CN114897116B - Automatic change pathology department and use sampling device based on thing networking - Google Patents
Automatic change pathology department and use sampling device based on thing networking Download PDFInfo
- Publication number
- CN114897116B CN114897116B CN202210579420.4A CN202210579420A CN114897116B CN 114897116 B CN114897116 B CN 114897116B CN 202210579420 A CN202210579420 A CN 202210579420A CN 114897116 B CN114897116 B CN 114897116B
- Authority
- CN
- China
- Prior art keywords
- sampling
- electronic tag
- hash code
- sample
- image
- 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.)
- Active
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06K—GRAPHICAL DATA READING; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K17/00—Methods or arrangements for effecting co-operative working between equipments covered by two or more of main groups G06K1/00 - G06K15/00, e.g. automatic card files incorporating conveying and reading operations
- G06K17/0022—Methods or arrangements for effecting co-operative working between equipments covered by two or more of main groups G06K1/00 - G06K15/00, e.g. automatic card files incorporating conveying and reading operations arrangements or provisious for transferring data to distant stations, e.g. from a sensing device
- G06K17/0029—Methods or arrangements for effecting co-operative working between equipments covered by two or more of main groups G06K1/00 - G06K15/00, e.g. automatic card files incorporating conveying and reading operations arrangements or provisious for transferring data to distant stations, e.g. from a sensing device the arrangement being specially adapted for wireless interrogation of grouped or bundled articles tagged with wireless record carriers
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/30—Computing systems specially adapted for manufacturing
Abstract
The invention relates to the technical field of medical instruments, in particular to an automatic sampling device for a pathology department based on the Internet of things, which comprises a high-speed sampling transmission belt, wherein a sampling sample with an electronic tag is placed on the high-speed sampling transmission belt, a camera is fixedly arranged on the high-speed sampling transmission belt, an electronic tag reader is fixedly arranged on one side of the camera, the camera and the electronic tag reader are electrically and mechanically connected with an upper computer, the camera is used for acquiring an image of the sampling sample with the electronic tag, the upper computer is used for extracting a hash code from the image of the sampling sample with the electronic tag, the electronic tag reader is used for identifying the serial number id of the sampling sample with the electronic tag, and the upper computer is also used for establishing mapping between the serial number id of the sampling sample with the electronic tag and the corresponding hash code.
Description
Technical Field
The invention relates to the technical field of medical instruments, in particular to an automatic sampling device for a pathology department based on the Internet of things.
Background
Many sampling techniques for pathology department are available in the prior art, for example, CN202120895201.8 of patent document discloses a human body sampling device for pathology department, which can drive a screw rod and a sliding mounting plate to rotate by screw threads through a second motor when in use, and further adjust the position of the sliding mounting plate, so that the sampling tube can be conveniently taken out and put in; for example, CN202020226744.6 in the patent literature discloses a pathology department sample sampling device, which is convenient for cutting tissue and placing a tissue sample in a packaging vessel, and for example, CN201710971856.7 discloses a pathology department sample sampling device, which adopts a structure convenient for disassembly, and can be disassembled and assembled conveniently, so as to realize replacement of a sampling needle.
Disclosure of Invention
The invention aims to provide an automatic sampling device for a pathology department based on the Internet of things, so as to solve the problems in the background technology.
In order to solve the technical problems, the invention provides the following technical scheme: automatic sampling device for pathology department based on thing networking, including high-speed sample transmission band, high-speed sample transmission band on be used for placing the sample of taking electronic tags, high-speed sample transmission band on fixedly set up the camera, camera one side fixedly set up the electronic tags and read the ware, camera, electronic tags read ware all with upper computer electrical connection, the camera be used for gathering the image of taking electronic tags's sample, the upper computer be located and draw the hash code by the image of taking electronic tags's sample, electronic tags read the serial number id that is used for discerning the sample of taking electronic tags, the upper computer still be used for establishing the mapping between serial number id and the corresponding hash code of taking electronic tags's sample.
Furthermore, the upper computer is provided with a hash code generating unit, a mapping construction unit, a storage unit and an output unit which are connected, wherein the hash code generating unit is used for extracting a hash code from the image of the sampling sample with the electronic tag; the mapping construction unit is used for establishing mapping between the serial number id of the sampling sample with the electronic tag and the corresponding hash code; the storage unit is used for storing the mapping between the serial number id of the sampling sample with the electronic tag and the corresponding hash code; and the output unit is used for interacting with the storage unit and supporting the input of the hash code and the output of the number id of the sampling sample with the electronic tag.
Further, a storage medium is configured on the upper computer, and the storage medium stores a program for executing commands of the hash code generation unit, the mapping construction unit, the storage unit and the output unit.
Further, the extracting of the hash code from the image of the sampled sample with the electronic tag specifically includes firstly extracting multi-vector image features from the image of the sampled sample with the electronic tag, and then converting the multi-vector image features into the hash code.
Further, the multi-vector image features are extracted from the image of the sampling sample with the electronic tag, specifically, the labeled identification points in the image features are firstly determined, and the relationship among the identification points is as follows:
r (h) = sum (n (e) × v (h, e)), v (h, e) is a relation value between identification points, n (e) is a corresponding weight, e is a variable representing different points, and a mathematical operator relation between the identification points:
Z＝1-R h 0.5 VNR e -1 V T R h 0.5 where V is the identification point forming a matrix, R h Forming a matrix for identifying relationship values between points, R e A matrix formed for the sum features, N being a matrix formed for N; and obtaining the image characteristics of multiple vectors by utilizing Z and convolution calculation.
Compared with the prior art, the invention has the beneficial effects that:
the sampling sample with the electronic tag is transmitted by the high-speed sampling transmission belt, the camera collects images of the sampling sample with the electronic tag, the upper computer extracts hash codes from the images of the sampling sample with the electronic tag, the electronic tag reader identifies the number id of the sampling sample with the electronic tag at the same time, the upper computer establishes mapping between the number id of the sampling sample with the electronic tag and the corresponding hash codes, so that the input hash codes can be supported, the number id of the sampling sample with the electronic tag is output, and the sampling sample data storage and the output speed can be greatly improved.
Drawings
Fig. 1 is an overall structural view of an automatic pathology department sampling device based on the internet of things.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be obtained by a person skilled in the art without making any creative effort based on the embodiments in the present invention, belong to the protection scope of the present invention.
The application discloses automatic pathology department uses sampling device based on thing networking, as figure 1, it includes high-speed sample transmission band 201, high-speed sample transmission band 201 on be used for placing the sample 200 of taking the electronic tags, high-speed sample transmission band 201 on fixedly set up camera 102, camera 102 one side fixedly set up electronic tags reader 101, camera 102, electronic tags reader 101 all be connected with host computer 100 electricity, camera 102 be used for gathering the image of the sample 200 of taking the electronic tags, host computer 100 be used for drawing the hash code by the image of the sample 200 of taking the electronic tags, electronic tags reader 101 be used for discerning the serial number id of the sample 200 of taking the electronic tags, host computer 100 still be used for establishing the mapping between serial number id of the sample 200 of taking the electronic tags and the corresponding hash code; in specific implementation, in the process that the sampling sample 200 with the electronic tag is transmitted through the high-speed sampling conveyor belt 201, the camera 102 collects an image of the sampling sample 200 with the electronic tag, the upper computer 100 extracts a hash code from the image of the sampling sample 200 with the electronic tag, the electronic tag reader 101 simultaneously identifies the serial number id of the sampling sample 200 with the electronic tag, and the upper computer 100 establishes mapping between the serial number id of the sampling sample 200 with the electronic tag and the corresponding hash code, so that the hash code can be input, and the serial number id of the sampling sample 200 with the electronic tag is output, so that the speed of storing and outputting the sampling sample data can be greatly improved.
Preferably, the upper computer 100 is configured with a hash code generating unit, a mapping construction unit, a storage unit and an output unit, which are connected to each other, wherein the hash code generating unit is configured to extract a hash code from an image of the sampling sample 200 with the electronic tag;
the mapping construction unit is used for establishing mapping between the serial number id of the sampling sample 200 with the electronic tag and the corresponding hash code; the storage unit is used for storing the mapping between the serial number id of the sampling sample 200 with the electronic tag and the corresponding hash code; the output unit is used for interacting with the storage unit, supporting the input of the hash code and outputting the number id of the sampling sample 200 with the electronic tag; in a specific implementation, the hash code generation unit extracts a hash code from an image of the sampled sample 200 with the electronic tag; the mapping construction unit establishes mapping between the serial number id of the sampling sample 200 with the electronic tag and the corresponding hash code; the storage unit stores the mapping between the serial number id of the sampling sample 200 with the electronic tag and the corresponding hash code; the output unit supports inputting a hash code and outputting the number id of the sampling sample 200 with the electronic tag.
Preferably, the hash code is extracted from the image of the sampled sample 200 with the electronic tag, specifically, the image features of the multiple vectors are first extracted from the image of the sampled sample 200 with the electronic tag, and then the image features of the multiple vectors are converted into the hash code.
The method comprises the following steps of extracting multi-vector image features from an image of a sampling sample with an electronic tag, specifically, firstly determining mark identification points in the image features, wherein the relationship among the identification points is as follows:
r (h) = sum (n (e) × v (h, e)), v (h, e) is a relation value between identification points, n (e) is a corresponding weight, e is a variable representing different points, and a mathematical operator relation between the identification points:
Z＝1-R h 0.5 VNR e -1 V T R h 0.5 where V is the identification point forming a matrix, R h Forming a matrix for identifying relationship values between points, R e A matrix formed for the sum features, N being a matrix formed for N; and obtaining the image characteristics of multiple vectors by utilizing Z and convolution calculation.
It can be understood that the upper computer described in the present application is configured with a storage medium, and the storage medium stores a program for executing commands of the hash code generation unit, the mapping construction unit, the storage unit, and the output unit.
Finally, it should be noted that: although the present invention has been described in detail with reference to the foregoing embodiments, it will be apparent to those skilled in the art that changes may be made in the embodiments and/or equivalents thereof without departing from the spirit and scope of the invention. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (4)
1. The sampling device for the automated pathology department based on the Internet of things is characterized by comprising a high-speed sampling transmission belt, wherein the high-speed sampling transmission belt is used for placing sampling samples with electronic tags, a camera is fixedly arranged on the high-speed sampling transmission belt, an electronic tag reader is fixedly arranged on one side of the camera, the camera and the electronic tag reader are electrically and mechanically connected with an upper computer, the camera is used for collecting images of the sampling samples with the electronic tags, the upper computer is used for extracting hash codes from the images of the sampling samples with the electronic tags, the electronic tag reader is used for identifying the serial number id of the sampling samples with the electronic tags, and the upper computer is also used for establishing mapping between the serial number id of the sampling samples with the electronic tags and the corresponding hash codes;
the method comprises the following steps of extracting multi-vector image features from an image of a sampling sample with an electronic tag, specifically, firstly determining mark identification points in the image features, wherein the relationship among the identification points is as follows:
r (h) = sum (n (e) × v (h, e)), v (h, e) is a relation value between identification points, n (e) is a corresponding weight, e is a variable representing different points, and a mathematical operator relation between the identification points:
Z＝1-R h 0.5 VNR e -1 V T R h 0.5 where V is the identification point forming a matrix, R h Forming a matrix for identifying relationship values between points, R e A matrix formed for the sum features, N being a matrix formed for N; and obtaining the image characteristics of multiple vectors by utilizing Z and convolution calculation.
2. The sampling device for the internet of things-based automated pathology department according to claim 1, wherein the upper computer is configured with a hash code generation unit, a mapping construction unit, a storage unit and an output unit which are connected, wherein the hash code generation unit is used for extracting a hash code from an image of a sampling sample with an electronic tag; the mapping construction unit is used for establishing mapping between the serial number id of the sampling sample with the electronic tag and the corresponding hash code; the storage unit is used for storing the mapping between the serial number id of the sampling sample with the electronic tag and the corresponding hash code; and the output unit is used for interacting with the storage unit and supporting the input of the hash code and the output of the number id of the sampling sample with the electronic tag.
3. The Internet of things-based sampling device for the automated pathology department according to claim 1, wherein a storage medium is configured on the upper computer, and the storage medium stores programs for executing commands of the hash code generation unit, the mapping construction unit, the storage unit and the output unit.
4. The internet-of-things-based sampling device for the automated pathology department according to claim 1, wherein the hash code is extracted from the image of the sampled sample with the electronic tag, specifically, multi-vector image features are firstly extracted from the image of the sampled sample with the electronic tag, and then the multi-vector image features are converted into the hash code.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210579420.4A CN114897116B (en) | 2022-05-25 | 2022-05-25 | Automatic change pathology department and use sampling device based on thing networking |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210579420.4A CN114897116B (en) | 2022-05-25 | 2022-05-25 | Automatic change pathology department and use sampling device based on thing networking |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN114897116A CN114897116A (en) | 2022-08-12 |
| CN114897116B true CN114897116B (en) | 2022-12-09 |
Family
ID=82725703
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210579420.4A Active CN114897116B (en) | 2022-05-25 | 2022-05-25 | Automatic change pathology department and use sampling device based on thing networking |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114897116B (en) |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102568219A (en) * | 2010-12-27 | 2012-07-11 | 卡波施交通公司 | Method for capturing images of vehicles |
| CN111612963A (en) * | 2020-05-21 | 2020-09-01 | 广东乐佳印刷有限公司 | Bill voucher anti-counterfeiting detection method and device based on intelligent equipment |
Family Cites Families (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP4285277B2 (en) * | 2004-03-03 | 2009-06-24 | カシオ計算機株式会社 | Image capturing apparatus, electronic tag information and image data management system, and program |
| US8430301B2 (en) * | 2009-11-23 | 2013-04-30 | Konica Minolta Laboratory U.S.A., Inc. | Document authentication using hierarchical barcode stamps to detect alterations of barcode |
| CN108229596B (en) * | 2016-12-09 | 2024-03-26 | 北京大码技术有限公司 | Combined two-dimensional code, electronic certificate carrier, generating and reading device and method |
| CN106649886A (en) * | 2017-01-13 | 2017-05-10 | 深圳市唯特视科技有限公司 | Method for searching for images by utilizing depth monitoring hash of triple label |
| CN210071671U (en) * | 2019-02-15 | 2020-02-14 | 武汉互创联合科技有限公司 | Imaging system capable of automatically identifying sample |
| CN110503362A (en) * | 2019-08-01 | 2019-11-26 | 深圳市珍久库科技有限公司 | A kind of intelligent repository management method and system based on block chain |
-
2022
- 2022-05-25 CN CN202210579420.4A patent/CN114897116B/en active Active
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102568219A (en) * | 2010-12-27 | 2012-07-11 | 卡波施交通公司 | Method for capturing images of vehicles |
| CN111612963A (en) * | 2020-05-21 | 2020-09-01 | 广东乐佳印刷有限公司 | Bill voucher anti-counterfeiting detection method and device based on intelligent equipment |
Also Published As
| Publication number | Publication date |
|---|---|
| CN114897116A (en) | 2022-08-12 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109009102B (en) | Electroencephalogram deep learning-based auxiliary diagnosis method and system | |
| CN107153844A (en) | The accessory system being improved to flowers identifying system and the method being improved | |
| CN1788295A (en) | Device for transmitting data via the internet | |
| CN104751004A (en) | Disease pre-warning method, device and system | |
| CN105825046A (en) | Medical data collecting and processing method and device | |
| CN114897116B (en) | Automatic change pathology department and use sampling device based on thing networking | |
| CN105574795A (en) | Mobile informationized public health service platform | |
| CN204926123U (en) | Plant species recognition device based on handheld terminal blade image | |
| Randazzo et al. | Development and Validation of an Algorithm for the Digitization of ECG Paper Images | |
| CN110660477A (en) | System and method for automatically screening and labeling helicobacter pylori | |
| CN111144506B (en) | Liver bag worm identification method based on ultrasonic image, storage medium and ultrasonic equipment | |
| CN109805921B (en) | Electrocardio data cross-platform sampling method and electrocardio monitoring system | |
| CN106709224A (en) | Diabetic retinopathy diagnosis system and method | |
| CN113693610B (en) | Method and device for processing few-lead electrocardiogram data, storage medium and computer equipment | |
| CN115032500A (en) | Grid-connected fault identification method based on big data analysis | |
| CN111402242B (en) | Medical image refinement processing system and method | |
| CN113723519A (en) | Electrocardio data processing method and device based on contrast learning and storage medium | |
| CN111709946A (en) | Image data analysis method and device, terminal equipment and storage medium | |
| CN212809223U (en) | Sample information acquisition cabin based on RFID technology | |
| CN206892868U (en) | A kind of efficient medical imaging acquisition analysis system | |
| CN107945860A (en) | The Hui Ku of medical instrument, outbound examine item by item method and apparatus and its point check system | |
| CN117238037B (en) | Dynamic action recognition method, device, equipment and storage medium | |
| Senavongse et al. | THE DESIGNING OF A BIOINFORMATICS MICROSCOPE TO OBSERVE BIOPSY CANCER CELLS USING AN IMAGING PROCESSING SYSTEM VIA MEDICAL WEB SERVICES | |
| CN107753016A (en) | A kind of cardiac electric data sampler data presentation system and method | |
| CN117153343B (en) | Placenta multiscale analysis system |
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 |