CN208255072U - A kind of Enterozoa worm's ovum diagnostic imaging system of full-automation - Google Patents
A kind of Enterozoa worm's ovum diagnostic imaging system of full-automation Download PDFInfo
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- CN208255072U CN208255072U CN201820749650.XU CN201820749650U CN208255072U CN 208255072 U CN208255072 U CN 208255072U CN 201820749650 U CN201820749650 U CN 201820749650U CN 208255072 U CN208255072 U CN 208255072U
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Abstract
The utility model provides a kind of Enterozoa worm's ovum diagnostic imaging system of full-automation, comprising: the first motor adjustment component, for driving sample mobile；Second motor adjustment component, for driving camera mobile；Sample stage is set on the first motor adjustment component, for carrying the sample；Camera support component is set on the second motor adjustment component, for carrying camera；Light source, for providing illumination to the sample；Camera is set on the camera support component, for the sample to be imaged.
Description
Technical field
The utility model relates to biomedical technical field of microscopy more particularly to a kind of Enterozoa worms of full-automation
Ovum diagnostic imaging system.
Background technique
Cecil McMaster egg count method and Jia Shi add rattan method to be the method for two kinds of the most commonly used inspection parasitic infection,
For it can be saturated the worm's ovum that saline solution floats, accuracy is higher than Jia Shi and adds rattan smear method Maxwell method, is generally made
The accuracy of diagnostic system is measured for international goldstandard.Research hotspot mainly concentrates human body infection by Schistosoma (generally to deposit at present
Be Egyptian and south east asia) and roundworm, nematode, whipworm, the coccidia of ruminant etc. infect.By taking horse as an example, chitin is utilized
Matter fluorescent marker and the imaging of image procossing combination smart phone count, and test the sample of roundworm and nematode mixed infection, but its
Sample preparation link is complicated, also relatively strong to the iteration dependence of smart phone.The existing research system about on-site test is more
Base is in smart phone, the advantage being convenient for carrying using it, but its amplification factor is very low, for entire Maxwell plate counting region
Bright field imaging, will increase the difficulty of later image processing.And later period image procossing carries out worm's ovum using the method for machine learning
Identification, for schistosome ovum, sensitivity can reach 79%, and specificity reaches more than 90%, can be by sensitivity in future
It is increased to 90% or more.In addition, installing the support of autonomous Design on commercial microscope to acquire image, the later period carries out figure again
As processing.Or it is based on mobile phone, using fluorescence imaging, managing device everywhere to carry out identification in conjunction with mobile phone app transmitting image is also hot topic
Research direction.In conclusion current research is based on fluorescent marker, sample preparation is complicated, the fluorogram sector-meeting of later period shooting
Information of causing a disease is lost, and field range is unintelligible, or is combined with machine learning, but accuracy rate is too low, therefore develops one kind
It is extremely urgent independent of expert's operation while the simple standardizable diagnostic system of sample preparation.
Utility model content
(1) technical problems to be solved
Be directed to above-mentioned technical problem, the utility model proposes a kind of Enterozoa worm's ovum of full-automation diagnosis at
As system.
(2) technical solution
The utility model provides a kind of Enterozoa worm's ovum diagnostic imaging system of full-automation, comprising: the first fortune
Dynamic regulating member, for driving sample mobile；Second motor adjustment component, for driving camera mobile；Sample stage is set to institute
It states on the first motor adjustment component, for carrying the sample；Camera support component is set to the second motor adjustment component
On, for carrying camera；Light source, for providing illumination to the sample；Camera is set on the camera support component, is used
It is imaged in the sample.
In some embodiments of the utility model, the first motor adjustment component includes: the direction x-y optical translation
Platform comprising two stepper motors can drive the sample stage thereon mobile with the direction y in the x-direction.
In some embodiments of the utility model, the second motor adjustment component includes: the direction z optical translation platform,
It includes a stepper motor, and the camera support component thereon can be driven to move along the z-axis direction.
In some embodiments of the utility model, the second motor adjustment component further include: tilt displacement platform, setting
In the upper surface of the direction the z optical translation platform, plane with respect to the horizontal plane with tilt angle can be formed.
In some embodiments of the utility model, the camera support component includes: phase board, is set to described second
On motor adjustment component；Camera lens outrigger is set on the phase board, for accommodating the lens assembly of the camera.
In some embodiments of the utility model, the camera includes: camera body, is set on the phase board；
Lens assembly is set in the camera lens outrigger, including CCTV lens and Board lens；The light source is LED light, setting
Position below the phase board, with the lens assembly face.
In some embodiments of the utility model, further includes: controller, for controlling the direction x-y optical translation
The movement of the stepper motor of platform and the direction the z optical translation platform.
(3) beneficial effect
It can be seen from the above technical proposal that the utility model has the following beneficial effects:
Full-automatic Enterozoa worm's ovum diagnostic imaging system device has the characteristics that small in size, inexpensive；It utilizes
The diagnostic imaging system of the utility model carries out manual inspection without expert, and high degree of automation is suitble to economic backward area
Disease prevention and in time diagnosis；Former system is avoided to the dependence of smart phone version, the imaging of bigger visual field can be obtained,
And field range is more clear；It for the sample more than background impurities, is imaged using bright field, can shorten and simplify to a large amount of samples
The pre-processing process of product, while neural network recognization is utilized, it is more quickly, more accurate than previous traditional method；System can
To realize that the parasitic infection degree at scene, medication effect are monitored in time, goes and finds out what's going on, treat in time in time.
Detailed description of the invention
Fig. 1 is the structural representation of the Enterozoa worm's ovum diagnostic imaging system of the utility model embodiment full-automation
Figure.
Fig. 2 is the structural schematic diagram of U-net network.
Fig. 3 is the user interface figure of computer.
Fig. 4 is the image spliced after the coccidia ovum Sample Scan of sheep is imaged, and wherein A is entire image, and B, C, D, E divide
It is not the enlarged drawing of a, b, c, d in A.
Fig. 5 is the image of different worm's ovums, and wherein A and B is respectively the image of the coccidia ovum of sheep line eggs and ox, C and D difference
For the coccidia ovum of dog and the image of roundworm egg.
Fig. 6 is the result images of neural network segmentation identification, and wherein A is that the roundworm egg sample that formalin solution saves is clapped
Original image out, B are probability graph of the roundworm egg image after Network Recognition, and C is that roundworm egg image utilizes the figure after threshold process.D
It is the original image that the whipworm ovum sample of formalin solution preservation is taken, E is probability graph of the whipworm ovum image after Network Recognition, F
It is that whipworm ovum image utilizes the figure after threshold process.G is the original image that the coccidia ovum sample that formalin solution saves is taken, and H is
Probability graph of the coccidia ovum image after Network Recognition, I are that coccidia ovum image utilizes the figure after threshold process.
Fig. 7 is in the result images of neural network segmentation identification, and wherein A is the original image that roundworm egg fresh sample is taken, and B is
Probability graph of the roundworm egg image after Network Recognition, C are that roundworm egg image utilizes the figure after threshold process.D is that ascarid coccidia ovum is mixed
The original image that fresh sample is taken is closed, E is probability graph of the ascarid coccidia ovum mixed image after Network Recognition, and F is the mixing of ascarid coccidia ovum
Image utilizes the figure after threshold process.G is the original image that line eggs fresh sample is taken, and H is line eggs image after Network Recognition
Probability graph, I, which is line eggs image, utilizes the figure after threshold process.J is the original image that coccidia ovum fresh sample is taken, and K is coccidia
Probability graph of the ovum image after Network Recognition, L are that coccidia ovum image utilizes the figure after threshold process.
[symbol description]
The direction 1-x-y optical translation platform；2- sample stage；The direction 3-z optical translation platform；4- phase board；5- camera lens outrigger；6-
Camera body；7- light source；8-CCTV lens；9-Board lens；10- sample；11- controller；12- computer；13- stepping
Motor.
Specific embodiment
Below in conjunction with the attached drawing in embodiment and embodiment, the technical scheme in the embodiment of the utility model is carried out clear
Chu, complete description.Obviously, the described embodiments are only a part of the embodiments of the utility model, rather than whole realities
Apply example.Based on the embodiments of the present invention, those of ordinary skill in the art institute without making creative work
The every other embodiment obtained, fall within the protection scope of the utility model.
The utility model embodiment provides a kind of Enterozoa worm's ovum diagnostic imaging system of full-automation, such as Fig. 1
It is shown, comprising: motor adjustment component, support member, optical component and control unit.
Motor adjustment component includes: the 1, direction z translation stage of the direction an x-y optical translation platform and a tilt displacement
Platform.
The direction x-y optical translation platform 1 includes two stepper motors 13: can drive sample stage 2 thereon in the x-direction with the side y
To movement.
The direction z optical translation platform 3 includes a stepper motor 13, and phase board 4 thereon can be driven to move along the z-axis direction.
Tilt displacement platform is set to the upper surface of the direction z optical translation platform, the upper surface of the opposite direction z optical translation platform
Certain pitch angle is tilted, the plane being tilted a certain angle with horizontal plane can be formed.
Support member includes: camera lens outrigger 5, phase board 4 and sample stage 2.Wherein, sample stage 2 is set to the direction x-y light
It learns on translation stage, it can be mobile with the direction y in the x-direction under the drive of the direction x-y optical translation platform 1.Phase board 4 is set to the side z
It, can be movable in the z-direction under the drive of the direction z optical translation platform 3 on optical translation platform 3.Camera lens outrigger 5 is set to phase board
On 4, for accommodating the lens assembly of camera.
Optical component includes camera and light source 7.Camera includes camera body 6 and lens assembly, and camera body 6 is set to phase
On board 4, lens assembly is set in camera lens outrigger 5, including CCTV lens (monitoring camera) 8 and Board lens (spherical mirror
Head) 9.Light source 7 is LED light, is set to 4 lower section of phase board, the position with camera lens assembly face.
Control unit includes: controller 11, which can use single-chip microcontroller, flat for controlling the direction x-y optics
The movement of the stepper motor 13 of moving stage 1 and the direction z optical translation platform 3.
Enterozoa worm's ovum diagnostic imaging system further includes computer 12, connects controller 11 and camera, is used for and control
Device 11 processed interacts, and handles the image of camera shooting.
When being examined using the Enterozoa worm's ovum diagnostic imaging system of the present embodiment, progress sample preparation first.This reality
Example is applied using Cecil McMaster egg count floating method, specifically includes: first weighing sample 1-5g (fresh excrement measuring samples),
Sample dilution is differed for 10 times to 30 times using saturated salt solution, then is sieved with 40 mesh copper mesh, improvement is transferred to after mixing well
Cecil McMaster tally.
After sample preparation is good, i.e., observed using diagnostic imaging system.The Cecil McMaster meter of sample 10 will be filled
Number plate is placed on sample stage 2.It opens LED light to be illuminated, controller 11 controls stepper motor 13 and rotates, and drives sample stage 2
It is moved in the x-direction with the direction y, realizes the transverse shifting of sample, phase board 4 is driven to move in the z-direction, realize camera to sample 10
Longitudinal focusing.The information of sample 10 is acquired by CCTV lens 8 and Board lens 9 by camera, can very clearly
The scanning imagery to entire viewing area is realized in imaging.The installation of tilt translation platform can very easily adjust camera and camera lens
The upper optical path and sample surfaces keeping parallelism of composition.The image of camera acquisition is sent to computer 12, is carried out by computer 12
Processing obtains inspection result.
In another embodiment Enterozoa worm's ovum diagnostic imaging system of the utility model, as shown in Fig. 2, computer 12
Image is handled using U-net network.Compared to traditional convolutional neural networks, with U-net network remain convolutional layer,
Pond layer increases the link of up-sampling to guarantee that the dimension of picture size of input and output is identical.Computer 12 utilizes U-net net
When network handles image, label is finished with existing image first, establishes training set, U-net network is trained.
After the completion of U-net network training, then by new sample image input U-net network progress image segmentation, image is cut
It cuts and mainly includes: convolution, Chi Hua, up-sampling and etc., eliminate the full articulamentum of traditional neural network.
In the present embodiment, the image processing system of computer 12 has user interface, as shown in figure 3, by should
Image acquisition parameter and image storing path etc. is arranged in user interface, and in figure image right region can show image
Acquisition situation in real time, is adjusted convenient for timely feedbacking to operator.
Fig. 4 is the image spliced after the coccidia ovum Sample Scan of sheep is imaged, and wherein A is entire image, and B, C, D, E divide
It is not the enlarged drawing of a, b, c, d in A.After collecting image, by the way that parameter is arranged, the later period carries out image mosaic.Fig. 5 is
The image of collected difference worm's ovum, number of the worm's ovum in single picture is fewer after diluting 30 times, and A and B are respectively sheep
The coccidia ovum of line eggs and ox, C and D are respectively the coccidia ovum and roundworm egg of dog.In terms of image analysis, carried out after acquisition
The segmentation of image identifies, in Fig. 6, A, D, G are the original images that the sample that formalin solution saves is taken, and B, E, H are images through net
Probability graph after network identification, C, F, I are to utilize the figure after threshold process.In Fig. 7, A, D, G, J are the original images that fresh sample is taken,
B, E, H, K are probability graph of the image after Network Recognition, and C, F, I, L are to utilize the figure after threshold process.Pass through image again later
It marks and utilizes the image processing methods such as size selection to four collection results of each sample (one acquisition 432 opens image)
It is counted.Wherein, image tagged is a function in traditional image procossing, and size selection is finished by prior expert
The dimension data that is come out of label screened.
In conclusion the utility model be imaged according to Maxwell plate upper surface specific requirement combination mechanical structure, 3D printing,
The technologies such as automatic control build the micro imaging system for capableing of automatically scanning and focusing, can acquire out~100mm2Range is big
For later period diagnosis, which has the characteristics that small in size, inexpensive small image.Utilize the diagnosing image system of the utility model
System carries out manual inspection without expert, and high degree of automation is suitble to the disease prevention and diagnosis in time of economic backward area；It keeps away
Having exempted from former system can be obtained the imaging of bigger visual field to the dependence of smart phone version, and field range is more clear；It is right
It in the sample more than background impurities, is imaged using bright field, can shorten and simplify the pre-processing process to a large amount of samples, simultaneously
It is more quickly, more accurate than previous traditional method using neural network recognization；The parasitic infection at scene may be implemented in system
Degree, medication effect are monitored in time, are gone and found out what's going in time, are treated in time.
So far, attached drawing is had been combined the present embodiment is described in detail.According to above description, those skilled in the art
There should be clear understanding to the utility model.
It should be noted that in attached drawing or specification text, the implementation for not being painted or describing is affiliated technology
Form known to a person of ordinary skill in the art, is not described in detail in field.In addition, the above-mentioned definition to each element and not only limiting
Various specific structures, shape or the mode mentioned in embodiment, those of ordinary skill in the art can carry out simply more it
Change or replaces, such as:
(1) direction term mentioned in embodiment, such as "upper", "lower", "front", "rear", "left", "right" etc. are only ginsengs
The direction of attached drawing is examined, is not used to limit the protection scope of the utility model；
(2) above-described embodiment can be based on the considerations of design and reliability, and the collocation that is mixed with each other uses or and other embodiments
Mix and match uses, i.e., the technical characteristic in different embodiments can freely form more embodiments.
Particular embodiments described above has carried out into one the purpose of this utility model, technical scheme and beneficial effects
Step is described in detail, it should be understood that being not limited to this foregoing is merely specific embodiment of the utility model
Utility model, within the spirit and principle of the utility model, any modification, equivalent substitution, improvement and etc. done should all wrap
Containing being within the protection scope of the utility model.
Claims (7)
1. a kind of Enterozoa worm's ovum diagnostic imaging system of full-automation characterized by comprising
First motor adjustment component, for driving sample mobile；
Second motor adjustment component, for driving camera mobile；
Sample stage is set on the first motor adjustment component, for carrying the sample；
Camera support component is set on the second motor adjustment component, for carrying camera；
Light source, for providing illumination to the sample；
Camera is set on the camera support component, for the sample to be imaged.
2. Enterozoa worm's ovum diagnostic imaging system as described in claim 1 full-automatic, which is characterized in that described the
One motor adjustment component includes:
The direction x-y optical translation platform comprising two stepper motors, can drive the sample stage thereon in the x-direction with the direction y
It is mobile.
3. Enterozoa worm's ovum diagnostic imaging system as claimed in claim 2 full-automatic, which is characterized in that described the
Two motor adjustment components include:
The direction z optical translation platform a comprising stepper motor can drive the camera support component thereon to move along the z-axis direction
It is dynamic.
4. Enterozoa worm's ovum diagnostic imaging system as claimed in claim 3 full-automatic, which is characterized in that described the
Two motor adjustment components further include:
Tilt displacement platform is set to the upper surface of the direction the z optical translation platform, and can be formed with respect to the horizontal plane has inclination angle
The plane of degree.
5. full-automatic Enterozoa worm's ovum diagnostic imaging system as described in claim 1, which is characterized in that the phase
Machine support member includes:
Phase board is set on the second motor adjustment component；
Camera lens outrigger is set on the phase board, for accommodating the lens assembly of the camera.
6. full-automatic Enterozoa worm's ovum diagnostic imaging system as claimed in claim 5, which is characterized in that
The camera includes:
Camera body is set on the phase board；
Lens assembly is set in the camera lens outrigger, including CCTV lens and Board lens；
The light source is LED light, is set to below the phase board, the position with the lens assembly face.
7. full-automatic Enterozoa worm's ovum diagnostic imaging system as claimed in claim 4, which is characterized in that also wrap
It includes:
Controller, for control the direction the x-y optical translation platform and the direction the z optical translation platform stepper motor it is dynamic
Make.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108732174A (en) * | 2018-05-18 | 2018-11-02 | 中国科学技术大学 | A kind of Enterozoa worm's ovum diagnostic imaging system of full-automation |
| CN113139973A (en) * | 2021-04-01 | 2021-07-20 | 武汉市疾病预防控制中心 | Artificial intelligence-based plasmodium identification method and equipment |
-
2018
- 2018-05-18 CN CN201820749650.XU patent/CN208255072U/en active Active
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108732174A (en) * | 2018-05-18 | 2018-11-02 | 中国科学技术大学 | A kind of Enterozoa worm's ovum diagnostic imaging system of full-automation |
| CN113139973A (en) * | 2021-04-01 | 2021-07-20 | 武汉市疾病预防控制中心 | Artificial intelligence-based plasmodium identification method and equipment |
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