CN109342378A - Bacterium colony growth conditions detection device and method based on multi-modality imaging technology - Google Patents
Bacterium colony growth conditions detection device and method based on multi-modality imaging technology Download PDFInfo
- Publication number
- CN109342378A CN109342378A CN201811047968.4A CN201811047968A CN109342378A CN 109342378 A CN109342378 A CN 109342378A CN 201811047968 A CN201811047968 A CN 201811047968A CN 109342378 A CN109342378 A CN 109342378A
- Authority
- CN
- China
- Prior art keywords
- bacterium colony
- image
- light source
- growth conditions
- camera
- 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.)
- Granted
Links
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/62—Systems in which the material investigated is excited whereby it emits light or causes a change in wavelength of the incident light
- G01N21/63—Systems in which the material investigated is excited whereby it emits light or causes a change in wavelength of the incident light optically excited
- G01N21/64—Fluorescence; Phosphorescence
- G01N21/6486—Measuring fluorescence of biological material, e.g. DNA, RNA, cells
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N21/41—Refractivity; Phase-affecting properties, e.g. optical path length
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N21/47—Scattering, i.e. diffuse reflection
Landscapes
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Immunology (AREA)
- Pathology (AREA)
- Analytical Chemistry (AREA)
- Biochemistry (AREA)
- General Health & Medical Sciences (AREA)
- General Physics & Mathematics (AREA)
- Physics & Mathematics (AREA)
- Chemical & Material Sciences (AREA)
- Engineering & Computer Science (AREA)
- Biomedical Technology (AREA)
- Molecular Biology (AREA)
- Nuclear Medicine, Radiotherapy & Molecular Imaging (AREA)
- Measuring Or Testing Involving Enzymes Or Micro-Organisms (AREA)
- Apparatus Associated With Microorganisms And Enzymes (AREA)
- Investigating, Analyzing Materials By Fluorescence Or Luminescence (AREA)
Abstract
The invention discloses a kind of bacterium colony growth conditions detection devices and method based on multi-modality imaging technology, the device includes: a white light source, a coherent laser light source and a fluorescence excitation light source, is irradiated as three classes light source in bacterium colony sample oblique upper and acquires for sample image respectively；One color camera, a high speed camera and a cooled camera, as three classes camera, the bacterium colony sample image under respectively irradiating to three classes light source respectively above bacterium colony sample is acquired；One imaging system, including imaging lens, light splitting piece, optical filter and relaying eyepiece, are arranged between bacterium colony sample and camera, realize the bacterium colony sample image imaging corresponding with three classes camera under three classes light source irradiates respectively, and imaging parameters are consistent；An additional computer receives three road imaging signals, completes image co-registration processing.Culture medium background influence is eliminated using multi-modal optical imagery and information fusion method, improves bacterium colony counting precision, realize the detection in all directions of bacterium colony growth conditions and is differentiated.
Description
Technical field
The present invention relates to field of optical detection more particularly to a kind of bacterium colony growth conditions inspections based on multi-modality imaging technology
Survey device and method.
Background technique
In food and drug safety field, microorganism is to lead to food apoilage, microbial toxin (pathogenic bacteria, helminth)
And the main reason for disease transmission (hepatitis virus), the food origin disease being induced by it are that the No.1 of China's food safety is asked
Topic.In the food hygiene management in China, microbiological indicator is divided into total plate count (total number of bacteria), coliform, mould, yeast
Bacterium and pathogenic bacteria.Bacterium colony, on the one hand can be by observing bacterium colony mainly as the mark for determining food microbial contamination degree
Quantity is contaminated the mark of degree as food, this is also in standard GB/T 4789.2-2010 " national food safety standard food
Product microbiological Test total plate count measurement " in carried out relevant regulations；It on the other hand, can also be by observation bacterium in food
The dynamic of middle breeding, to provide foundation when carrying out hygienical evaluation to test sample.Total plate count is exceeded or bacterial reproduction mistake
Fastly, it can illustrate that basic hygienic requirements is not achieved in the sanitary condition of its product to a certain extent, it will destroy the battalion of food
It forms point, accelerates the putrid and deteriorated of food, food is made to lose edible value.The exceeded serious food of consumer's edible microorganismus,
It is easy to suffer from the intestines problems such as dysentery, may cause the symptoms such as vomiting, diarrhea, be detrimental to health safety.
Bacterium colony counting is a most basic and most important job of microorganism routine inspection, and main use is cultivated at present
The mode of base artificial counting carries out, but during bacterium colony culture and artificial counting, following various factors can be to accurate fixed
Amount brings error.
Sprawling growth and pollution directly interfere to count or the growth of bacterium in sample are inhibited to influence the accurate of count results
Property.Culture fungus block uniformity difference causes bacterium colony growth uneven, and dispersion degree difference will cause bacterium colony chaining to a certain extent
Shape growth causes to count difficult.Particulate contaminant causes counting error in sample, some its sizes of the solid particle in sample with
Shape and bacterium colony are extremely similar, are difficult to differentiate between in shape, to cause counting error.Bacterium colony was grown slowly, required for causing
It is long to cultivate gate time.
Currently, the fields such as food and drug safety detection, count bacterium colony and the monitoring of growth conditions are from manually, partly
Manually develop to directions such as automation, intelligences.This requires online test methods to have high-resolution, quickly dynamic, multimode
The advantages that state, to realize the intelligence and informationization of bacterium colony detection technique.
Summary of the invention
Since the bacterium colony for needing to detect is wide in variety, growth course differs greatly, and in order to improve detection efficiency and precision, needs
A kind of detection method that can obtain many kinds of parameters simultaneously.The present invention is directed to these problems, provide it is a kind of based on it is multi-modal at
As the bacterium colony growth conditions detection device and method of technology, using optical detective technology, it is high to reach detection process precision, lossless
Hurt, speed is fast and other effects.
For living body bacterium colony, bacterium colony partial shape can change in growth course, can be by acquiring image
Feature obtains its growth conditions, and carries out counting processing to bacterium colony using image processing algorithm.And in bacterium colony growth course,
Diffusing structure and refractive index can change a lot, and after coherent laser is incident, different directions and scattering angle light are in space shape
When the phenomenon that at speckle interference, diffusing structure and refractive index change, the fluctuating quilt of speckle image frequency and intensity can be caused
It is average, by certain processing, quantitative analysis can be carried out to its growth course.Each hatching egg can be generated in bacterium colony growth course
White matter can generate fluorescence, and in its growth course under certain wavelength and the irradiation of the light of intensity, and fluorescence intensity can be with
The quantity of the protein with fluorescent effect wherein generated changes, and therefore, is counted with to fluorescence intensity change
Available bacterium colony growth conditions.
The present invention provides a kind of bacterium colony growth conditions detection device and method based on multi-modality imaging technology, technical sides
Case is as follows:
Bacterium colony growth conditions detection device based on multi-modality imaging technology includes:
One white light source, a coherent laser light source and a fluorescence excitation light source, as three classes light source on bacterium colony sample is oblique
Side is irradiated respectively to be acquired for sample image；
One color camera, a high speed camera and a cooled camera, as three classes camera, respectively to three above bacterium colony sample
Bacterium colony sample image under class light source respectively irradiates is acquired；
One imaging system, including imaging lens, light splitting piece, optical filter and relaying eyepiece, are arranged in bacterium colony sample and camera
Between, realize the bacterium colony sample image imaging corresponding with three classes camera under three classes light source irradiates respectively, and imaging parameters are consistent；
An additional computer receives three classes imaging signal, completes image co-registration processing.
Further, white light source, imaging lens and color camera constitute digital image acquisition device, are used to acquisition in real time
White-light image in bacterium colony growth course.
Further, coherent laser light source, imaging lens and high speed camera constitute laser coherence speckle imaging device, are used to
Acquire laser speckle image.
Further, fluorescence excitation light source, imaging lens, optical filter and cooled camera constitute fluorescence intensity imaging device,
For acquiring fluorescent image.
The present invention also provides the bacterium colony growth conditions detection methods based on multi-modality imaging technology, comprising:
Step 1: different types of common industrial bacterium colony is selected to be cultivated；
Step 2: utilizing bacterium colony growth conditions detection device, collects and records the White-light image in bacterium colony incubation, moves
State speckle image and fluorescent image；
Step 3: White-light image, dynamic speckle image and fluorescent image by image collecting device program numbers signal into
Enter computer and carries out image co-registration processing；
Step 4: will by image co-registration, treated that picture signal is compared with professional person's judging result, preservation
For training set, the topological relation between measurement parameter and bacterium colony growth conditions is established；
Step 5: trained set is brought into on-line measurement result, realizes the judgement to bacterium colony growth conditions.
Further, the acquisition with processing of White-light image include:
Denoising disposal is carried out to picture, original image is handled using Gaussian template, improves signal noise ratio (snr) of image；
Colony characteristics extraction is carried out using dilation erosion algorithm, mycelia growth in single colonie is obtained to different growing stage and is walked
To and length, calculate the ratio between mycelia pixel number and the gross area, obtain colony density；
Based on obtained mycelia growth characteristics image, individual element point is analyzed, and obtains link pixel quantity and total
Ratio between pixel quantity obtains mycelia growth Connected degree；
Compare the bacterium colony White-light image feature under different time, which includes shape feature and color characteristic, root
According to individual element intensity, colony characteristics variability is calculated.
Further, dynamic speckle image procossing includes:
On the basis of obtaining bacterium colony scattering properties, using the speckle measured based on the calculating of model parameter Power estimation method
The dynamic speckle power spectrum of image obtains bacterium colony growth activity parameter, wherein bacterium colony scattering properties includes colonial morphology, refraction
Rate, diffusing structure, scattering strength and angular distribution.
Further, fluorescence image processing includes:
Metabolism generates different proteins in bacterium colony growth course, is excited using monochromatic light, fluorescence signal is generated, according to fluorescence
Signal wavelength judges bacterium colony type, obtains bacterium colony growth activity according to fluorescence intensity measurement, carries out to fluorescence signal intensity related
Analysis obtains bacterium colony metabolic activity maximum time point, judges bacterium colony growth conditions.
Further, in the bacterium colony growth course reacted White-light image, dynamic speckle image and fluorescent image not
Same state parameter further uses multimodal information fusion method, above-mentioned three kinds of images is merged, comprehensive quantitative evaluation bacterium
It is born long status.
The present invention is monitored bacterium colony culture growth conditions using multi-modal optical imaging method, can effectively eliminate training
Base background influence is supported, bacterium colony counting precision is improved；
Using multi-modal measurement method, bacterium colony technology not only may be implemented, and bacterium colony can be detected according to dynamic speckle
Growth activity；
It can detecte the specific proteins generated in bacterium colony growth course using fluorescence detection method, while according to albumen spy
Sign fluorescence judges Colonial types, and obtains its growth conditions according to bacterium colony fluorescence coherent signal；
Detection and differentiation in all directions can be carried out to bacterium colony growth conditions using the method for multimodal information fusion.
Detailed description of the invention
Fig. 1 is bacterium colony growth conditions detection device schematic diagram of the embodiment of the present invention based on multi-modality imaging technology；
Fig. 2 is the algorithm flow chart that dynamic speckle power spectrum is calculated in the embodiment of the present invention；
Fig. 3 is the detection method flow chart of bacterium colony growth conditions of the embodiment of the present invention based on multi-modality imaging technology.
Specific embodiment
To make the objectives, technical solutions, and advantages of the present invention clearer, below in conjunction with specific embodiment, and reference
Attached drawing, the present invention is described in further detail.
The bacterium colony growth conditions detection device based on multi-modality imaging technology that the embodiment of the invention provides a kind of, wherein
Fig. 1 is please referred to, which includes:
One white light source 1, a coherent laser light source 2 and a fluorescence excitation light source 3 are oblique in bacterium colony sample as three classes light source
Top is irradiated respectively to be acquired for sample image；
One color camera, a high speed camera and a cooled camera, as three classes camera, above bacterium colony sample respectively to
Bacterium colony sample image under three classes light source respectively irradiates is acquired；
One imaging system, including imaging lens, light splitting piece, optical filter and relaying eyepiece, setting the bacterium colony sample with
Between the camera, the bacterium colony sample image imaging corresponding with the three classes camera under the three classes light source irradiates respectively is realized,
And imaging parameters are consistent；
An additional computer receives three classes imaging signal, completes image co-registration processing.
Further, white light source, imaging lens and color camera constitute digital image acquisition device, are used to acquisition in real time
White-light image in bacterium colony growth course；
In the present embodiment, digital image acquisition device:, can be real mainly including white light source 1, imaging lens and color camera
When acquisition bacterium colony growth course in color image.
Further, coherent laser light source, imaging lens and high speed camera constitute laser coherence speckle imaging device, are used to
Acquire laser speckle image；
In the present embodiment, laser coherence speckle imaging device: mainly including coherent laser light source 2, imaging lens and high speed
Camera, major function are to realize the acquisition of laser coherence speckle image.
Further, fluorescence excitation light source, imaging lens, optical filter and cooled camera constitute fluorescence intensity imaging device,
For acquiring fluorescent image；
In the present embodiment, fluorescence intensity imaging device: mainly including fluorescence excitation light source 3, imaging lens, filter wheel and height
Sensitivity cooled camera, major function are to realize excitation fluorescence signal acquisition.
The bacterium colony growth conditions detection method based on multi-modality imaging technology that the embodiment of the invention also provides a kind of, please join
See Fig. 3, comprising:
Step 1: different types of common industrial bacterium colony is selected to be cultivated；
Step 2: utilizing bacterium colony growth conditions detection device, collects and records the White-light image in bacterium colony incubation, moves
State speckle image and fluorescent image；
Step 3: White-light image, dynamic speckle image and fluorescent image by image collecting device program numbers signal into
Enter computer and carries out image co-registration processing；
Step 4: will by image co-registration, treated that picture signal is compared with professional person's judging result, preservation
For training set, the topological relation between measurement parameter and bacterium colony growth conditions is established；
Step 5: trained set is brought into on-line measurement result, realizes the judgement to bacterium colony growth conditions.
Further, the acquisition with processing of White-light image include:
Denoising disposal is carried out to picture, original image is handled using Gaussian template, improves signal noise ratio (snr) of image；
Colony characteristics extraction is carried out using dilation erosion algorithm, mycelia growth in single colonie is obtained to different growing stage and is walked
To and length, calculate the ratio between mycelia pixel number and the gross area, obtain colony density；
Based on obtained mycelia growth characteristics image, individual element point is analyzed, and obtains link pixel quantity and total
Ratio between pixel quantity obtains mycelia growth Connected degree；
Compare the bacterium colony White-light image feature under different time, which includes shape feature and color characteristic, root
According to individual element intensity, colony characteristics variability is calculated.
In the present embodiment, bacterium colony growth conditions color image processing method includes:
Processing for bacterium colony color image, according to different strain growth characteristics, at collected White-light image
Reason extracts characteristics of image, including shape feature and color characteristic, and calculates area of colony, Connected degree, and compares in a period of time
Shape degree of variation.
Extraction for blade train of thought density feature uses Digital Image Processing mode, carries out at denoising to picture first
Reason handles original image using Gaussian template, improves signal noise ratio (snr) of image；Then using dilation erosion algorithm to colony shape feature
It extracts, mycelia growth trend and length in single colonie then is obtained to different growing stage respectively, calculate mycelia pixel
The ratio between points and the gross area, obtain colony density；The calculating that mycelia grows Connected degree is based on obtained mycelia growth characteristics figure
Picture, individual element point are analyzed, and ratio between link pixel quantity and total pixel quantity is obtained, and are obtained mycelia growth and are connected
Degree of connecing, the bacterium colony White-light image feature being respectively compared in a period of time calculate colony characteristics variation according to individual element intensity
Property.
Further, dynamic speckle image procossing includes:
On the basis of obtaining bacterium colony scattering properties, using the speckle measured based on the calculating of model parameter Power estimation method
The dynamic speckle power spectrum of image obtains bacterium colony growth activity parameter, wherein bacterium colony scattering properties includes colonial morphology, refraction
Rate, diffusing structure, scattering strength and angular distribution.
In the present embodiment, the dynamic speckle image processing method of bacterium colony growth conditions includes:
The speckle image measured is analyzed using the dynamic speckle processing method based on parameter Estimation, it is available
Dynamic speckle signal, and quantitative analysis is carried out to bacterium colony growth conditions on this basis.Dynamic speckle signal was grown by bacterium colony
Diffusing structure and variations in refractive index in journey cause, and the speckle signals that are concerned with change in space and temporal intensity fluctuation and frequency
Reflect bacterium colony growth activity.It can use collected speckle image and laser measured for distribution power spectral density function
The change frequency and intensity of speckle signals.The dynamic speckle image obtained in the present invention using Fig. 1 device can be expressed as matrix
Form, and in view of the noise in measurement process can be expressed as
Y=HC+n,
Wherein Y is measuring signal, and H is dynamic scattering function, and C is to represent volume fraction different in flow rate, and n is represented to be deposited in measurement
Noise, and signal is independent from each other with noise.
Mainly and colonial morphology, refractive index and diffusing structure size are related for dynamic scattering function in the present invention, use
Mie scattering method can extract its diffusing structure according to the mycelia geometry that bacterium colony White-light image is shown, it is strong to obtain its scattering
The information such as degree and angular distribution.In the present invention on the basis of obtaining bacterium colony scattering properties, using optimize etc. mathematical methods, with
The mode of recursive iteration handles laser coherence speckle signals, obtains the power Spectral Estimation of dynamic speckle signal, principle
It is as follows:
The noise of k frequency and the covariance matrix of interference are indicated first are as follows:
The covariance matrix of sample of signal indicates are as follows:
In the situation known to measured value and dynamic scattering function, the estimation about x can be by weighted least-squares criterion
It provides:
Its algorithm flow is referring to figure 2..
Further, fluorescence image processing includes:
Metabolism generates different proteins in bacterium colony growth course, is excited using monochromatic light, fluorescence signal is generated, according to fluorescence
Signal wavelength judges bacterium colony type, obtains bacterium colony growth activity according to fluorescence intensity measurement, carries out to fluorescence signal intensity related
Analysis obtains bacterium colony metabolic activity maximum time point, judges bacterium colony growth conditions.
In the present embodiment, the fluorescence image processing method of bacterium colony growth conditions includes:
Metabolism generates different proteins in bacterium colony growth course, these protein can show certain fluorescent characteristic,
Using the monochromatic light exposure bacterium colony sample in certain wavelength (ultraviolet band) in the present invention, while narrowband is used in Image Acquisition
Optical filter removes influence of the exciting light for collected fluorescent image.The wavelength of fluorescence characteristic that different bacterium colonies generate is different, bacterium
It is related that the fluorescence signal intensity that growth process of being born generates to it generates protein concentration, when bacterium colony metabolic activity changes,
Fluorescence signal intensity can also generate certain fluctuating, it is assumed that and bacterium colony fluorescence signal intensity can be expressed as x (n) in a period of time,
Using the available bacterium colony metabolic activity maximum time point of correlation analysis, to judge bacterium colony growth conditions, auto-correlation
Analytical formula can indicate are as follows:
According to the fluorescence intensity auto-correlation function being calculated, it can judge that bacterium colony is grown according to auto-correlation function maximum
State most active time point.
Further, in the bacterium colony growth course reacted White-light image, dynamic speckle image and fluorescent image not
Same state parameter further uses multimodal information fusion method, above-mentioned three kinds of images is merged, comprehensive quantitative evaluation bacterium
It is born long status.
In the present embodiment, image co-registration includes: with state monitoring method
The White-light image obtained in the present invention using multi-modal optical imaging system and respective handling method, dynamic speckle figure
Picture and fluorescent image can react the different conditions parameter in bacterium colony growth course.In the present invention, multimode is further used
State information fusion method merges the image that various distinct methods measure, raw so as to comprehensive quantitative evaluation bacterium colony
Long status.
In the present embodiment, different types of common industrial bacterium colony is selected to be cultivated, using in the present invention it is multi-modal at
As apparatus and method, different times Colony hybridization is obtained, after carrying out use processing, is compared with professional person's judging result
It is right, and trained set is saved as, establish the topological relation between measurement parameter and bacterium colony growth conditions；Then to on-line measurement knot
Fruit brings established classification model of fit into, determines to realize bacterium colony growth conditions.
Particular embodiments described above has carried out further in detail the purpose of the present invention, technical scheme and beneficial effects
Describe in detail bright, it should be understood that the above is only a specific embodiment of the present invention, is not intended to restrict the invention, it is all
Within the spirit and principles in the present invention, any modification, equivalent substitution, improvement and etc. done should be included in protection of the invention
Within the scope of.
Claims (9)
1. a kind of bacterium colony growth conditions detection device based on multi-modality imaging technology characterized by comprising
One white light source, a coherent laser light source and a fluorescence excitation light source, as three classes light source in bacterium colony sample oblique upper point
It is not irradiated and is acquired for sample image；
One color camera, a high speed camera and a cooled camera, as three classes camera, respectively to described three above bacterium colony sample
Bacterium colony sample image under class light source respectively irradiates is acquired；
One imaging system, including imaging lens, light splitting piece, optical filter and relaying eyepiece, setting the bacterium colony sample with it is described
Between camera, realizes that the bacterium colony sample image under the three classes light source irradiates respectively is corresponding with the three classes camera and be imaged, and at
As parameter is consistent；
An additional computer receives three classes imaging signal, completes image co-registration processing.
2. the bacterium colony growth conditions detection device according to claim 1 based on multi-modality imaging technology, which is characterized in that
The white light source, imaging lens and color camera constitute digital image acquisition device, are used to acquisition bacterium colony growth course in real time
In White-light image.
3. the bacterium colony growth conditions detection device according to claim 1 based on multi-modality imaging technology, which is characterized in that
The coherent laser light source, imaging lens and high speed camera constitute laser coherence speckle imaging device, for acquiring laser speckle
Image.
4. the bacterium colony growth conditions detection device according to claim 1 based on multi-modality imaging technology, which is characterized in that
The fluorescence excitation light source, imaging lens, optical filter and cooled camera constitute fluorescence intensity imaging device, for acquiring fluorogram
Picture.
5. a kind of bacterium colony growth conditions detection method based on multi-modality imaging technology characterized by comprising
Step 1: different types of common industrial bacterium colony is selected to be cultivated；
Step 2: using bacterium colony growth conditions detection device described in Claims 1-4 4, bacterium colony incubation is collected and recorded
In White-light image, dynamic speckle image and fluorescent image；
Step 3: the three classes image, which enters computer by image collecting device program numbers signal, to carry out at image co-registration
Reason；
Step 4: the picture signal after described image fusion treatment is compared with professional person's judging result, saves as instruction
Practice set, establishes the topological relation between measurement parameter and bacterium colony growth conditions；
Step 5: the training is brought into on-line measurement result and is gathered, realizes the judgement to bacterium colony growth conditions.
6. the bacterium colony growth conditions detection method according to claim 5 based on multi-modality imaging technology, which is characterized in that
The acquisition of the White-light image includes: with processing
Denoising disposal is carried out to picture, original image is handled using Gaussian template, improves signal noise ratio (snr) of image；
Colony characteristics extraction is carried out using dilation erosion algorithm, to different growing stage obtain in single colonie mycelia growth trend and
Length calculates the ratio between mycelia pixel number and the gross area, obtains colony density；
Based on obtained mycelia growth characteristics image, individual element point is analyzed, and obtains link pixel quantity and total pixel
Ratio between point quantity obtains mycelia growth Connected degree；
Comparing the bacterium colony White-light image feature under different time, described image feature includes shape feature and color characteristic, according to
Individual element intensity calculates colony characteristics variability.
7. the bacterium colony growth conditions detection method according to claim 5 based on multi-modality imaging technology, which is characterized in that
The dynamic speckle image procossing includes:
On the basis of obtaining bacterium colony scattering properties, using the speckle image measured based on the calculating of model parameter Power estimation method
Dynamic speckle power spectrum, obtain bacterium colony growth activity parameter, wherein the bacterium colony scattering properties include colonial morphology, refraction
Rate, diffusing structure, scattering strength and angular distribution.
8. the bacterium colony growth conditions detection method according to claim 5 based on multi-modality imaging technology, which is characterized in that
The fluorescence image processing includes:
Metabolism generates different proteins in bacterium colony growth course, is excited using monochromatic light, fluorescence signal is generated, according to fluorescence signal
Wavelength judges bacterium colony type, obtains bacterium colony growth activity according to fluorescence intensity measurement, carries out correlation analysis to fluorescence signal intensity
Bacterium colony metabolic activity maximum time point is obtained, judges bacterium colony growth conditions.
9. according to the bacterium colony growth conditions detection method based on multi-modality imaging technology any in claim 5 to 8,
It is characterized in that, to different conditions in the bacterium colony growth course of the White-light image, dynamic speckle image and fluorescent image reaction
Parameter further uses multimodal information fusion method, three kinds of images is merged, the growth of comprehensive quantitative evaluation bacterium colony
State.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811047968.4A CN109342378B (en) | 2018-09-07 | 2018-09-07 | Colony growth state detection device and method based on multi-modal imaging technology |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811047968.4A CN109342378B (en) | 2018-09-07 | 2018-09-07 | Colony growth state detection device and method based on multi-modal imaging technology |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN109342378A true CN109342378A (en) | 2019-02-15 |
| CN109342378B CN109342378B (en) | 2021-01-01 |
Family
ID=65304992
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201811047968.4A Expired - Fee Related CN109342378B (en) | 2018-09-07 | 2018-09-07 | Colony growth state detection device and method based on multi-modal imaging technology |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109342378B (en) |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110141208A (en) * | 2019-04-12 | 2019-08-20 | 上海健康医学院 | A kind of flow imaging system that dynamic image combines and method |
| CN111122526A (en) * | 2019-12-18 | 2020-05-08 | 中国科学院南海海洋研究所 | Water algae detection method based on laser-induced fluorescence and fluid dynamic photomicrography |
| CN112611701A (en) * | 2020-12-10 | 2021-04-06 | 天津大学 | Circulating tumor cell detection device based on dynamic coherent optical imaging technology |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20090159812A1 (en) * | 2007-12-19 | 2009-06-25 | Singulex, Inc | Scanning analyzer for single molecule detection and methods of use |
| CN103842769A (en) * | 2011-08-02 | 2014-06-04 | 加利福尼亚大学董事会 | Rapid, massively parallel single-cell drug response measurements via live cell interferometry |
| CN204116228U (en) * | 2014-09-09 | 2015-01-21 | 青岛佳明测控科技股份有限公司 | The online fluorescence detection device of microorganism |
| CN106580294A (en) * | 2016-12-30 | 2017-04-26 | 上海交通大学 | Physiological signal remote monitoring system based on multimodal imaging technique and application thereof |
-
2018
- 2018-09-07 CN CN201811047968.4A patent/CN109342378B/en not_active Expired - Fee Related
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20090159812A1 (en) * | 2007-12-19 | 2009-06-25 | Singulex, Inc | Scanning analyzer for single molecule detection and methods of use |
| CN103842769A (en) * | 2011-08-02 | 2014-06-04 | 加利福尼亚大学董事会 | Rapid, massively parallel single-cell drug response measurements via live cell interferometry |
| CN204116228U (en) * | 2014-09-09 | 2015-01-21 | 青岛佳明测控科技股份有限公司 | The online fluorescence detection device of microorganism |
| CN106580294A (en) * | 2016-12-30 | 2017-04-26 | 上海交通大学 | Physiological signal remote monitoring system based on multimodal imaging technique and application thereof |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110141208A (en) * | 2019-04-12 | 2019-08-20 | 上海健康医学院 | A kind of flow imaging system that dynamic image combines and method |
| CN111122526A (en) * | 2019-12-18 | 2020-05-08 | 中国科学院南海海洋研究所 | Water algae detection method based on laser-induced fluorescence and fluid dynamic photomicrography |
| CN112611701A (en) * | 2020-12-10 | 2021-04-06 | 天津大学 | Circulating tumor cell detection device based on dynamic coherent optical imaging technology |
| CN112611701B (en) * | 2020-12-10 | 2023-02-28 | 天津大学 | Circulating tumor cell detection device based on dynamic coherent optical imaging technology |
Also Published As
| Publication number | Publication date |
|---|---|
| CN109342378B (en) | 2021-01-01 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN108351289B (en) | Analysis device | |
| Peng et al. | Potential prediction of the microbial spoilage of beef using spatially resolved hyperspectral scattering profiles | |
| CN100495032C (en) | Method and apparatus for detecting surface quality of egg | |
| CN108663339A (en) | Corn online test method of going mouldy based on spectrum and image information fusion | |
| CN105181912B (en) | A kind of Noninvasive Measuring Method of Freshness in rice storage | |
| CN109342378A (en) | Bacterium colony growth conditions detection device and method based on multi-modality imaging technology | |
| JP7271561B2 (en) | Method for identifying microorganisms using spectroscopic techniques | |
| Martsenyuk et al. | Multispectral control of water bodies for biological diversity with the index of phytoplankton | |
| CN104198325B (en) | Stem ratio measuring method in pipe tobacco based on computer vision | |
| Kwon et al. | Applications of smartphone cameras in agriculture, environment, and food: A review | |
| EP3688182B1 (en) | Methods and systems for automated assessment of antibiotic sensitivity | |
| CN102628794A (en) | Method for quickly measuring total quantity of livestock meat bacteria based on hyperspectral imaging technology | |
| CN103900972A (en) | Multi-feature fusion-based meat freshness hyperspectral image visual detection | |
| KR20220038602A (en) | Methods and systems for identifying microorganisms | |
| CN105466921A (en) | Simultaneous detection method of many samples | |
| US20040253660A1 (en) | Automated microbiological testing apparatus and method | |
| CN117095393A (en) | Microorganism detection method, system, electronic equipment and storage medium based on microscopic hyperspectral imaging technology | |
| CN104297136A (en) | Hyperspectral image-based method for forecasting growth of pseudomonas aeruginosa | |
| JP2017521069A (en) | Method for detecting the presence or absence of biological particles | |
| CN102788796B (en) | Nutrient diagnosis device and nutrient diagnosis method for nitrogen of crops based on multi-information integration of high spectral images and fluorescent images | |
| CN109668857A (en) | Tealeaves total plate count detection device and method based on near-infrared hyper-spectral image technique | |
| JP5807956B2 (en) | Method for measuring crop growth frequency of soil and method for judging fake production | |
| Muthalagu et al. | Developmental screening tool: accuracy and feasibility of non-invasive anaemia estimation | |
| CN115035102A (en) | Method for judging minimum bacteriostatic concentration based on coaxial holographic image | |
| JP4477173B2 (en) | Microorganism measuring method and apparatus |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20210101 Termination date: 20210907 |
|
| CF01 | Termination of patent right due to non-payment of annual fee |