CN109870401B - Flow cytometer and super-resolution cell image acquisition method - Google Patents

Flow cytometer and super-resolution cell image acquisition method Download PDF

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CN109870401B
CN109870401B CN201910151369.5A CN201910151369A CN109870401B CN 109870401 B CN109870401 B CN 109870401B CN 201910151369 A CN201910151369 A CN 201910151369A CN 109870401 B CN109870401 B CN 109870401B
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余宁梅
田典
方元
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Xian University of Technology
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Abstract

The invention discloses a flow cytometer, which mainly combines the characteristics of parallel light, cell flow in a micro-channel in a micro-fluidic chip and scanning imaging of a double-linear array detector, and can obtain cell images with higher resolution and clearer details on the basis of an area array detector and a single-linear array detector, so that the cell flow counting, classification, identification and the like are more accurate. The invention also discloses a method for acquiring the super-resolution cell image, which is characterized in that the flow cytometer of the invention is used for acquisition, the cell flow rate can be calculated according to the frame interval number of cells flowing through two linear array detectors and the frame frequency of the double linear array detectors, so that two cell super-resolution images with time difference can be recovered according to the cell flow rate, and meanwhile, the two cell super-resolution images with time difference are used for enhancing the image details to obtain the super-resolution cell image, thereby solving the problem that the cell flow rate influences the image recovery effect.

Description

Flow cytometer and super-resolution cell image acquisition method
Technical Field
The invention belongs to the technical field of cell detection devices, relates to a flow cytometer, and further relates to a super-resolution cell image acquisition method.
Background
Cell detection plays an important role in medical research and in the detection of many diseases. At present, the cell detection instrument is large in size and expensive, and is only suitable for being carried out in medical institutions. The microfluidic technology can integrate basic operations of sample preparation, separation, reaction, detection and the like on a chip. The microfluidic chip is convenient to use, has the characteristics of high analysis speed, portability, low power consumption and automation, and is suitable for being used in the fields, communities and other scenes.
The combination of microfluidic technology and image processing technology makes it possible to miniaturize, cost-effectively operate, and to make cell detection systems popular. Although the traditional problems can be solved by the existing flow cytometer based on the microfluidic technology and the area array detector, the imaging effect is poor, the resolution ratio is low, and the flow cytometer is easily influenced by the quality of a light source and a micro-channel, so that the later cell analysis and treatment difficulty is high. Compared with the prior flow cytometer based on the single-line array image sensor, the prior flow cytometer based on the single-line array image sensor can better obtain high-quality images, but does not solve the problem of imaging blurring, and requires that cells of a micro-channel in a micro-fluidic chip move at a relatively uniform speed, so that the realization difficulty is extremely high.
Disclosure of Invention
The invention aims to provide a flow cytometer, which solves the problem that cell flow velocity influences cell image recovery imaging blurring.
The invention also aims to provide a super-resolution cell image acquisition method.
The invention adopts a first technical scheme that the flow cytometer comprises a micro-fluidic chip, wherein two linear array detectors which are parallel to each other are arranged below the micro-fluidic chip, the lower surface of the micro-fluidic chip is attached to the upper surface of the linear array detectors, and the two linear array detectors are both connected with a data processing device;
the micro-fluidic chip is characterized by further comprising a parallel light source arranged right above the micro-fluidic chip, wherein the parallel light source irradiates the micro-fluidic chip to form a parallel light area, a linear micro-channel a is arranged inside the micro-fluidic chip, one end of the micro-channel a is provided with a sample inlet, the other end of the micro-channel a is provided with a sample outlet, an included angle is formed between the micro-channel a and the linear array detector, and the included angle theta meets the following relation: theta is more than or equal to 0 degree and less than or equal to 90 degrees, the two sides of the micro-channel a are respectively provided with a micro-channel b, one end of the micro-channel b is provided with a buffer solution inlet, and the other end of the micro-channel b is communicated with the micro-channel a near the sample inlet.
The first technical solution of the present invention is also characterized in that,
the data processing device is an upper computer PC.
The data processing device comprises a data transmission module and a data processing module which are connected together.
An ASIC chip is arranged in the data processing module.
And an FPGA chip is arranged in the data processing module.
An angle dial is sleeved on the periphery of the microfluidic chip.
The second technical scheme adopted by the invention is a super-resolution cell image acquisition method, which is used for acquiring by applying the flow cytometer of the first technical scheme of the invention and specifically comprises the following steps:
step 1, introducing a sample into a sample inlet, and introducing a buffer solution into the sample inletBuffer solution is introduced into the port, the sample and the buffer solution are intersected in the microchannel a to form laminar flow and flow to the sample outlet, and the two linear array detectors collect cell images of the same cells of the sample with time difference and respectively obtain Rp1And Rp2；
Step 2, establishing a planar rectangular coordinate system by taking the linear array direction of the linear array detector as an x axis and taking the direction vertical to the linear array detector as a y axis, decomposing the flow speed of the cells along the x axis and the y axis, calculating the distance d' of the two linear array detectors in the cell flow direction according to the front-back distance d of the two linear array detectors in the y axis direction and the included angle theta between the microchannel a and the linear array detectors as follows,
d'＝d/sinθ (11)，
according to the distance s of the two linear array detectors in the cell flowing direction, the flowing speed v of the cell is calculated as follows,
v＝d'·n/f (12)，
in the formula (12), n is the frame interval number of the cells passing through the two linear array detectors, f is the frame frequency of each linear array detector, since n can only be a natural number which is not 0 and has a certain error, when the error is accumulated to 1 frame, the error is corrected, the frame interval number is corrected, n' is n + gamma, wherein gamma is a correction factor, gamma is more than or equal to 0 and less than 1,
decomposing the flow velocity of the cells along the x-axis and the y-axis respectively to obtain the decomposition velocity v of the x-axisxAnd the decomposition velocity v of the y-axisyAs follows below, the following description will be given,
vx＝v·cosθ (13)
vy＝v·sinθ (14)，
decomposition velocity v of x-axisxThe transverse speed of the cell on the cell image collected by the linear array detector, the transverse displacement s of the cell between cell image frames collected by the linear array detector is,
s＝vx/f (15)。
step 3, calculating the corrected transverse displacement s' of the cell between the cell image frames collected by the linear array detector according to the transverse displacement s, and respectively enabling the cell image Rp1And Rp2Each frame of image in the image processing system is subjected to reverse displacement and longitudinal splicing to finally obtain a cell recovery image R'p1、R'p2；
Step 4, restoring images R 'of cells respectively through interpolation amplification algorithm'p1And R'p2Zooming to recover cell super-resolution image R'p1And R "p2；
Step 5, carrying out super-resolution image R on the cells "p1And R "p2And processing by a high-contrast retention algorithm or a multi-frame super-resolution algorithm, improving the image resolution and enhancing the image details again to finally obtain a super-resolution cell image, and finishing the acquisition of the super-resolution cell image.
The second technical solution of the present invention is also characterized in that,
step 2, step 3, step 4 and step 5 are all implemented by the data processing device (3).
Step 3 is to specifically collect the cell image R of the linear array detectorp1I frame picture PiMoving s & i +1 frames along the negative direction of the x axis, wherein i is 1, 2, 3 and … n, n is a natural number which is not 0, and obtaining the ith frame of preliminary recovery image
Figure BDA0001981634910000041
q 11, 2, 3, … n, n is a natural number different from 0 when
Figure BDA0001981634910000042
And
Figure BDA0001981634910000043
when the sum of the pixel differences of the corresponding positions is minimum, let q1When the error caused by gamma is accumulated to 1 frame, the correction factor gamma of the interval number of the correction frames of the linear array detector is 1/q1If the interval number of the correction frames of the linear array detector is n' ═ n +1/q1The corrected flow velocity v 'of the cell is calculated from the number n' of corrected frame intervals as follows,
v'＝d·n'/f (16)，
decomposing the corrected flow velocity of the cell along the x-axis and the y-axis respectively to obtain a corrected decomposition velocity v of the x-axisxModified decomposition velocity v of' and y-axisy' in the following manner,
vx'＝v'·cosθ (17)
vy'＝v'·sinθ (18)，
cell image R acquired by linear array detectorp1The corrected lateral shift s' between frames is,
s'＝vx'/f (19). The ith frame image PiMoving s 'i frames along the negative direction of the x axis to obtain the ith frame final recovery image R'piPi is 1, 2, 3, … n, n is a natural number other than 0, and i frames are finally restored to an image R'piSplicing is carried out to obtain a cell recovery image R'p1Analogously according to the cell image Rp2Obtaining cell recovery image R'p2。
Step 4, specifically, according to the number n' of the corrected frame intervals of the linear array detector and the cell image R collected by the linear array detectorp1The resolution of (2) is H.times.W, and H and W are respectively expressed, and a cell recovery image R 'is calculated'p1The resolution of (a) is H '× W', H '═ H, W ═ n' W, and the image R 'is restored to the cell by interpolation and enlargement algorithm'p1Zooming to recover cell super-resolution image R'p1Similarly, image R 'was recovered from the cells'p2Zooming to recover cell super-resolution image R'p2。
The invention has the beneficial effects that: the flow cytometer of the invention adopts the parallel light source, so that the diffraction of the cell is very small during imaging; the double-linear-array detector is used for independently and simultaneously acquiring data, the double-linear-array detector is inclined at a certain angle with the micro-channel, the flow velocity of each cell is convenient to calculate, the super-resolution image of each cell is acquired according to the flow velocity of each cell, and the cells are counted at the same time, so that the omission of the cells can be effectively avoided. According to the method for acquiring the super-resolution cell image, two images with time difference are recovered by using the cell image acquired by the double-linear-array detector, the image details can be further recovered, and the finally obtained super-resolution cell image is higher in resolution, clearer in details and easier to process compared with images acquired by other flow cytometers, and can realize cell tracking, cell segmentation, multi-cell counting, multi-cell classification and the like.
Drawings
FIG. 1 is a schematic diagram of the structure of a flow cytometer of the present invention;
FIG. 2 is a schematic diagram of a microfluidic chip and a parallel light source in a flow cytometer according to the present invention;
FIG. 3 is a schematic structural diagram of a microfluidic chip and a linear array detector in a flow cytometer according to the present invention;
FIG. 4 is a schematic view of a sampling pattern of an in-line array detector of a flow cytometer of the present invention;
FIG. 5 is a schematic diagram illustrating the cell velocity decomposition principle in the super-resolution cell image acquisition method according to the present invention;
FIG. 6 is an original cell image during simulation and verification of a super-resolution cell image acquisition method according to the present invention;
FIG. 7 is an image collected by a conventional area array detector during simulation and verification of a method for collecting super-resolution cell images according to the present invention;
FIG. 8 is a cell image of a sample collected by a linear array detector in a flow cytometer of the present invention during simulation and verification of a method for collecting super-resolution cell images of the present invention;
FIG. 9 is a cell image of a sample collected by another linear array detector in the flow cytometer of the present invention during simulation and verification of the method for collecting super-resolution cell images of the present invention;
FIG. 10 is a cell recovery image of the simulated single line array detector to FIG. 8 according to a cell flow rate during simulation and verification of a super-resolution cell image acquisition method of the present invention;
FIG. 11 is a cell recovery image of the simulated single line array detector to FIG. 8 according to another cell flow rate during simulation and verification of the super-resolution cell image acquisition method of the present invention;
FIG. 12 is a super-resolution cell image during simulation and verification of a super-resolution cell image acquisition method according to the present invention;
FIG. 13 is a super-resolution image of a cell of a simulated single line array detector during a simulation verification process of the acquisition method of a super-resolution cell image of the present invention.
In the figure, 1 is a microfluidic chip, 2 is a linear array detector, 3 is a data processing device, 4 is a microchannel a, 5 is a parallel light source, 6 is a microchannel b, 7 is a sample inlet, 8 is a buffer solution inlet, 9 is a sample outlet, and 10 is an angle dial.
Detailed Description
The present invention will be described in detail below with reference to the accompanying drawings and specific embodiments.
The invention relates to a flow cytometer, as shown in figure 1, which comprises a microfluidic chip 1, wherein two linear array detectors 2 which are parallel to each other are arranged below the microfluidic chip 1, the lower surface of the microfluidic chip 1 is attached to the upper surfaces of the linear array detectors 2, and the two linear array detectors 2 are both connected with a data processing device 3; the data processing device 3 has two structures: in the first structure, the data processing device 3 is an upper computer PC provided with a data interface; in a second configuration, the data processing apparatus 3 includes a data transmission module and a data processing module connected together
The data processing module has three structures, which are respectively as follows:
in the first structure, an ASIC chip is arranged in a data processing module;
in the second structure, an embedded system is arranged in the data processing module;
in the third structure, an FPGA chip is arranged in the data processing module.
The invention discloses a flow cytometer, as shown in fig. 2, further comprising a parallel light source 5 with constant light intensity arranged right above a microfluidic chip 1, wherein the parallel light source 5 irradiates on the microfluidic chip 1 to form a parallel light area, as shown in fig. 3, a linear micro-channel a4 is arranged inside the microfluidic chip 1, one end of a micro-channel a4 is provided with a sample inlet 7, the other end of a micro-channel a4 is provided with a sample outlet 9, an included angle is formed between the micro-channel a4 and a linear array detector 2, and the included angle theta satisfies the following relation: theta is more than or equal to 0 degree and less than or equal to 90 degrees, both sides of the microchannel a4 are provided with a microchannel b6, one end of the microchannel b6 is provided with a buffer solution inlet 8, the other end of the microchannel b6 is communicated with the microchannel a4 at a position close to the sample inlet 7, and the periphery of the microfluidic chip 1 is sleeved with an angle dial 10.
The invention relates to a method for acquiring a super-resolution cell image, which is used for acquiring by a flow cytometer and specifically comprises the following steps:
step 1, introducing a sample into a sample inlet 7, introducing a buffer solution into a buffer solution inlet 8, enabling the sample and the buffer solution to be intersected in a microchannel a4 to form laminar flow and flow towards a sample outlet 9, and acquiring cell images of the same cells of the sample with time difference by two linear array detectors, wherein the cell images are respectively Rp1And Rp2。
Step 2, as shown in fig. 4, a planar rectangular coordinate system is established with the linear array direction of the linear array detector 2 as the x-axis and the direction perpendicular to the linear array detector 2 as the y-axis, the flow velocity of the cells can be decomposed along the x-axis and the y-axis, and the distance d' of the two linear array detectors 2 in the cell flow direction is calculated as follows according to the front-back distance d of the two linear array detectors 2 in the y-axis direction and the included angle theta between the microchannel a and the linear array detectors 2,
d'＝d/sinθ (11)，
according to the distance s of the two linear array detectors 2 in the cell flowing direction, the flowing speed v of the cell is calculated as follows,
v＝d'·n/f (12)，
in the formula (12), n is the frame interval number of the cells passing through the two linear array detectors, f is the frame frequency of each linear array detector, and since n is only a natural number which is not 0, and has a certain error, when the error is accumulated to 1 frame, the cell image recovery is affected, so that the cell image needs to be corrected, the frame interval number is n' ═ n + γ, wherein γ is a correction factor, and γ is not less than 0 and is less than 1.
Decomposing the flow velocity of the cells along the x-axis and the y-axis respectively to obtain the decomposition velocity v of the x-axisxAnd the decomposition velocity v of the y-axisyAs follows below, the following description will be given,
vx＝v·cosθ (13)
vy＝v·sinθ (14)，
decomposition velocity v of x-axisxIs the transverse speed of the cell on the cell image acquired by the linear array detector 2, the transverse displacement s of the cell between cell image frames acquired by the linear array detector 2 is,
s＝vx/f (15)。
step 3, according to the transverse displacement sCalculating the corrected transverse displacement s' of the cell between the cell image frames collected by the linear array detector 2, and respectively enabling the cell image Rp1And Rp2Each frame of image in the image processing system is subjected to reverse displacement and longitudinal splicing to finally obtain a cell recovery image R'p1、R'p2；
Step 3 is to specifically acquire the cell image R by the linear array detector 2p1I frame picture PiMoving s & i +1 frames along the negative direction of the x axis, wherein i is 1, 2, 3 and … n, n is a natural number which is not 0, and obtaining the ith frame of preliminary recovery image
Figure BDA0001981634910000081
q 11, 2, 3, … n, n is a natural number different from 0 when
Figure BDA0001981634910000082
And
Figure BDA0001981634910000083
when the sum of the pixel differences at the corresponding positions is minimum, i.e. when the frame interval number error is accumulated to 1 frame, let q1When the error caused by gamma is accumulated to 1 frame, the correction factor gamma of the interval number of the correction frames of the linear array detector is 1/q1If the number of the correction frame intervals of the linear array detector 2 is n' ═ n +1/q1The corrected flow velocity v 'of the cell is calculated from the number n' of corrected frame intervals as follows,
v'＝d·n'/f (16)，
decomposing the corrected flow velocity of the cell along the x-axis and the y-axis respectively to obtain a corrected decomposition velocity v of the x-axisxModified decomposition velocity v of' and y-axisy' in the following manner,
vx'＝v'·cosθ (17)
vy'＝v'·sinθ (18)，
then the cell image R collected by the linear array detector 2p1The corrected lateral shift s' between frames is,
s'＝vx'/f (19). The ith frame image PiMoving s 'i frames along the negative direction of the x axis to obtain the ith frame final recovery image R'pi，pi＝1、23, … n, n is a natural number other than 0, i frames are finally restored to an image R'piSplicing is carried out to obtain a cell recovery image R'p1Analogously according to the cell image Rp2Obtaining cell recovery image R'p2。
Step 4, restoring images R 'of cells respectively through interpolation amplification algorithm'p1And R'p2Zooming to recover cell super-resolution image R'p1And R "p2；
Step 4 is specifically that the correction frame interval number n' of the linear array detector 2 and the cell image R collected by the linear array detector 2 are used for correcting the cell imagep1The resolution of (2) is H.times.W, and H and W are respectively expressed, and a cell recovery image R 'is calculated'p1The resolution of (a) is H '× W', H '═ H, W ═ n' W, and the image R 'is restored to the cell by interpolation and enlargement algorithm'p1Zooming to recover cell super-resolution image R'p1Similarly, image R 'was recovered from the cells'p2Zooming to recover cell super-resolution image R'p2。
Step 5, carrying out super-resolution image R on the cells "p1And R "p2And processing by a high-contrast retention algorithm or a multi-frame super-resolution algorithm, improving the image resolution and enhancing the image details again to finally obtain a super-resolution cell image, and finishing the acquisition of the super-resolution cell image.
Step 2, step 3, step 4 and step 5 are all implemented by the data processing device (3).
The two mutually parallel linear array detectors 2 have the following functions: collecting a cell flow image a in a microchannel 4 on the microfluidic chip 1, and eliminating the influence of background impurities on a detection result; the accurate speed of the cells in a short time can be calculated conveniently, and the influence of unstable cell flow speed on the image splicing and synthesizing precision is eliminated; and enhancing image details by using the cell images with time difference acquired by the two linear array detectors 2.
Simulation verification
Setting the included angle theta between the micro-channel 4 and the double-linear array detector to be 45 degrees, simulating the flow cytometer of the invention, and collecting cell images, wherein FIG. 6 is an original cell image, and cells flow in the micro-channel a4 at a non-uniform speedRespectively using a conventional area array detector and two parallel linear array detectors 2 to acquire images, wherein the cell image shown in fig. 7 is an image acquired by the conventional area array detector, and fig. 8 and 9 are cell images R acquired by the two linear array detectors respectively, wherein the same cells in the sample have time differencep1And Rp2；
In the step of recovering the cell flow rate in the microchannel a4 by using the analog simulation single-line array detector to obtain the cell flow rates in fig. 10 and 11, respectively, the cell images in fig. 10 and 11 have great difference, so that the cell flow rate in the microchannel a4 has great influence on the imaging effect;
the method for acquiring the super-resolution cell image performs operation simulation, the instantaneous speed of each cell is calculated according to the distance and the frame frequency of two parallel linear array detectors 2 in the whole process, and then the super-resolution cell image is recovered, wherein the cell super-resolution image of one linear array detector 2 is shown in figure 12, and the super-resolution cell image of the two parallel linear array detectors 2 is shown in figure 13. Comparing fig. 12 and fig. 13, it can be seen that the quality of the super-resolution image can be further improved by two parallel line detectors 2 using the slight difference of the super-resolution image caused by the time difference, and the influence of different and unstable cell flow rates on the recovery effect can be eliminated.

Claims (4)

1. The method for acquiring the super-resolution cell image is characterized in that a flow cytometer is used for acquiring, the flow cytometer comprises a micro-fluidic chip (1), an angle dial (10) is sleeved on the periphery of the micro-fluidic chip (1), two linear array detectors (2) which are parallel to each other are arranged below the micro-fluidic chip (1), the lower surface of the micro-fluidic chip (1) is attached to the upper surface of the linear array detectors (2), the two linear array detectors (2) are both connected with a data processing device (3), the data processing device (3) comprises a data transmission module and a data processing module which are connected together, the data processing device (3) is an upper computer PC, an ASIC chip is arranged in the data processing module, and an FPGA chip is arranged in the data processing module; the micro-fluidic chip is characterized by further comprising a parallel light source (5) arranged right above the micro-fluidic chip (1), wherein the parallel light source (5) irradiates the micro-fluidic chip (1) to form a parallel light area, a linear micro-channel a (4) is arranged inside the micro-fluidic chip (1), one end of the micro-channel a (4) is provided with a sample inlet (7), the other end of the micro-channel a (4) is provided with a sample outlet (9), an included angle is formed between the micro-channel a (4) and the linear array detector (2), and the included angle theta meets the following relation: theta is more than or equal to 0 degree and less than or equal to 90 degrees, the two sides of the micro-channel a (4) are respectively provided with a micro-channel b (6), one end of the micro-channel b (6) is provided with a buffer solution inlet (8), and the other end of the micro-channel b (6) is communicated with the micro-channel a (4) at a position close to the sample inlet (7), and the method specifically comprises the following steps:
step 1, introducing a sample into a sample inlet (7), introducing a buffer solution into a buffer solution inlet (8), enabling the sample and the buffer solution to be intersected in a micro-channel a (4) to form laminar flow and flow towards a sample outlet (9), and collecting cell images of the same cells of the sample with time difference by two linear array detectors (2), wherein the cell images are respectively Rp1And Rp2；
Step 2, establishing a plane rectangular coordinate system by taking the linear array direction of the linear array detector (2) as an x axis and the direction vertical to the linear array detector (2) as a y axis, decomposing the flow velocity of cells along the x axis and the y axis, and calculating the distance d' of the two linear array detectors (2) in the cell flow direction according to the front-back distance d of the two linear array detectors (2) in the y axis direction and the included angle theta between the microchannel a and the linear array detectors (2) as follows,
d'＝d/sinθ (11)，
according to the distance s of the two linear array detectors (2) in the cell flow direction, the flow velocity v of the cell is calculated as follows,
v＝d'·f/n (12)，
in the formula (12), n is the frame interval number of the cells passing through the two linear array detectors (2), f is the frame frequency of each linear array detector (2), since n can only be a natural number which is not 0 and has a certain error, when the error is accumulated to 1 frame, the error is corrected, the corrected frame interval number is n' ═ n + gamma, wherein gamma is a correction factor, gamma is more than or equal to 0 and less than 1,
the flow velocity of the cells is along the x-axis anddecomposing the y axis to obtain the decomposition speed v of the x axisxAnd the decomposition velocity v of the y-axisyAs follows below, the following description will be given,
vx＝v·cosθ (13)
vy＝v·sinθ (14)，
decomposition velocity v of x-axisxThe transverse speed of the cells on the cell image acquired by the linear array detector (2) is shown, the transverse displacement s of the cells between cell image frames acquired by the linear array detector (2) is shown as,
s＝vx/f (15)；
step 3, calculating the corrected transverse displacement s' of the cell between the cell image frames collected by the linear array detector (2) according to the transverse displacement s, and respectively enabling the cell images Rp1And Rp2Each frame of image in the image processing system is subjected to reverse displacement and longitudinal splicing to finally obtain a cell recovery image R'p1、R'p2；
Step 4, restoring images R 'of cells respectively through interpolation amplification algorithm'p1And R'p2Zooming to recover cell super-resolution image R'p1And R "p2；
Step 5, carrying out super-resolution image R on the cells "p1And R "p2And processing by a high-contrast retention algorithm or a multi-frame super-resolution algorithm, improving the image resolution and enhancing the image details again to finally obtain a super-resolution cell image, and finishing the acquisition of the super-resolution cell image.
2. The method for acquiring super-resolution cell images according to claim 1, wherein the steps 2, 3, 4 and 5 are all performed by a data processing device (3).
3. The method for acquiring super-resolution cell images according to claim 1, wherein the step 3 is to acquire the cell image R acquired by the linear array detector (2)p1I frame picture PiMoving s & i +1 frames along the negative x-axis, where i is 1, 2,3.… n, n is a natural number different from 0, and the ith frame preliminary recovery image R is obtainedq1，q11, 2, 3, … n, n is a natural number different from 0, when R isq1-1And Rq1When the sum of the pixel differences of the corresponding positions is minimum, let q1When the error caused by gamma is accumulated to 1 frame, the correction factor gamma of the interval number of the correction frames of the linear array detector is 1/q1If the interval number of the correction frames of the linear array detector (2) is n ═ n +1/q1The corrected flow velocity v 'of the cell is calculated from the number n' of corrected frame intervals as follows,
v'＝d'·f/n' (16)，
decomposing the corrected flow velocity of the cell along the x-axis and the y-axis respectively to obtain a corrected decomposition velocity v of the x-axisxModified decomposition velocity v of' and y-axisy' in the following manner,
vx'＝v'·cosθ (17)
vy'＝v'·sinθ (18)，
then the cell image R collected by the linear array detector (2)p1The corrected lateral shift s' between frames is,
s'＝vx'/f (19)，
the ith frame image PiMoving s 'i frames along the negative direction of the x axis to obtain the ith frame final recovery image R'piPi is 1, 2, 3, … n, n is a natural number other than 0, and i frames are finally restored to an image R'piSplicing is carried out to obtain a cell recovery image R'p1Analogously according to the cell image Rp2Obtaining cell recovery image R'p2。
4. The method for acquiring super-resolution cell images according to claim 3, wherein the step 4 is specifically based on the number of the corrected frame intervals n' of the linear array detector (2) and the cell image R acquired by the linear array detector (2)p1The resolution sizes H.times.W, H and W respectively representing the height and width of the cell recovery image R'p1The resolution of (a) is H ' × W ', H ' ═ H, W ' ═ n ' W, and the image R ' is restored to the cell by interpolation and enlargement algorithm 'p1Zooming to recover cell super-resolution image R'p1Similarly, it is fineCell recovery image R'p2Zooming to recover cell super-resolution image R'p2。
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