CN106644902A - Evaluation method of stability of laminar flow of flow cytometer - Google Patents
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- 238000011156 evaluation Methods 0.000 title claims abstract description 8
- 238000000034 method Methods 0.000 claims abstract description 33
- 238000007621 cluster analysis Methods 0.000 claims abstract description 14
- 206010019133 Hangover Diseases 0.000 claims description 9
- 238000004458 analytical method Methods 0.000 claims description 6
- 230000008859 change Effects 0.000 claims description 4
- 239000007788 liquid Substances 0.000 abstract description 6
- 239000004005 microsphere Substances 0.000 abstract description 5
- 230000008569 process Effects 0.000 description 8
- 238000001514 detection method Methods 0.000 description 6
- 238000005070 sampling Methods 0.000 description 5
- 230000015572 biosynthetic process Effects 0.000 description 4
- 230000007423 decrease Effects 0.000 description 4
- 239000002245 particle Substances 0.000 description 4
- 230000000750 progressive effect Effects 0.000 description 4
- 230000000630 rising effect Effects 0.000 description 4
- 238000000917 particle-image velocimetry Methods 0.000 description 3
- 230000008878 coupling Effects 0.000 description 2
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- 238000005859 coupling reaction Methods 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
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- 239000000725 suspension Substances 0.000 description 1
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- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N15/00—Investigating characteristics of particles; Investigating permeability, pore-volume or surface-area of porous materials
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Abstract
The invention provides an evaluation method of stability of a laminar flow of a flow cytometer. The evaluation method comprises the following steps of (1) detecting 90-degree Mie scattered light of microspheres in a flowing chamber by utilizing a high-speed microscopic image acquisition system; (2) performing cluster analysis on situations that the length of the light intensity/smear is insufficient, normal, diffracted, overlapped and the like of the acquired massive images by utilizing a grey cluster analyzing method, and obtaining a standard normal smear; (3) determining the boundary of the smear by utilizing a mid-point method, and calculating the corresponding flow velocity of the microspheres; (4) characterizing the stability of a liquid path system of the flow cytometer by utilizing the stability of the flow velocity of the microspheres.
Description
Technical field
The statistical analysis field the present invention relates to microballoon tests the speed, and in particular to the flow chamber inner laminar flow stability of flow cytometer
Evaluation areas.
Background technology
Flow cytometer is a kind of unicellular or other particles to being in high speed, streamlined flow in suspension, by detection
Scattered light signal and (or) fluorescence signal, realize at a high speed the clinical inspection analytic instrument of multi-parameter quantitative analysis one by one.Wherein, liquid
The main purpose of road system is to make the sample liquid comprising sample (cell or microballoon) under the parcel of sheath fluid, is formed stable
Laminar flow, so as to reach the purpose for obtaining unicellular stream.The stability of liquid-way system will directly affect cell/microballoon by flow chamber
The location and time of detection zone, and then affect the signal strength signal intensity and light pulses duration of corresponding scattered light and fluorescence signal.
Liquid-way system stability is estimated, especially cell/microballoon is entered by speed stability during flow chamber detection zone
Row assessment, it is possible to achieve the quick anticipation to whole stability of instrument.
At present, the decision method of flow cytometer liquid-way system stability mainly has pressure application and pulse signal signature analysis
Method.Pressure application referred to and is observed by the sample hydraulic coupling and sheath hydraulic coupling to most critical in liquid-way system, and for not
Same detection rates require that both amplitudes of variation just can determine that within limits liquid-way system is stablized.But, pressure application is
Gas pressure to acting on sample liquid and sheath fluid is detected, rather than directly flow rate of liquid is detected, so cannot
Weigh the impact of follow-up sampling structure and pipeline to laminar flow and cell/microballoon speed.Pulse signal method for feature analysis is referred to and passed through
The scattered light and fluorescence signal that data acquisition module is produced when the flow chamber detection zone to cell detect, using obtaining
Pulse width stability characterizing the stability of cell speed.The method needs the scattered light for completing cell/microballoon to excite,
The sequence of operations such as collection, opto-electronic conversion, pulse process and parameter extraction, are related to light path system, electronic circuit processing system,
So as to increased the uncertain factor of measurement process, it is impossible to truly reflect cell/microballoon in the indoor mobility status of flowing.
High-precision flow field characteristic analysis method is mainly particle image velocimetry method (Particl image
Velocimetry, PIV), its tachometric survey depends on the trace particle being dispersed in flow field, by measuring trace particle
The instantaneous velocity for knowing the displacement in very short time interval to measure flow field indirectly is distributed, and can provide abundant flow field space knot
Structure and flow behavior.However, PIV technologies are used for liquid flow field analyzes used Microsphere Size and flow cytomery sample
This adjoining dimensions, so as to many trace particles cannot be utilized to be analyzed the flow behavior of the indoor laminar flow of flowing and unicellular stream.
The content of the invention
In order to solve the above problems, it is an object of the invention to provide a kind of flow cytometer laminar flow stability assessment side
Method, the method comprising the steps of：1) the 90 ° of Mie scatterings using high speed micro image collection system to the indoor microballoon of flowing
Light is detected；2) using grey clustering analysis method it is not enough to light intensity in the great amount of images that collects/trailing length, normal,
Situations such as diffraction and overlap, carries out cluster analysis, obtains the normal streak image of standard, implements step as follows：It is provided with n
Object of observation, m evaluation index, s different grey classes, then each object of observation have m characteristic to need to observe, sequence can be obtained
Row are as shown in formula (1)：
X1=(x1(1),x1(2),…,x1(n))
X2=(x2(1),x2(2),…,x2(n))
……
Xm=(xm(1),xm(2),…,xm(n)) (1)
It is determined that grey class 1,2 ..., the central point λ of s1,λ2,...,λs, the span of each index is also correspondingly divided
For s grey class；Grey class is carried out into continuation to different directions, it is considered to increase by 0 grey class and s+1 ash classes, and determine its central point λ0With
λs+1, so as to obtain new center point sequence：λ0,λ1,λ2,...,λs,λs+1, tie point (λk, 1) and in the little grey class of kth -1
Heart point (λk-1, 0), tie point (λl, 1) with the central point (λ of l+1 little grey classl+1, 0), obtain ladder of the j indexs with regard to k ash classes
Shape whitened weight functionFor observation x of index j, can be by
Calculate its belong to grey class k (k=1,2 ... degree of membership s)Calculate object i (i=1,2 ..., n) with regard to
The synthetic clustering coefficient of grey class k
Wherein,For j index k subclass whitened weight functions, ηjFor weight of index j in comprehensively cluster,
ByJudge that object i belongs to grey class k*；
3) determine hangover border using mid-point method, and calculate corresponding microballoon flow velocity；4) using the stability of microballoon flow velocity
Characterize the stability of flow cytometer liquid-way system.
Preferably, the step 2) in carry out the index of cluster analysis and determine as follows：
, normal, diffraction not enough to light intensity in image/trailing length and overlap in this four classes image per a line pixel respectively
Gray value summation, obtain horizontal gray scale summation curve；First derivative is solved to horizontal gray scale summation curve；Set positive negative sense threshold
Value, and the extreme point number in threshold range is counted, index of effective extreme point number as cluster analysis；
, normal, diffraction not enough to light intensity in image/trailing length and overlap each row pixel in this four classes image respectively
Gray value summation, obtain longitudinal gray scale summation curve；First derivative is solved to longitudinal gray scale summation curve；Set positive negative sense threshold
It is worth, and the number of times to curve through positive negative threshold value is counted, can be used as the finger of cluster analysis with the intersection point number of positive negative threshold value
Mark.
Preferably, the step 3) in microballoon flow velocity tried to achieve by formula v=l/t, wherein l be microballoon trailing length, t is phase
The machine time for exposure.
Preferably, the step 4) also include by formulaStandard deviation is calculated, using trailing length
Mean value is characterized to microballoon speed, and the standard deviation using trailing length is estimated to the stability of microballoon speed.
It should be appreciated that aforementioned description substantially and follow-up description in detail are exemplary illustration and explanation, should not
As the restriction to claimed content of the invention.
Description of the drawings
With reference to the accompanying drawing enclosed, the present invention more purpose, function and advantages are by by the as follows of embodiment of the present invention
Description is illustrated, wherein：
Fig. 1 is high-speed image sampling microballoon measuring principle figure；
Fig. 2 is microballoon streak image；
Fig. 3 is horizontal gray scale summation curve：The normal ash classes of Fig. 3 (a)；Fig. 3 (b) curtailments ash class；Fig. 3 (c) overlaps ash
Class；
Fig. 4 is horizontal gray scale summation derivative curve：The normal ash classes of Fig. 4 (a)；Fig. 4 (b) curtailments ash class；Fig. 4 (c) weights
Folded ash class；
Fig. 5 longitudinal directions gray scale summation curve：The normal ash classes of Fig. 5 (a)；Fig. 5 (b) curtailments ash class；Fig. 5 (c) overlaps grey class；
Fig. 6 is longitudinal gray scale summation derivative curve：The normal ash classes of Fig. 6 (a)；Fig. 6 (b) curtailments ash class；Fig. 6 (c) weights
Folded ash class；
Fig. 7 is column element gray value rising edge curve map；
Fig. 8 is column element gray value trailing edge curve map.
Specific embodiment
By reference to one exemplary embodiment, the purpose of the present invention and function and the side for realizing these purposes and function
Method will be illustrated.However, the present invention is not limited to one exemplary embodiment disclosed below；Can by multi-form come
It is realized.The essence of specification is only to aid in the detail of the various equivalent modifications Integrated Understanding present invention.
Hereinafter, embodiments of the invention will be described with reference to the drawings.In the accompanying drawings, identical reference represents identical
Or similar part, or same or like step.
The invention provides a kind of method of the flow chamber inner laminar flow stability assessment of flow cytometer, the method is using high
Fast micro image collection system is detected to 90 ° of Mie scattered lights of the indoor microballoon of flowing, and utilizes grey clustering analysis method
, normal, diffraction not enough to light intensity in the great amount of images that collects/trailing length and cluster analysis is carried out situations such as overlap, obtain
The normal streak image of standard.Then, determine hangover border using mid-point method, and calculate corresponding microballoon flow velocity.Finally, utilize
The stability of microballoon flow velocity characterizes the stability of flow cytometer liquid-way system.
The present invention chooses 90 ° of side scattered lights can avoid the direct light of excitation source from disturbing as object of observation, and
The background light source of traditional micro image collection is removed, so as to reduce the contrast that background optical information improves image simultaneously.Work as microballoon
When flow chamber laser excitation region, the streak image of microballoon can be adopted by changing the time for exposure of high speed camera
Collection, and then obtain the flow velocity of microballoon.High-speed image sampling microballoon speed-measuring method schematic diagram such as Fig. 1 institutes based on 90 ° of Mie scatterings
Show.
Because flow cytometer can be detected each second to tens thousand of cells, while the exposure moment of high speed camera is micro-
Ball has randomness in the indoor position of flowing, so the microballoon streak image for collecting generally comprises blank, normal, length not
4 kinds of situations of foot and overlap, as shown in Figure 2.
The present invention is classified using the clustering method based on trapezoidal whitened weight function to microballoon streak image, its tool
Body realizes that step is as follows：
It is provided with n object of observation, m evaluation index, s different grey class.Then each object of observation has m characteristic
Observation is needed, can be obtained shown in sequence such as formula (1)：
X1=(x1(1),x1(2),…,x1(n))
X2=(x2(1),x2(2),…,x2(n))
… …
Xm=(xm(1),xm(2),…,xm(n)) (1)
It is determined that grey class 1,2 ..., the central point λ of s1,λ2,...,λs, the span of each index is also correspondingly divided
For s grey class.Grey class is carried out into continuation to different directions, it is considered to increase by 0 grey class and s+1 ash classes, and determine its central point λ0With
λs+1, so as to obtain new center point sequence：λ0,λ1,λ2,...,λs,λs+1, tie point (λk, 1) and in the little grey class of kth -1
Heart point (λk-1, 0), tie point (λl, 1) with the central point (λ of l+1 little grey classl+1, 0), obtain ladder of the j indexs with regard to k ash classes
Shape whitened weight functionFor observation x of index j, can be by
Calculate its belong to grey class k (k=1,2 ... degree of membership s)Calculating object i (i=1,2 ..., n) with regard to ash
The synthetic clustering coefficient of class k
Wherein,For j index k subclass whitened weight functions, ηjFor weight of index j in comprehensively cluster.
ByJudge that object i belongs to grey class k*.
From the laser diode that wavelength is 605nm, power is 80mW to exciting light in one embodiment of the present of invention；It is micro-
Object lens are the SPAHL-50 of Japanese Sigma Koki companies, and numerical aperture is 0.42, enlargement ratio 50, operating distance 20.5mm；
Image capturing system uses the Q450 high-speed image acquisition systems of Dantec companies, and supporting high-speed cmos camera is Vision
The V310 of research companies, ultimate resolution 1280 × 800, maximum speed be 500,000 fps, minimum aperture time 1us, it is single
The physical dimension of pixel is 20 μm of 20 μ m；Detection sample uses the standard Quality Control microballoon of Beckman Coulter companies
Flow-Check Pro Fluoro-spheres A69183, microsphere diameter is 20 ± 1 μm.Time for exposure is set to 40 μm, profit
Loading operation is performed with flow cytometer.Proceed by IMAQ after laminar condition is stable, sampling frame per second be set to 3300 frames/
S, sampling picture sum is set to 12000.
Respectively to the gray value summation in 4 class images per a line pixel, horizontal gray scale summation curve such as Fig. 3 institutes are obtained
Show.Gray value threshold value is set as 35, carrying out statistics using up number to threshold value can be used as the index of cluster analysis.Not enough ash class
Due to longitudinally there is gray value progressive formation, rising edge is slowly varying in its horizontal gray scale summation curve；Normal ash class without
Longitudinal gray scale progressive formation, therefore rising edge and trailing edge change are very fast；Grey class is overlapped in longitudinal direction without progressive formation, but is existed a plurality of
The phenomenon that hangover is overlapped, therefore its rising edge is all higher than 1 with trailing edge number.First derivative is solved to curve in Fig. 3, such as Fig. 4 institutes
Show.Positive threshold is set as 55, negative sense threshold value is -50, and the extreme point number in threshold range is counted.Work as extreme value
When the amplitude of point is more than 55 or less than -55, counted as effective extreme point.Effective extreme point that is not enough, normal, overlapping
Number is respectively 1,2,4.Effectively extreme point number can be used as the index of cluster analysis.
If the trailing length wretched insufficiency or gray value of not enough ash class are not enough, effective extreme point number is likely to result in for 0；
Overlapping grey class has various possibilities, and overlaps hangover quantity, lap position, overlap mode of grey class etc. and do not know, and overlaps ash
Effective extreme point number of class may be greater than 2 other integers.
In the same manner, respectively longitudinal gray scale summation curve is obtained as schemed to the gray value summation of each row pixel in 4 class images
Shown in 5.Gray value threshold value is set as 200, carrying out statistics using above-listed number to threshold value can be used as the index of cluster analysis.It is not enough
Due to longitudinally there is gray value progressive formation in grey class, the peak value of its longitudinal gray scale summation is less；Overlap grey class complete in longitudinal direction
The probability of overlap is relatively low, therefore columns of the gray value not for 0 is more than normal condition.First derivative is solved to curve in Fig. 5, is such as schemed
Shown in 6.Positive threshold is set as 150, negative sense threshold value is -250, and the number of times to curve through positive negative threshold value is counted.Just
Often the streak image intensity profile of ash class is relatively uniform, therefore its longitudinal gray scale summation first derivative curve has dull increase and decrease special
Property, there is no shake in positive and negative Near Threshold, it is 4 with the intersection point of positive negative threshold value.Streak image ash that is not enough and overlapping grey class
There is gradual change or saltus step in degree distribution, exist in positive and negative Near Threshold and shake, and old friend's points are not less than 4.With the intersection point of positive negative threshold value
Number can be used as the index of cluster analysis.
Microballoon speed is tried to achieve by formula v=l/t, and wherein l is microballoon trailing length, and t is the camera exposure time.In order to ensure
Accurate evaluation to liquid-way system stability, needs to be analyzed the raising and lowering process of the gray value that trails, reasonable selection
Hangover border, reduces the calculation error of microballoon trailing length.
Ranks summation, and the 5 row pictures of symmetrical selection centered on gray value summation maximum are entered to the gray value of normal picture
Vegetarian refreshments.The 5 row pixel gray value uphill process chosen are as shown in Figure 7.From figure 7 it can be seen that 5 column element is in the 303rd row
Gray value before only has fine jitter, and basic held stationary.Arrange to the 309th from the 304th row, gray value rapid increase, and
Linear change.In the same manner, the decline process of 5 row pixel gray values is as shown in Figure 8.The 5 row pixel gray values chosen are the
Basic held stationary before 420 row, from the 421st row to the 428th row gray value rapid decrease, and linearly changes.
Based on the characteristic that each row pixel gray value fast linear changes, the present invention is entered from mid-point method to the border trailed
Row determines.Mid-point method refers to the immediate pixel of mean value for choosing gray value and edge variation process as hangover border.
By taking Fig. 7,8 as an example, the average gray of the row pixel of uphill process 5 is the 36.5,36.5,34,33.1 and 35 and the 307th row pixel
The gray value (38,37,35,34 and 35) of point is closest, therefore using the 307th row as the start boundary point for trailing；Decline process 5 is arranged
The average gray of pixel be the 33.2,31.7,31.2,31.4 and 27.4 and the 307th row pixel gray value (32,30,
30th, 31 and 27) closest, thus using the 424th row as hangover start boundary point.
Determine the hangover border of normal picture using mid-point method, the mean value for calculating pixel number shared by trailing length is
116.9, by formulaCalculate standard deviation sigma=1.7.Due to the indoor microballoon speed of flowing cannot be obtained
True value, thus can utilize trailing length mean value microballoon speed is characterized, and using trailing length standard deviation to microballoon
The stability of speed is estimated, and then completes the assessment of flow cytometer laminar flow stability.
With reference to the explanation of the invention and practice that disclose here, the other embodiment of the present invention is for those skilled in the art
All will be readily apparent and understand.Illustrate and embodiment be to be considered only as it is exemplary, the present invention true scope and purport it is equal
It is defined in the claims.
Claims (4)
1. a kind of flow cytometer laminar flow stability appraisal procedure, the method comprising the steps of：
1) 90 ° of Mie scattered lights of the indoor microballoon of flowing are detected using high speed micro image collection system；
2) using grey clustering analysis method is not enough to light intensity in the great amount of images that collects/trailing length, normal, diffraction and weight
Folded situations such as, carries out cluster analysis, obtains the normal streak image of standard, implements step as follows：
Be provided with n object of observation, m evaluation index, s different grey class, then each object of observation have m characteristic needs
Observation, can obtain shown in sequence such as formula (1)：
X1=(x1(1),x1(2),…,x1(n))
X2=(x2(1),x2(2),…,x2(n))
……
Xm=(xm(1),xm(2),…,xm(n)) (1)
It is determined that grey class 1,2 ..., the central point λ of s1,λ2,...,λs, the span of each index is also correspondingly divided into s
Grey class；Grey class is carried out into continuation to different directions, it is considered to increase by 0 grey class and s+1 ash classes, and determine its central point λ0And λs+1, from
And obtain new center point sequence：λ0,λ1,λ2,...,λs,λs+1, tie point (λk, 1) with the central point of the little grey class of kth -1
(λk-1, 0), tie point (λl, 1) with the central point (λ of l+1 little grey classl+1, 0), j indexs are obtained with regard to the trapezoidal white of k ash classes
Change weight function(j=1,2 ..., m；K, l=1,2 ..., s), for observation x of index j, can be by
Calculate its belong to grey class k (k=1,2 ... degree of membership s)Calculating object i (i=1,2 ..., n) with regard to grey class k
Synthetic clustering coefficient
Wherein,For j index k subclass whitened weight functions, ηjFor weight of index j in comprehensively cluster,
ByJudge that object i belongs to grey class k*；
3) determine hangover border using mid-point method, and calculate corresponding microballoon flow velocity；
4) stability of flow cytometer liquid-way system is characterized using the stability of microballoon flow velocity.
2. method according to claim 1, wherein the step 2) in carry out the index of cluster analysis as follows
It is determined that：
, normal, diffraction not enough to light intensity in image/trailing length and overlap in this four classes image per the ash of a line pixel respectively
Angle value is sued for peace, and obtains horizontal gray scale summation curve；First derivative is solved to horizontal gray scale summation curve；Positive negative sense threshold value is set,
And the extreme point number in threshold range is counted, index of effective extreme point number as cluster analysis；
, normal, diffraction not enough to light intensity in image/trailing length and overlap the ash of each row pixel in this four classes image respectively
Angle value is sued for peace, and obtains longitudinal gray scale summation curve；First derivative is solved to longitudinal gray scale summation curve；Positive negative sense threshold value is set,
And the number of times to curve through positive negative threshold value is counted, can be used as the index of cluster analysis with the intersection point number of positive negative threshold value.
3. method according to claim 1, wherein the step 3) in microballoon flow velocity tried to achieve by formula v=l/t, whereinlFor
Microballoon trailing length, t is the camera exposure time.
4. method according to claim 1, wherein the step 4) also include by formulaCalculate mark
It is accurate poor, microballoon speed is characterized using the mean value of trailing length, and using trailing length standard deviation to microballoon speed
Stability be estimated.
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| CN107103604A (en) * | 2017-05-23 | 2017-08-29 | 重庆天之助生物科技有限公司 | A kind of particulate colourity auto-clustering analysis system |
| CN111936842A (en) * | 2018-03-30 | 2020-11-13 | 希森美康株式会社 | Flow cytometer and particle detection method |
| CN114441418A (en) * | 2022-01-28 | 2022-05-06 | 天津凌视科技有限公司 | Imaging system, imaging method and readable storage medium for high-speed flowing particles |
| CN116957992A (en) * | 2023-09-20 | 2023-10-27 | 南京木木西里科技有限公司 | Real-time microscopic image anti-shake method based on feature tracking |
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- 2016-11-01 CN CN201610934593.8A patent/CN106644902A/en active Pending
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107103604A (en) * | 2017-05-23 | 2017-08-29 | 重庆天之助生物科技有限公司 | A kind of particulate colourity auto-clustering analysis system |
| CN111936842A (en) * | 2018-03-30 | 2020-11-13 | 希森美康株式会社 | Flow cytometer and particle detection method |
| CN114441418A (en) * | 2022-01-28 | 2022-05-06 | 天津凌视科技有限公司 | Imaging system, imaging method and readable storage medium for high-speed flowing particles |
| CN116957992A (en) * | 2023-09-20 | 2023-10-27 | 南京木木西里科技有限公司 | Real-time microscopic image anti-shake method based on feature tracking |
| CN116957992B (en) * | 2023-09-20 | 2024-01-05 | 南京木木西里科技有限公司 | Real-time microscopic image anti-shake method based on feature tracking |
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Application publication date: 20170510 |
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