CN101492740A - Correct measurement method for nucleus DNA matter content in cell quantitative investigation - Google Patents
Correct measurement method for nucleus DNA matter content in cell quantitative investigation Download PDFInfo
- Publication number
- CN101492740A CN101492740A CNA2009100608459A CN200910060845A CN101492740A CN 101492740 A CN101492740 A CN 101492740A CN A2009100608459 A CNA2009100608459 A CN A2009100608459A CN 200910060845 A CN200910060845 A CN 200910060845A CN 101492740 A CN101492740 A CN 101492740A
- Authority
- CN
- China
- Prior art keywords
- value
- eiod
- nucleus
- correction coefficient
- nuclear
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Images
Landscapes
- Measuring Or Testing Involving Enzymes Or Micro-Organisms (AREA)
- Investigating Or Analysing Biological Materials (AREA)
Abstract
The invention provides a method for accurately measuring the content of karyon DNA substances in quantitative analysis of cells, including the following steps: expansion algorithm mathematical morphology is used for obtaining EIOD value; statistical method is used for obtaining EIOD standard value so that the IOD correction coefficient of a single karyon is calculated; the characteristic parameters and correction coefficient of karyon are used for training the regression model of the correction coefficient by SVR algorithm, and the model and the SVR algorithm are used for returning and reconstructing CIOD value of cells; the CIOD value of reference karyon is used for converting the content of DNA substances of each karyon. The method improves the accuracy and anti-interference of measuring the content of DNA substances; the conversion method of the content of DNA substances in the invention can obtain the content of DNA substances which can be easily understood and utilized, is the same as medical expression, and is conveniently applied to diagnosis or research.
Description
Technical field
The present invention relates to the accurate measuring method of nucleus DNA matter content in a kind of cell quantitative, belong to biomedical engineering field.
Background technology
The mensuration of nucleus DNA matter content is the core of cell quantitative, simultaneously also be the variation that utilizes quantitative cell analysis method diagnosis and examination early-stage cancer and research nucleus DNA matter content with the relation of various pathologies necessary before topic and most important foundation.The accuracy of dna material content measurement is directly connected to the accuracy and the stability of screening for cancer, also directly affects the verity of quantitative cytology result of study, has crucial meaning.
Generally, nucleus DNA matter content can't directly measure, but by measuring dyeing back nuclear integration optics density value (IOD value), thereby measures the optical absorption of dna material in the nucleus, the indirect interior dna material content of nucleus that obtains.
But because precision, the optical characteristics of equipment and the odjective causes such as complexity of set lights and situation of image capture device, utilize the IOD value to calculate dna material content and have bigger error, the interior dna material content of nucleus what can not reflect fully really.So the IOD value of pair cell nuclear is proofreaied and correct, obtaining accurately, dna material content becomes very important and necessary work.
Patent US 6,026,174 and US 7,274,908 in, utilize nuclear IOD value to calculate dna content, provided corresponding D NA cubage method, but do not provided corresponding bearing calibration.In actual application, the calculating of dna content is subjected to the influence of extraneous various objective factors easily, makes that the dna content value of calculating is inaccurate, thereby influences the accuracy of diagnosing tumor.
Summary of the invention
The object of the present invention is to provide the accurate measuring method of nucleus DNA matter content in a kind of cell quantitative, utilize the non-linear correction method of morphological image and support vector regression SVR that the dna content value is proofreaied and correct, can effectively eliminate the influence that extraneous factor is measured dna content, improve the accuracy and the objectivity of dna content value, thereby improve the accuracy of diagnosing tumor, for the variation of researching DNA content and the relation of various illnesss very significant meaning is arranged also simultaneously.
Technical scheme of the present invention is: the accurate measuring method of nucleus DNA matter content in the cell quantitative is characterized in that: comprise the following steps: a, utilize the expansion algorithm in the mathematical morphology, the mask figure of pair cell nuclear carries out dilation operation; And utilize mask figure and archeocyte nuclear image calculation after expanding to expand integration optical density (OD) EIOD value; B, the nuclear EIOD of G0/G1 phase in the sample is added up, obtain the EIOD standard value, and utilize the EIOD value of this EIOD sample value and nucleus self, calculate each nuclear correction coefficient; C, nuclear correction coefficient are as output, and the characteristic parameter vector by support vector regression SVR training program, obtains the regression model of nucleus correction coefficient about its characteristic parameter vector as input; D, characteristic parameter vector are as input, the nucleus correction coefficient about the regression model of its characteristic parameter vector as model, return the correction coefficient of reconstituted cell nuclear by the SVR training program, and utilize the EIOD value of this correction coefficient and nucleus itself, integration optical density (OD) CIOD value behind the calculation correction; The Normocellular nucleus CIOD value of e, statistics G0/G1 phase obtains the value with reference to CIOD, and utilizes the CIOD value of this value and nucleus self to calculate dna material content.
Principle of work of the present invention is: the present invention has following four key problem in technology points: utilize the expansion algorithm of mathematical morphology to ask for the EIOD value; Utilize statistical method to obtain the EIOD standard value, and calculate the IOD correction coefficient of individual cells nuclear thus; Utilize nuclear characteristic parameter and correction coefficient, by the SVR algorithm, training correction coefficient regression model, and utilize this model and SVR algorithm to return the CIOD value of reconstituted cell; Utilize with reference to nuclear CIOD value, each nuclear dna material content value converts.
The invention has the beneficial effects as follows: (1) has improved the accuracy of dna material content measurement.Because the method that the restriction of all odjective causes, tradition directly utilize measurement IOD value to obtain dna material content has bigger error.The present invention utilizes nuclear various optics, texture, morphological specificity that EIOD is proofreaied and correct, the reason that can effectively various errors be produced takes into account in the calculating, various errors are carried out nonlinear calibration, improved the accuracy of dna material content measurement greatly.(2) improved the freedom from jamming of dna material content measurement.Simply utilize the IOD value to obtain the method for dna material content, be subjected to the influence of image segmentation algorithm bigger.The foundation that the present invention utilizes nuclear EIOD value to replace the IOD value to carry out the dna material cubage, the EIOD value has effectively compensated the inaccurate measuring error that causes of image segmentation algorithm, has kept the simple feature of former algorithm simultaneously.(3) the present invention utilizes the SVR algorithm to carry out the recurrence and the estimation of correction coefficient, and utilizes nuclear various characteristic parameter.Contain the conditional information that various errors produce in the various characteristic parameters, utilize the SVR algorithm to carry out the estimation and the blind Detecting of correction coefficient, consider various linearities and nonlinearity erron simultaneously, obtain accurately objectively proofreading and correct.(4) conversion method of dna material content of the present invention can access the dna material content of easy to understand and utilization, and is consistent with expression medically, is convenient to apply to diagnosis or research.
Description of drawings
Fig. 1 is that embodiment of the invention nucleus EIOD value returns reconstruction model training process synoptic diagram.
Fig. 2 is that embodiment of the invention nucleus EIOD value returns the process of reconstruction synoptic diagram.
Embodiment
The present invention is described further below in conjunction with drawings and Examples.
The present invention will solve following problem:
(1) provides a method of accurately measuring dna material content in the nucleus, improve the accuracy of measuring nucleus DNA matter content, do interference etc.
(2) provide one the IOD value carried out gauged method, make IOD value after the correction can reflect what of dna material content in the nucleus more accurately.
(3) can provide a kind of accurate conversion method of nucleus DNA matter content, the dna material content value of coming out that converts can provide the comparability of different nucleus DNA matter contents in this sample inside.
The concrete enforcement of the embodiment of the invention is as follows: the content that mainly comprises three aspects: ask for expansion integration optical density (OD) (EIOD), proofread and correct integration optical density (OD) (CIOD) and converted dna substances content.
One, expansion integration optical density (OD) (EIOD) asks for
At first, the embodiment of the invention has designed an applied mathematics morphology algorithm and has asked for turgid cell mask figure, and asks for the method for expansion integration optical density (OD) (EIOD).
After using image segmentation algorithm pair cell nuclear to carry out cutting apart, can obtain the mask figure { Ω of individual cells nuclear
X, y, wherein x and y represent the coordinate figure of pixel, Ω
X, y=1 this pixel of expression belongs to this nucleus inside, Ω
X, y=0 this pixel of expression is outside this nucleus.
Utilize the expansion algorithm of mathematical morphology, figure expands to this mask, and mask figure { Ω obtains expanding
X, y +.Wherein, Ω
X, y +Be the expansion mask.Work as Ω
X, y=1 or pixel (x, the Ω of y) any one 8 neighborhood pixels (x ', y ')
X ', y '=1, then
Otherwise
Among the mask figure after overexpansion, nuclear size is in fact than an original big circle.
Utilize formula (1) can calculate expansion integration optical density (OD):
OD wherein
X, yThe optical density (OD) value of expression pixel, can utilize formula (2) to calculate:
OD
x，y＝-log(g
x，y/g
0) (2)
G wherein
X, yThe gray-scale value of representing this pixel, g
0The gray-scale value of expression background illumination.
This shows that compare with traditional IOD method of calculation, this method is also considered calculating with archeocyte extranuclear neighbour zone.If this zone includes nuclear dna material, then this part optical density (OD) also can be calculated into, if this subregion does not have dna material, then its optical density (OD) value is 0, can not influence the accuracy of calculation result.As seen, it can represent the content of dna material in the nucleus more accurately.This method has effectively been avoided having improved result's stability and accuracy owing to cut apart the inaccurate influence that brings to the calculating of integration optical density (OD).
Two, proofread and correct the calculating of integration optical density (OD) (CIOD)
Secondly, the embodiment of the invention has also designed a kind of method of utilizing the support vector regression algorithm EIOD to be carried out corrected reconstructed.
This method is divided into two parts, and training and recurrence are rebuild.Training is in systems development process, utilizes correction coefficient and nuclear various optics, form and the textural characteristics of standard, obtains regression model by the SVR training program; Returning process of reconstruction is in the application process of reality, the regression model that the utilization training obtains and various optics, form and the textural characteristics parameter of nucleus actual measurement, obtain correction coefficient by SVR recurrence program, and utilize the EIOD value of this correction coefficient and actual computation, finally calculate the integration optics density value CIOD after the correction.Training process such as Fig. 1 return process of reconstruction such as Fig. 2.
Training process
In training process, choose and be in the G0/G1 nucleus in the same sample, calculate their EIOD value.By the method for statistics, find out the EIOD value of standard, as gauged normalization method standard value.It can be the average of these nucleus EIOD value, also can be the mode of these nucleus EIOD value.The correction factor calculation method is:
γ
i＝EIOD
0/EIOD
i (3)
Wherein, EIOD
0Be EIOD standard value, EIOD
iBe this nuclear EIOD value.
Simultaneously, by nuclear gray-scale map and mask figure, can calculate numerous eigenwerts such as nuclear optics, form, texture, they can be represented with floating number.The characteristic parameter that calculates is many more, and regression result is accurate more.Here use f
iRepresent this nuclear feature value vector.
Utilize these correction coefficient and nucleus proper vector { (γ
i, f
i), by the support vector regression program, can obtain the regression model of correction coefficient.
Process of reconstruction
In process of reconstruction,, calculate its characteristic parameter vector f simultaneously for each cell
iWith the EIOD value EIOD before the correction
i, utilize the characteristic parameter vector f
iWith the correction coefficient regression model, can obtain correction coefficient γ
iFormula below utilizing, the nucleus EIOD value after can obtaining proofreading and correct.
CIOD
i＝γ
iEIOD
i (4)
Wherein, EIOD
iBe this nuclear EIOD value, CIOD
iBe the CIOD value after this nucleus correction.
EIOD value after overcorrection is what of reaction dna substances content more accurately, also have more comparability in same sample.
Three, the conversion of dna material content
At last, the embodiment of the invention has proposed to utilize the conversion method of proofreading and correct back CIOD value calculating dna material content.
For the dna material content after proofreading and correct, choose stable G0/G1 phase cell as contrasting, calculate their CIOD mode CIOD
ControlAs the conversion standard.By following formula, can obtain dna material content.
DC
i＝2CIOD
i/CIOD
control (5)
Dna material content after the conversion is identical with the dna material content that medical science is thought, unit is c.The dna material content of general G0/G1 phase cell is 2c.
The present invention utilizes features such as nuclear different optical, form, texture, by the support vector regression algorithm, obtains different nuclear correction coefficient, and each nuclear IOD value is proofreaied and correct.Because the aspects such as different illumination intensity, texture distribution and form size of cell have been considered in correction, make that the IOD value after proofreading and correct is unified more, accurate, and the interior dna material content of nucleus what can reflect more really.Simultaneously, in same sample, different nuclear dna material content have comparability, for diagnosis and research provide important evidence.
Claims (1)
1, the accurate measuring method of nucleus DNA matter content in the cell quantitative is characterized in that: comprise the following steps: a, utilize the expansion algorithm in the mathematical morphology, the mask figure of pair cell nuclear carries out dilation operation; And utilize mask figure and archeocyte nuclear image calculation after expanding to expand integration optical density (OD) EIOD value; B, the nuclear EIOD of G0/G1 phase in the sample is added up, obtain the EIOD standard value, and utilize the EIOD value of this EIOD sample value and nucleus self, calculate each nuclear correction coefficient; C, nuclear correction coefficient are as output, and the characteristic parameter vector by support vector regression SVR training program, obtains the regression model of nucleus correction coefficient about its characteristic parameter vector as input; D, characteristic parameter vector are as input, the nucleus correction coefficient about the regression model of its characteristic parameter vector as model, return the correction coefficient of reconstituted cell nuclear by the SVR training program, and utilize the EIOD value of this correction coefficient and nucleus itself, integration optical density (OD) CIOD value behind the calculation correction; The Normocellular nucleus CIOD value of e, statistics G0/G1 phase obtains the value with reference to CIOD, and utilizes the CIOD value of this value and nucleus self to calculate dna material content.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CNA2009100608459A CN101492740A (en) | 2009-02-24 | 2009-02-24 | Correct measurement method for nucleus DNA matter content in cell quantitative investigation |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CNA2009100608459A CN101492740A (en) | 2009-02-24 | 2009-02-24 | Correct measurement method for nucleus DNA matter content in cell quantitative investigation |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN101492740A true CN101492740A (en) | 2009-07-29 |
Family
ID=40923529
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CNA2009100608459A Pending CN101492740A (en) | 2009-02-24 | 2009-02-24 | Correct measurement method for nucleus DNA matter content in cell quantitative investigation |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN101492740A (en) |
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102622534A (en) * | 2012-04-11 | 2012-08-01 | 哈尔滨工程大学 | Correction method of deoxyribonucleic acid high-pass sequencing data for gene expression detection |
| CN104634735A (en) * | 2013-11-08 | 2015-05-20 | 麦克奥迪（厦门）医疗诊断系统有限公司 | Nonlinear correction method of cell DNA detection equipment |
| CN105255997A (en) * | 2012-04-10 | 2016-01-20 | 中国计量科学研究院 | Method for error correction in transgenic organism quantitative determination |
| CN106340016A (en) * | 2016-08-31 | 2017-01-18 | 湖南品信生物工程有限公司 | DNA quantitative analysis method based on cell microscope image |
| CN109540890A (en) * | 2018-11-27 | 2019-03-29 | 湖南品胜生物技术有限公司 | A kind of DNA quantitative analysis method based on microcytoscope image |
| CN110211108A (en) * | 2019-05-29 | 2019-09-06 | 武汉兰丁医学高科技有限公司 | A kind of novel abnormal cervical cells automatic identifying method based on Feulgen colouring method |
| CN112750493A (en) * | 2020-12-22 | 2021-05-04 | 深思考人工智能机器人科技（北京）有限公司 | DNA ploid quantitative analysis method and system based on Papanicolaou staining mode |
-
2009
- 2009-02-24 CN CNA2009100608459A patent/CN101492740A/en active Pending
Cited By (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105255997A (en) * | 2012-04-10 | 2016-01-20 | 中国计量科学研究院 | Method for error correction in transgenic organism quantitative determination |
| CN105255997B (en) * | 2012-04-10 | 2017-12-08 | 中国计量科学研究院 | A kind of genetically modified organism corrects deviation method in quantitatively detecting |
| CN102622534A (en) * | 2012-04-11 | 2012-08-01 | 哈尔滨工程大学 | Correction method of deoxyribonucleic acid high-pass sequencing data for gene expression detection |
| CN102622534B (en) * | 2012-04-11 | 2015-09-30 | 哈尔滨工程大学 | A kind of DNA high pass sequencing data bearing calibration detected for gene expression |
| CN104634735A (en) * | 2013-11-08 | 2015-05-20 | 麦克奥迪（厦门）医疗诊断系统有限公司 | Nonlinear correction method of cell DNA detection equipment |
| CN104634735B (en) * | 2013-11-08 | 2018-03-02 | 麦克奥迪（厦门）医疗诊断系统有限公司 | A kind of non-linear correction method of cell DNA detection device |
| CN106340016A (en) * | 2016-08-31 | 2017-01-18 | 湖南品信生物工程有限公司 | DNA quantitative analysis method based on cell microscope image |
| CN106340016B (en) * | 2016-08-31 | 2019-03-22 | 湖南品信生物工程有限公司 | A kind of DNA quantitative analysis method based on microcytoscope image |
| CN109540890A (en) * | 2018-11-27 | 2019-03-29 | 湖南品胜生物技术有限公司 | A kind of DNA quantitative analysis method based on microcytoscope image |
| CN110211108A (en) * | 2019-05-29 | 2019-09-06 | 武汉兰丁医学高科技有限公司 | A kind of novel abnormal cervical cells automatic identifying method based on Feulgen colouring method |
| CN112750493A (en) * | 2020-12-22 | 2021-05-04 | 深思考人工智能机器人科技（北京）有限公司 | DNA ploid quantitative analysis method and system based on Papanicolaou staining mode |
| CN112750493B (en) * | 2020-12-22 | 2024-05-03 | 深思考人工智能机器人科技（北京）有限公司 | DNA ploid quantitative analysis method and system based on Papanicolaou staining mode |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN101492740A (en) | Correct measurement method for nucleus DNA matter content in cell quantitative investigation | |
| Verhulp et al. | A three-dimensional digital image correlation technique for strain measurements in microstructures | |
| Bryhn et al. | An operational definition of a statistically meaningful trend | |
| CN105976411B (en) | A kind of preposition measurement module and Calibration Method for electrical impedance tomography data collecting system | |
| CN103983595A (en) | Water quality turbidity calculating method based on ultraviolet-visible spectroscopy treatment | |
| CN106483147B (en) | Long-time sequence passive microwave soil moisture precision improvement research method based on multi-source data | |
| Habert et al. | Reduction of the uncertainties in the water level-discharge relation of a 1D hydraulic model in the context of operational flood forecasting | |
| Rymarczyk et al. | Optimising the use of Machine learning algorithms in electrical tomography of building Walls: Pixel oriented ensemble approach | |
| CN103854305A (en) | Module transfer method based on multiscale modeling | |
| CN102034266A (en) | Rapid sparse reconstruction method and equipment for exciting tomography fluorescence imaging | |
| Scott et al. | Error and uncertainty in radiocarbon measurements | |
| CN105784672A (en) | Drug detector standardization method based on dual-tree complex wavelet algorithm | |
| Cheng et al. | Observation data compression for variational assimilation of dynamical systems | |
| Fancourt et al. | Error measurement in craniometrics: the comparative performance of four popular assessment methods using 2000 simulated cranial length datasets (g-op) | |
| CN102012466A (en) | Method for measuring noise of digital X-ray imaging system | |
| CN114391857A (en) | Dual-energy X-ray bone mineral density detection method based on mobile least square algorithm | |
| Strub et al. | Accelerating global parameter estimation of gravitational waves from Galactic binaries using a genetic algorithm and GPUs | |
| CN115952743B (en) | Multi-source precipitation data collaborative downscaling method and system coupled with random forest and HASM | |
| Sümegi et al. | Some notes on the interpretation and reliability of malacological proxies in paleotemperature reconstructions from loess-comments to Obreht et al.'s “A critical reevaluation of paleoclimate proxy records from loess in the Carpathian Basin” | |
| CN108195724A (en) | The measuring method and measuring device of grain composition content | |
| Sordoń et al. | Voltammetric determination of caffeic, syringic and vanillic acids taking into account uncertainties in both axes | |
| Errico et al. | Some general and fundamental requirements for designing observing system simulation experiments (OSSEs) | |
| Horny et al. | Age estimation based on a combined arteriosclerotic index | |
| Matheson et al. | Simultaneous multifactor Bayesian analysis (SiMBA) of PET time activity curve data | |
| Rachakonda et al. | Uncertainty evaluation by Monte Carlo method |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| C53 | Correction of patent for invention or patent application | ||
| CB03 | Change of inventor or designer information |
Inventor after: Xu Duanquan Inventor after: Sun Xiaorong Inventor after: Pang Baochuan Inventor before: Pang Baochuan Inventor before: Xu Duanquan |
|
| COR | Change of bibliographic data |
Free format text: CORRECT: INVENTOR; FROM: PANG BAOCHUAN XU DUANQUAN TO: XU DUANQUAN SUN XIAORONG PANG BAOCHUAN |
|
| C02 | Deemed withdrawal of patent application after publication (patent law 2001) | ||
| WD01 | Invention patent application deemed withdrawn after publication |
Open date: 20090729 |