CN105181649B - A kind of Novel free marking mode identifies cell instrument method - Google Patents
A kind of Novel free marking mode identifies cell instrument method Download PDFInfo
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- CN105181649B CN105181649B CN201510649334.6A CN201510649334A CN105181649B CN 105181649 B CN105181649 B CN 105181649B CN 201510649334 A CN201510649334 A CN 201510649334A CN 105181649 B CN105181649 B CN 105181649B
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Abstract
The invention discloses a kind of Novel free marking mode to identify cell instrument method, including：Prepare label-free cell solution to be measured and import in microchannel or be made cell suspension chip；Conduction laser excitation cell to be measured distributes in the scattering light of three dimensions, and scattering light is detected by two-dimentional cmos detector by optical imaging system or without any optical imaging system and obtains two-dimentional light scattering pattern corresponding to cell to be measured；The two-dimentional light scattering pattern of acquisition is transmitted to pattern recognition classifier system, and study belongs to the two-dimentional light scattering pattern of different types of known cell to system automatically, and realizes label-free, automatic identification to unknown cell.Recognition result triggers related device, realizes label-free, automation cell count or cell classification function.Fluorescent staining of the present invention without carrying out complexity to cell, it can automate, identification, counting, classification of the label-free realization to cell to be measured, it is simple and efficient to handle, analysis cost is significantly reduced, is had wide range of applications.
Description
Technical field
The present invention relates to cell classification identification, the light scattering pattern that cell is obtained in particular with label-free cell instrument is believed
Breath, pattern-recognition then is carried out to light scattering pattern, realize label-free, automatic cytological counting or classification feature.
Background technology
Conventional flow cytometer can be used for the analysis and sorting of cell.It is, in general, that conventional flow cytometer need to be to cell
Dyeing processing is carried out, and fluorescent staining or other biomarker may produce certain influence to cell, particularly in work
In terms of body cell functional study.Secondly, light path needed for fluorescence measurement is complicated, and this directly increases instrument cost, and fluorescence is surveyed
Amount needs to calibrate instrument, and complex operation is, it is necessary to professional.Finally, in terms of later stage signal transacting, because fluorescence is sent out
Penetrate between spectrum and there may be overlapped, it is necessary to carry out the operation such as complementary color, and existing streaming cell instrument is thin in the later stage
In terms of born of the same parents' Classification and Identification, corresponding cell subsets can only be identified according to predetermined physics, chemical feature parameter ranges, lacked automatic
Machine learning and carry out the function of Classification and Identification, particularly in terms of label-free, automatic cytological Classification and Identification.
Clinically the examination of cervical carcinoma is mainly by means of cervical cytological examination and HPV immune detections.It is thin for uterine neck
For born of the same parents learn inspection, the cervical cell to come off is gathered from cervical tissue first, is dyed, film-making, then by clinical pathology
Teacher of the studying medicine carries out artificial diagosis under the microscope.Experienced doctor can accurately differentiate uterine neck normally and cancerous tumor cell,
It there may come a time when to need to carry out HPV detections and Biopsy under Colposcopy to make a definite diagnosis.Cervical cytological examination process steps are complicated, take
It is long, and artificial diagosis needs doctor to have abundant clinical experience, and diagosis result has stronger subjectivity.HPV detect and
Biopsy under Colposcopy accuracy rate is high but more difficult popularization.
The content of the invention
The invention discloses a kind of Novel free marking mode to identify cell instrument method, gathers obtaining label-free cell or cell
On the basis of the two-dimentional light scattering pattern of cluster, pattern-recognition is carried out to scattering pattern, reaches label-free, automatic cytological counts
With the purpose of Classification and Identification.In terms of sample process, overcome conventional flow cytometer needs to carry out fluorescent staining this method
Shortcoming, realize label-free sample process；It is high that conventional flow cytometer light path complexity, cost are overcome on light path system
Shortcoming；In terms of signal transacting, innovative employs pattern-recognition to be scattered the automatic Classification and Identification of pattern.Above skill
The organic integration of art realizes the innovation on cell sorting method.In terms of using effect, the innovative approach is gathered available for cell
The quick identification of number of clusters, label-free identification also is realized to normal cervical cell and the uterine neck HeLa cells of canceration.
A kind of Novel free marking mode identifies cell instrument method, and concrete scheme comprises the following steps：
Make label-free cell solution to be measured and import in microchannel or be made cell suspension chip；
The light that LASER Light Source is sent is coupled into optical fiber by four times of object lens, fiber optic conduction laser and excite microchannel or
Unicellular or many cells gathering groups in cell suspension, distribute in the scattering light of three dimensions；
Scattering light passes through optical imaging system, is detected by two-dimentional cmos detector and obtains two-dimentional light corresponding to cell to be measured
Scattering pattern；
Or scattering light needs not move through optical imaging system, is detected by two-dimentional cmos detector and obtains cell pair to be measured
The two-dimentional light scattering pattern answered；
The two-dimentional light scattering pattern of acquisition is transmitted to PRS, and the system passes through to known different cell categories
Two-dimentional light scattering pattern carries out machine learning, realizes unmarked, the automatic identification to unknown cell；
Recognition result is used to trigger label-free pattern-recognition cell instrument automatic cytological counting or cellular classification system.
Further, device corresponding to two-dimentional light scattering pattern acquisition includes：Light-source system, swash for producing LASER Light Source
Send out the scattering light of tested cell；Two-dimentional light scattering pattern detects record system, and record collects the scattering light of tested cell；Pattern is known
Other system, automatic Classification and Identification is carried out by data processing and machine learning；Cell count or cellular classification system, including numeral
Counter and mechanical sorter.
Further, scattering light passes through optical imaging system, when obtaining two-dimentional light scattering pattern corresponding to cell to be measured, needs
Move adjustment three-D displacement platform and find laser convergent point, LASER Light Source is entered after four times of object lens with Best Coupling state
Enter in optical fiber, the other end of optical fiber is used to excite the unicellular or cell aggregation in microchannel or cell suspension as probe
Group.
Further, the cell in microchannel in solution to be measured scatters light caused by laser excitation, by optics into
As system or without optical imaging system；
During by optical imaging system, cell to be measured produces scattering by laser excitation in microchannel or cell suspension
Light, the scattering light are observed by ten times of object lens, adjust ten times of object lens, it was observed that the object lens are defocused by the original image of cell,
Scattering optical pattern is obtained on COMS two-dimensional detectors.
Without optical imaging system, that is, any optical imaging lens are not needed, scattering light passes through a physical pore size, directly
Two-dimentional light scattering pattern is formed in CMOS planes.
Further, algorithm for pattern recognition is using enhancing AdaBoost algorithms, to the N number of two-dimentional light scattering diagram detected
Sample, the pattern for selecting N-1 known classification are trained, and the Weak Classifier of one group of pattern-recognition are obtained, then with this weak point
The combination of class device is tested original n-th pattern, is selected most strong Weak Classifier by loop test and is combined, and is finally given pair
The high-accuracy of cell classification identification to be measured.
Further, the above method is used for the classification of yeast cells cluster group.
Further, the above method is used for the classification of normal cervix cell and canceration cervical cell.
Beneficial effects of the present invention：
(1) Novel free marking mode identification cell instrument apparatus proposed by the present invention is easy, overcomes conventional flow cytometer
The shortcomings of light path is complicated, equipment is expensive, cumbersome, easy it can quickly obtain two-dimentional light scattering pattern.
(2) the unmarked technology that the present invention uses, overcoming conventional flow cytometer needs to carry out fluorescent staining to cell,
The problem of so as to cause cell sample to damage, fluorescent staining can be avoided to be done to caused by cell particularly living cells function
Disturb.
(3) Novel free marking mode proposed by the present invention identification cell instrument can realize to cell or cell mass it is label-free,
Mechanized classification identifies, i.e., reaches the Classification and Identification to cell to be measured by the algorithm for pattern recognition of automation.
(4) Novel free marking mode identification cell instrument generalization ability proposed by the present invention is strong, can be widely used for different cells
Classification and Identification.
(5) analysis process of the present invention is workable, can choose the Weak Classifier composition strong classifier of appropriate number, to the greatest extent
Possible raising recognition accuracy.After obtaining strong classification, operating personnel need to only input the automatically acquisition point of detection image can
Class recognition result.
(6) label-free, automatic mode identification cell art proposed by the invention, counted available for corresponding physics is excited
Device or sorter, realize counting to cell, sorting function.
(7) the invention provides a kind of determination methods of new progress cell mass quantity differentiation.
(8) the invention provides the judgement side of a kind of new carry out normal cervix cell and the HeLa cell classifications of canceration
Method.
Brief description of the drawings
Fig. 1 is the structure and schematic diagram of apparatus of the present invention,
The single yeast cells simulation drawings of Fig. 2 (a)-Fig. 2 (d) and experiment scatter diagram contrast；
Fig. 3 (a)-Fig. 3 (d) varying number yeast cells gathering groups artwork, scatter diagram contrast；
Fig. 4 (a)-Fig. 4 (d) normal cervix cell and HeLa cells artwork, scatter diagram contrast；
In Fig. 1：1st, LASER Light Source, 2, four times of object lens, 3, fiber coupler, 4, microchannel or cell suspension chip, 5,
Ten times of object lens or physical pore size, 6, two-dimentional cmos detector, 7, PRS, 8 categorizing systems；
The varying number yeast cells gathering groups classification results of table 1；
The normal cervix cell of table 2 and HeLa cell classification results.
Embodiment：
The present invention is described in detail below in conjunction with the accompanying drawings：
As shown in figure 1, a kind of Novel free marking mode identification cell instrument is mainly visited by light-source system, two-dimentional light scattering pattern
Survey record system, data processing categorizing system is formed.Wherein light-source system includes LASER Light Source 1, four times of object lens 2, fiber coupling
Device 3, microchannel or cell suspension chip 4；Two-dimentional light scattering pattern detection record system includes ten times of object lens or physical pore size
5, two-dimentional cmos detector 6；Data processing categorizing system component analysis system includes PRS 7, categorizing system 8.
The two-dimentional light scattering pattern detecting system of the present invention includes unicellular and cell aggregation group light scattering activating system,
Micro-fluidic or cell suspension chip system, and two-dimentional light scattering pattern obtain system.The data processing categorizing system of the present invention
The later data processing of two-dimentional light scattering pattern is carried out using algorithm for pattern recognition, is realized to unicellular and cell mass
Label-free, mechanized classification identification.Exemplified by AdaBoost machine learning algorithms in identification in mode of the invention, but it is not limited to
The identification of cell light scattering pattern is carried out using the specific mode identification method.The present invention is independent of traditional fluorescent staining
And manual sort, by the pattern-recognition to scattering pattern, realize to varying number yeast cells group and cervical cell
The label-free of different pathological status, mechanized classification identification.Application of the present invention extend to general biological cell physiology,
Pathological analysis.Novel free marking mode disclosed in this invention identifies cell instrument method, without carrying out complicated fluorescence to cell
Dyeing, can label-free, automation realize the counting in classification to cell to be measured, identification, and later stage, sorting etc., it is easy to operate
Fast, as a result accurately and reliably, analysis cost is significantly reduced, is had wide range of applications.
1 couple of present invention carries out the detailed description of concrete operation step below in conjunction with the accompanying drawings：
Step 1：Cell solution to be measured is prepared, the method that solution is prepared according to different cells to be measured is not quite similar.
Step 2：Cell solution to be measured is imported into microchannel 4 or cell suspension chip 4 is made.
Step 3：LASER Light Source 1 is opened, LASER Light Source 1 uses 532nm wave-length green laser diode-pumped solid laser
Device (DPSS).Diode pumping solid laser has longevity of service, efficiency high, power consumption is low, fuel factor is small, small volume etc. is aobvious
The advantage of work.In order to ensure that a diameter of 1.0mm laser beam can be coupled into 105 μm of diameter, numerical aperture to greatest extent
(NA) in 0.22 optical fiber, present invention selection numerical aperture for 0.1 four times of object lens 2 to improve coupling efficiency.
Step 4：Constantly mobile adjustment calibration laser couplers make LASER Light Source after four times of object lens 2, can be with optimal coupling
Conjunction state enters optical fiber one end in fiber coupler 3.The optical fiber other end of fiber coupler 3 is used to excite miniflow to lead to as probe
Road 4 or cell or cell mass in cell suspension chip 4.
Step 5：Cell to be measured produces scattering light in laser excitation microchannel 4 or cell suspension chip 4.Pass through first
Object lens are observed, and moving fiber goes to position cell, until cell to be measured is in the centre of laser beam and can excite completely lateral
Scatter light.
Step 6：Obtain the two-dimentional light scattering pattern of cell to be measured.Adjust ten times of object lens 5 so that the cytological map in the visual field
As most clear, what is at this time obtained is the original image of cell.The image of the invention to be obtained is not cell itself imaging,
But the two-dimensional scattering optical pattern of its formation.On the basis of focusing, object lens are adjusted according to identical direction and identical distance, i.e.,
Carry out " defocusing ", two-dimentional light scattering pattern will be at this time formed in the plane of COMS two-dimensional detectors 6.The COMS two dimensions of the present invention
Detector size is 22.3 × 14.9mm, and record pixel is about 17,900,000.There are integrated level height, work(using COMS two-dimensional detectors
Consume small, cost is low, the advantages that easily integration with other chips.Or cell scattering light is without any optical imaging system, i.e.,
Without any lens, also two-dimentional light scattering pattern can will be formed in the plane of cmos detector 6 by means of physical pore size 5.
Step 7：The two-dimentional light scattering pattern that the COMS two-dimensional detectors 6 of acquisition are collected is conveyed into PRS
7。
Step 8：The scattering pattern of acquisition is standardized, is unified into 220 × 220 pixels.Dissipating after standardization
Penetrate pattern use pattern recognizer and carry out Classification and Identification.
Step 9：In PRS 7, it can be calculated as the case may be using corresponding pattern-recognition to be divided
Class identifies.The present invention, to the N number of scattering pattern detected, uses leave-one-out side by taking AdaBoost algorithms as an example
Method, the pattern for selecting N-1 therein known classification are trained, then with the n-th pattern left to this Weak Classifier
Combination is debugged, so as to obtain one group of Weak Classifier combination.Then, by original N-1 training sample one of those with original
The n-th pattern change first left, so as to which training obtains one group of Weak Classifier again.Multilayer weak typing is obtained along these lines
Device, choose the multilayer Weak Classifier of respective numbers, by by the classification results complementation of Weak Classifier so as to effectively be combined, structure
Build a strong grader.The number of the multilayer Weak Classifier included of the strong classifier, can make it that classification results are optimal.
When training sample is enough, it can train to obtain final grader being packaged by single, so as to meet that Classification and Identification will
Ask.
Step 10：Learn cell two dimension light scattering pattern to be measured automatically by PRS, unknown cell is realized
Label-free, automatic identification.Recognition result triggers the corresponding device of categorizing system 8, realize label-free, automation cell count or
Cell classification function.
Embodiment 1
The suitable yeast soln of concentration has been configured, the two-dimentional light scattering diagram of yeast soln is obtained using the device of the present invention
Sample, experimental result and theoretical modeling result are subjected to contrast verification.Fig. 2 illustrates the two-dimensional scattering figure that single yeast cells is formed
The theoretical modeling result figure 2 (a) and Fig. 2 (b) of sample and experimental result Fig. 2 (c) and Fig. 2 (d) contrast.Yeast is unicellular micro- life
Thing, cell dia are about 3-6 μm, and the scatter diagram of experiment presents two kinds of different aspect graphs 2 (c) and Fig. 2 (d).In simulation
Yeast cells is assumed the spheric granules with different-diameter, refractive index 1.42, incident wavelength 532nm, surrounding medium folding
Penetrate rate and elect 3.8 μm as cell dia in 1.334, Fig. 2 (a), a diameter of 5.0 μm in (b).As can be observed from Figure, test
As a result with theoretical modeling result either striped quantity or fringe position all matches mutuallies, the standard of apparatus of the present invention can be verified
True property.
Embodiment 2
Using the device of the present invention, 60 corresponding gathering groups two dimension light are obtained from 60 groups of yeast cells gathering groups and are dissipated
Penetrate pattern.Wherein, have 30 groups be the aggregation of 3 yeast cells pattern, in addition 30 groups be 4 yeast cells aggregations pattern.Often
The size of individual scattering pattern is all 220 × 220 pixels, and passes through normalized, such as Fig. 3 (a)-Fig. 3 (d).
The present invention carries out leave-one-out experiments using AdaBoost methods.Specific implementation step is：To known to 59
The light scattering pattern of classification (3 yeast cells aggregations or 4 yeast cells aggregations) is trained, and obtains one group of pattern-recognition
Weak Classifier, then this Weak Classifier is tested with the 60th pattern.The correct number (CN) of test data is recorded, is led to
Cross formula AR=CN/TN and accuracy (AR) is calculated.TN represents the quantity of all two-dimentional light scattering patterns.As shown in table 1, grind
Discovery is studied carefully when the number of plies increase of Weak Classifier, and respective change occurs for AR.The present invention uses 3 layers of Weak Classifier, can obtain most
Big accuracy 86.7%.It is 93.3% wherein for 3 yeast cells gathering groups AR, 4 yeast cells gathering groups AR are
80%.
The yeast cells gathering groups classification results of table 1
Embodiment 3
Apparatus of the present invention are used for the Classification and Identification of normal cervix cell and canceration cervical cell (HeLa cells).For uterine neck
The Classification and Identification of cell, 92 two-dimentional light scattering diagrams are obtained altogether using the label-free pattern-recognition cell instrument method of the present invention
Sample, wherein 54 are normal cervix cell light scattering patterns, 38 are HeLa cell light scattering patterns, as a result such as Fig. 4 (a)-Fig. 4
(d) shown in.When carrying out pattern-recognition using AdaBoost methods, Weak Classifier is trained with 91 scattering patterns, the 92nd
For testing.As shown in table 2, research finds that the accuracy rate AR to classify when the Weak Classifier number of plies is 7 reaches maximum 90.2%,
The wherein accuracy AR of normal cervix cell is that the accuracy AR of 90.7%, HeLa cells is 89.5%.Normal cervix cell and
For the cervical cell of canceration under the observation of 400 power microscopes, their profiles are similar, but its internal structure has occurred that and changed
Become.The pattern of two-dimentional light scattering includes the information of cell interior change, point that label-free pattern-recognition cell instrument can automate
Class identifies the two classes cell.90.2% cervical cell Classification and Identification accuracy shows label-free pattern-recognition cell in the present invention
Instrument has good potential applicability in clinical practice.
The cervical cell classification results of table 2
The description that above-mentioned combination accompanying drawing is carried out to the embodiment of the present invention, not to the limit of the scope of the present invention
System, on the basis of technical scheme, those skilled in the art need not pay creative work can make it is each
Kind modification is deformed still within protection scope of the present invention.
Claims (8)
1. a kind of label-free pattern-recognition cell instrument method, it is characterized in that, comprise the following steps：
Make label-free cell solution to be measured and import in microchannel or be made cell suspension chip；
The light that LASER Light Source is sent is coupled into optical fiber by four times of object lens, and fiber optic conduction laser simultaneously excites microchannel or cell
Unicellular or many cells gathering groups in suspension, distribute in the scattering light of three dimensions；
Scattering light passes through optical imaging system, is detected by two-dimentional cmos detector and obtains two-dimentional light scattering corresponding to cell to be measured
Pattern；
Or scattering light needs not move through optical imaging system, is detected and is obtained corresponding to cell to be measured by two-dimentional cmos detector
Two-dimentional light scattering pattern；
The two-dimentional light scattering pattern of acquisition is transmitted to PRS, and the system passes through the two dimension to known different cell categories
Light scattering pattern carries out machine learning, realizes unmarked, the automatic identification to unknown cell；
Recognition result is used to trigger label-free pattern-recognition cell instrument automatic cytological counting or cellular classification system.
2. a kind of label-free pattern-recognition cell instrument method as claimed in claim 1, it is characterized in that, two-dimentional light scattering pattern obtains
Device corresponding to taking includes：Light-source system, the scattering light of tested cell is excited for producing LASER Light Source；Two-dimentional light scattering pattern
Record system is detected, record collects the scattering light of tested cell；PRS, carried out by data processing and machine learning
Automatic Classification and Identification；Cell count or cellular classification system, including digit counter and mechanical sorter.
3. a kind of label-free pattern-recognition cell instrument method as claimed in claim 1, it is characterized in that, scattering light by optics into
As system, it is necessary to which mobile adjustment three-D displacement platform finds laser convergence when obtaining two-dimentional light scattering pattern corresponding to cell to be measured
Point, LASER Light Source is set to enter after four times of object lens with Best Coupling state in optical fiber, the other end of optical fiber is used as probe
In exciting the unicellular or cell aggregation group in microchannel or cell suspension.
4. a kind of label-free pattern-recognition cell instrument method as claimed in claim 1, it is characterized in that, microchannel or cell hang
Cell to be measured produces scattering light by laser excitation in liquid, and the scattering light is observed by ten times of object lens, adjusts ten times of object lens, observation
To the original image of cell, the object lens are defocused, scattering optical pattern is obtained on COMS two-dimensional detectors.
5. a kind of label-free pattern-recognition cell instrument method as claimed in claim 1, it is characterized in that, it is to be measured molten in microchannel
Cell in liquid scatters light caused by laser excitation, without optical imaging system, that is, does not need any optical imaging lens,
Scattering light passes through a physical pore size, and two-dimentional light scattering pattern is directly formed in CMOS planes.
6. a kind of label-free pattern-recognition cell instrument method as claimed in claim 1, it is characterized in that, algorithm for pattern recognition uses
Strengthen AdaBoost algorithms, to N number of unicellular or cell aggregation group the two-dimentional light scattering pattern detected, select N-1
The pattern of known classification is trained, and the Weak Classifier of one group of pattern-recognition is obtained, then with the n-th pattern pair originally left
This Weak Classifier is tested, and a strong classifier for including a number of Weak Classifier is obtained by testing.
7. a kind of label-free pattern-recognition cell instrument method as claimed in claim 1, it is characterized in that, the above method is used for yeast
The classification of cell aggregation group.
8. a kind of label-free pattern-recognition cell instrument method as claimed in claim 1, it is characterized in that, the above method is used for normal
The classification of cervical cell and canceration cervical cell.
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| CN106520535B (en) * | 2016-10-12 | 2019-01-01 | 山东大学 | A kind of label-free cell detection device and method based on mating plate illumination |
| CN111751263A (en) * | 2020-06-08 | 2020-10-09 | 西安交通大学 | Mark-free cell two-dimensional scattering image inversion method based on gray level co-occurrence matrix |
| CN111751266A (en) * | 2020-07-10 | 2020-10-09 | 西安交通大学 | Mark-free cell nucleus scattering inversion method based on multi-scale gray level co-occurrence matrix |
| CN113155713B (en) * | 2021-05-28 | 2023-05-05 | 山东大学 | Label-free high-content video flow cytometer and method based on transfer learning |
| CN114418995B (en) * | 2022-01-19 | 2023-02-03 | 生态环境部长江流域生态环境监督管理局生态环境监测与科学研究中心 | Cascade algae cell statistical method based on microscope image |
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