ring after correction is obtained; and calculating the distance from the diffraction light ring to the cell diffraction ring through the characterization position of the diffraction light ring, and obtaining a curve of the distance from the strongest light intensity point of the diffraction light ring to the center of the cell diffraction ring.
The beneficial effects of the invention are as follows:
the elliptic cell detection device based on lens-free imaging has stable structure and simple device; setting application scenes such as quick deployment, low-cost large-scale deployment, instant detection and the like; the method has the advantages of low cost and high portability; the elliptical cell detection device can accurately detect elliptical cells under the conditions of low resolution and serious diffraction interference when a lens-free imaging system collects cell images, and achieves miniaturization of the elliptical cell detection device.
The detection method of the elliptic cells is simple and clear, has strong operability, improves the automation degree of elliptic cell measurement, and reduces the labor cost of operation.
Drawings
FIG. 1 is a schematic diagram of the structure of an elliptical cell detection device based on lens-free imaging of the present invention.
In the figure, a lamp light box, a 2 LED light source, a 3 convex lens, a 4 sample clamping groove, a 5 shading plate, a 6 sample pad, a 7 CMOS image sensor, an 8 circuit board protection box and a 9 sample pad.
Detailed Description
The invention will be described in detail below with reference to the drawings and the detailed description.
The invention discloses an elliptical cell detection device based on lens-free imaging, which is shown in fig. 1 and comprises a lamp light box 1 and a circuit board protection box 8 which are arranged up and down, wherein the lamp light box 1 is rotatably connected with the circuit board protection box 8, the lamp light box 1 can rotate on the circuit board protection box 8, the side wall of the lamp light box 1 is provided with an opening, a light shielding plate 5 matched with the opening of the lamp light box 1 is fixed on the circuit board protection box 8, an LED light source 2, a convex lens 3 and a CMOS image sensor 7 which are positioned on the same axis are sequentially arranged in the lamp light box 1 from top to bottom, a sample pad 9 is arranged on the periphery of the CMOS image sensor 7, a sample clamping groove 4 is arranged on the sample pad 9, the CMOS image sensor 7 is positioned on the circuit board protection box 8, and a CMOS image sensor circuit connected with the CMOS image sensor 7 is arranged in the circuit board protection box 8.
The invention relates to a detection method of elliptic cells, which is applied to the detection of elliptic cells by the device based on lens-free imaging, and is implemented according to the following steps:
step 1, manufacturing an oval cell sample 6 to be tested.
And 2, placing the oval cell sample 6 to be detected on the CMOS image sensor 7, fixing the oval cell sample in the sample clamping groove 4, and rotating the lamp light box 1 to enable an opening of the lamp light box and a shading plate to form a closed collection chamber.
And 3, starting the LED light source 2, and enabling light rays emitted by the LED light source 2 to be gathered through the convex lens 3 and vertically emitted to the oval cell sample 6 to be detected.
And 4, opening the CMOS image sensor 7, and exporting the acquired image data to a processing module of the CMOS image sensor circuit through a data interface.
And 5, detecting the center of the blood cells by using a Hough transform algorithm on the derived image data, and dividing the image according to the center of the blood cells to detect a blood cell diffraction ring.
And 6, carrying out sub-pixel interpolation operation on the basis of the step 5 to obtain a sub-pixel image, and converting the sub-pixel image from a rectangular coordinate system to a polar coordinate system by taking the center coordinates obtained in the step 5 as the center.
obtaining a curve of the distance from the strongest light intensity point of the diffraction bright ring to the center of the cell diffraction ring according to the radial super-resolution and the circumferential super-resolution: the radial super-resolution is to find the fastest rising point and the fastest falling point of the peak corresponding to the diffraction bright ring, and correct the position of the peak maximum value point by the intersection point of the slopes of the two points; circumferential super-resolution is reduced in noise through Gaussian smoothing, and further, the characterization position of the diffraction bright ring after correction is obtained; and calculating the distance from the diffraction light ring to the cell diffraction ring through the characterization position of the diffraction light ring, and obtaining a curve of the distance from the strongest light intensity point of the diffraction light ring to the center of the cell diffraction ring.
And 8, calculating a light intensity maximum point of the diffraction bright ring according to the distance curve in the step 6, and representing the position of the diffraction bright ring.
Step 10, representing the diameter of the diffraction ring by the sum of two radiuses, and matching the radiuses to obtain the angle alpha of the diffraction ring 1 ,α 2 ,…,α i The diameter length at i is a natural number other than 0:
in the formula (10), D 1 (α 1 ),D 2 (α 2 ),…,D i (α i ) Is the diffraction ring at angle alpha 1 ,α 2 ,…,α i Diameter length at the location;
define set a to represent these data:
A＝{D 1 (α 1 ),D 2 (α 2 )，…，D i (α i )} (11)。
step 11, carrying out matching identification of elliptic cells, wherein the shadow length of the elliptic long axis position is expressed as:
D maj (α maj )＝min(A) (12)
let pi/4 < alpha maj < 3pi/4, definition set B is expressed as
B＝{D 1 (β 1 ),D 2 (β 2 )，…，D i (β i )} (13)
The length of the shadow at the location of the minor axis of the ellipse can be expressed as:
D min (α min )＝min(B)
the definition parameter M represents the difference between the major and minor axes of elliptic cells:
M＝|D maj (α maj )-D min (α min )|
defining a threshold M T If M > M T Then a normal oval cell is judged, otherwise other cells.
Claims (2)
1. The method is characterized in that the method is used for detecting elliptic cells by using an elliptic cell detection device based on lens-free imaging, the elliptic cell detection device based on lens-free imaging comprises a lamp light box (1) and a circuit board protection box (8), wherein an LED light source (2), a convex lens (3) and a CMOS image sensor (7) which are positioned on the same axis are sequentially arranged in the lamp light box (1) from top to bottom, the CMOS image sensor (7) is positioned on the circuit board protection box (8), a CMOS image sensor circuit connected with the CMOS image sensor (7) is arranged in the circuit board protection box (8), a sample pad (9) is arranged on the periphery of the CMOS image sensor (7), a sample clamping groove (4) is formed in the sample pad (9), the lamp light box (1) is rotatably connected with the circuit board protection box (8), the side wall of the lamp light box (1) is arranged on the circuit board protection box (8) and is provided with an opening, and the lamp light box (1) is fixedly matched with the opening (5) of the circuit board protection box (8);
the method is implemented according to the following steps:
step 1, preparing an elliptic cell sample (6) to be tested;
step 2, placing the oval cell sample (6) to be detected on a CMOS image sensor (7) and fixing the oval cell sample in a sample clamping groove (4), and rotating a lamp light box (1) to enable an opening of the lamp light box and a shading plate to form a closed collection chamber;
step 3, turning on the LED light source (2) to enable light rays emitted by the LED light source (2) to be gathered by the convex lens (3) and vertically emitted to the elliptical cell sample (6) to be detected;
step 4, opening the CMOS image sensor (7), and exporting the acquired image data to a processing module of the CMOS image sensor circuit through a data interface;
step 5, detecting the center of a blood cell by using a Hough transformation algorithm on the derived image data, and dividing the image according to the center of the blood cell to detect a blood cell diffraction ring;
step 6, carrying out sub-pixel interpolation operation on the basis of the step 5 to obtain a sub-pixel image, and converting the sub-pixel image from a rectangular coordinate system to a polar coordinate system by taking the center coordinates obtained in the step 5 as the center;
step 7, determining a curve of the distance from the strongest light intensity point of the diffraction bright ring to the center of the cell diffraction ring through a super-resolution algorithm;
step 8, calculating a light intensity maximum point of the diffraction bright ring according to the distance curve in the step 6, and representing the position of the first diffraction bright ring;
step 9, increasing the polar coordinate system parameter theta from 0 degree to 360 degrees, increasing according to the set step length, and sequentially repeating the steps 7-8 until 360-degree radius data are obtained, and forming the 360-degree radius data into a radius sequence { x' pk1 (θ 1 )，x' pk2 (θ 2 )，…，x' pkn (θ n )}，x' pkn (θ n ) The radius value corresponding to the polar coordinate system parameter theta is represented, and n is a natural number which is not 0;
step 10, representing the diameter of the diffraction ring by the sum of two radiuses, and matching the radiuses to obtain the angle alpha of the diffraction ring 1 ,α 2 ,…,α i The diameter length at i is a natural number other than 0:
in the formula (10), D 1 (α 1 ),D 2 (α 2 ),…,D i (α i ) Is the diffraction ring at angle alpha 1 ,α 2 ,…,α i Diameter length at the location;
define set a to represent these data:
A＝{D 1 (α 1 ),D 2 (α 2 )，…，D i (α i )} (11)；
step 11, carrying out matching identification of elliptic cells, wherein the shadow length of the elliptic long axis position is expressed as:
D maj (α maj )＝min(A) (12)
let pi/4 < alpha maj < 3pi/4, definition set B is expressed as
B＝{D 1 (β 1 ),D 2 (β 2 )，…，D i (β i )} (13)
The length of the shadow at the location of the minor axis of the ellipse can be expressed as:
D min (α min )＝min(B)
the definition parameter M represents the difference between the major and minor axes of elliptic cells:
M＝|D maj (α maj )-D min (α min )|
defining a threshold M T If M > M T Then a normal oval cell is judged, otherwise other cells.
2. The method for detecting elliptic cells according to claim 1, wherein the step 7 is specifically to obtain a mapping relationship between the light intensity and the length of a diffraction occurrence point, i.e. the edge of the cell, according to the light intensity information carried by the image data, where the relationship indicates that a plurality of peaks occur in a two-dimensional coordinate system, each peak represents a diffraction bright ring, and the maximum point of the peak represents the position of the diffraction bright ring;
the first diffraction bright ring is the first diffraction bright ring: the radial super-resolution is to find the fastest rising point and the fastest falling point of the peak corresponding to the first diffraction bright ring, and correct the position of the peak maximum value point by the intersection point of the slopes of the two points; the circumferential super-resolution is subjected to noise reduction through Gaussian smoothing, and further the characterization position of the corrected first diffraction bright ring is obtained; and calculating the distance from the first diffraction light ring to the cell diffraction ring through the characterization position of the first diffraction light ring, and obtaining a curve of the distance from the strongest light intensity point of the first diffraction light ring to the center of the cell diffraction ring.
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