CN114660076B - Medical tube coating quality detection method and system - Google Patents
Medical tube coating quality detection method and system Download PDFInfo
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- 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
- G01N21/84—Systems specially adapted for particular applications
- G01N21/88—Investigating the presence of flaws or contamination
- G01N21/8851—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B11/00—Measuring arrangements characterised by the use of optical techniques
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B11/00—Measuring arrangements characterised by the use of optical techniques
- G01B11/08—Measuring arrangements characterised by the use of optical techniques for measuring diameters
- G01B11/12—Measuring arrangements characterised by the use of optical techniques for measuring diameters internal diameters
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B11/00—Measuring arrangements characterised by the use of optical techniques
- G01B11/30—Measuring arrangements characterised by the use of optical techniques for measuring roughness or irregularity of surfaces
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- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
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- G06N3/02—Neural networks
- G06N3/08—Learning methods
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
- G06T7/0012—Biomedical image inspection
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- 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
- G01N21/84—Systems specially adapted for particular applications
- G01N21/88—Investigating the presence of flaws or contamination
- G01N21/8851—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges
- G01N2021/8887—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges based on image processing techniques
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10056—Microscopic image
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- G—PHYSICS
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- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20081—Training; Learning
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- G06T2207/00—Indexing scheme for image analysis or image enhancement
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- G06T2207/20084—Artificial neural networks [ANN]
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- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30168—Image quality inspection
Abstract
The invention provides a medical tube coating quality detection method and system, which are applied to the technical field of data processing, and the method comprises the following steps: the implantation environment information is determined by obtaining the type of the medical tube. And performing feature extraction on the implantation environment to generate first environment feature information. And matching the first structural threshold characteristic according to the first environmental characteristic information. The medical tube is subjected to image acquisition. The collected image features are extracted to generate first structural features of the medical tube. Determining whether the first structural feature satisfies the first structural threshold feature. And if so, obtaining a first structural quality inspection qualified instruction, and adding a first quality inspection result. The technical problem that the quality of the medical tube coating cannot be accurately measured due to the fact that a medical tube coating quality detection method is lacked in the prior art is solved. The comprehensive and accurate quality detection result of the medical tube is generated, and the technical effect of evaluating the quality of the medical tube coating more accurately and comprehensively is realized.
Description
Technical Field
The invention relates to the technical field of data processing, in particular to a medical tube coating quality detection method and system.
Background
Medical tubes are widely used in various medical scenes, and various types of surgical tubes are clinically used, such as artificial blood vessels, artificial bones, postoperative drainage tubes and other medical tube materials with different purposes and other parameters are different. In order to avoid problems such as rejection, blood coagulation, and allergic reaction during use, medical tubes are often coated with a coating of a special material to meet the requirements of different implantation environments.
However, the quality of the medical tube coating in the prior art lacks of a standardized detection method, so that the quality of the medical tube coating cannot be accurately measured, and unnecessary safety accidents are caused.
Therefore, the technical problem that the quality of the medical tube coating cannot be accurately measured due to the lack of a medical tube coating quality detection method exists in the prior art.
Disclosure of Invention
The application provides a medical tube coating quality detection method and system, which are used for solving the technical problem that medical tube coating quality cannot be accurately measured due to the fact that a medical tube coating quality detection method is lacked in the prior art.
In view of the above, the present application provides a medical tube coating quality detection method and system.
In a first aspect of the present application, a medical tube coating quality detection method is provided, the method is applied to a medical tube coating quality detection system, the system is communicatively connected with an image acquisition module, and the method includes: obtaining a first medical tube model, and determining first implantation environment information; performing feature extraction on the first implantation environment to generate first environment feature information; matching a first structure threshold characteristic according to the first environment characteristic information; conveying the first medical tube to a first image acquisition module to obtain a first image acquisition result; performing feature extraction on the first image acquisition result to generate a first structural feature, wherein the first structural feature and the first structural threshold feature are in one-to-one correspondence; determining whether the first structural feature satisfies the first structural threshold feature; and if so, obtaining a first structural quality inspection qualified instruction, and adding a first quality inspection result.
In a second aspect of the present application, there is provided a medical tube coating quality detection system, the system being in communication with an image acquisition module, the system comprising: a first obtaining unit, configured to obtain a model of a first medical tube, and determine first implantation environment information; the first generation unit is used for extracting the characteristics of the first implantation environment and generating first environment characteristic information; the first matching unit is used for matching a first structure threshold characteristic according to the first environment characteristic information; the second obtaining unit is used for conveying the first medical tube to the first image acquisition module to obtain a first image acquisition result; the first processing unit is used for performing feature extraction on the first image acquisition result to generate a first structural feature, wherein the first structural feature and the first structural threshold feature are in one-to-one correspondence; a first judging unit configured to judge whether the first structural feature satisfies the first structural threshold feature; and the third obtaining unit is used for obtaining a first structural quality inspection qualified instruction if the first structural quality inspection qualified instruction is met, and adding the first quality inspection result.
In a third aspect of the present application, there is provided an electronic device including: a processor coupled to a memory for storing a program that, when executed by the processor, causes a system to perform the steps of the method according to the first aspect.
In a fourth aspect of the present application, a computer-readable storage medium is provided, on which a computer program is stored, which computer program, when being executed by a processor, carries out the steps of the method according to the first aspect.
One or more technical solutions provided in the present application have at least the following technical effects or advantages:
according to the method provided by the embodiment of the application, the implantation environment information is determined by acquiring the type of the medical tube. And performing feature extraction on the implantation environment to generate first environment feature information. And matching the first structural threshold characteristic according to the first environmental characteristic information. The medical tube is subjected to image acquisition. The collected image features are extracted to generate first structural features of the medical tube. The quality of the medical tube coating is evaluated from multiple aspects such as macroscopic microstructure, compatibility, antibacterial property and the like, and finally, a more accurate detection result of the quality of the medical tube coating is obtained. The technical problem that the quality of the medical tube coating cannot be accurately measured due to the fact that a medical tube coating quality detection method is lacked in the prior art is solved. The comprehensive and accurate quality detection result of the medical tube is generated, and the technical effect of evaluating the quality of the medical tube coating more accurately and comprehensively is realized.
The foregoing description is only an overview of the technical solutions of the present application, and the present application can be implemented according to the content of the description in order to make the technical means of the present application more clearly understood, and the following detailed description of the present application is given in order to make the above and other objects, features, and advantages of the present application more clearly understandable.
Drawings
FIG. 1 is a schematic flow chart of a method for detecting the quality of a coating on a medical tube according to the present application;
fig. 2 is a schematic flow chart illustrating a process of determining whether the first structural characteristic satisfies the first structural threshold characteristic in a medical tube coating quality inspection method provided in the present application;
fig. 3 is a schematic flow chart illustrating the antibacterial property evaluation result obtained in the medical tube coating quality detection method provided by the present application;
FIG. 4 is a schematic diagram of a medical tube coating quality detection system according to the present application;
fig. 5 is a schematic structural diagram of an exemplary electronic device of the present application.
Description of reference numerals: the electronic device comprises a first obtaining unit 11, a first generating unit 12, a first matching unit 13, a second obtaining unit 14, a first processing unit 15, a first judging unit 16, a third obtaining unit 17, an electronic device 300, a memory 301, a processor 302, a communication interface 303 and a bus architecture 304.
Detailed Description
The application provides a medical tube coating quality detection method and system, which are used for solving the technical problem that the medical tube coating quality cannot be accurately measured due to the fact that a medical tube coating quality detection method is lacked in the prior art.
In view of the above technical problems, the technical solution provided by the present application has the following general idea:
according to the method provided by the embodiment of the application, the implantation environment information is determined by acquiring the type of the medical tube. And performing feature extraction on the implantation environment to generate first environment feature information. And matching the first structural threshold characteristic according to the first environmental characteristic information. The medical tube is subjected to image acquisition. The collected image features are extracted to generate first structural features of the medical tube. Determining whether the first structural feature satisfies the first structural threshold feature. The medical tube coating quality is evaluated from multiple aspects, and finally, a more accurate medical tube coating quality detection result is obtained. The technical problem that the quality of the medical tube coating cannot be accurately measured due to the fact that a medical tube coating quality detection method is lacked in the prior art is solved.
Having described the basic principles of the present application, the technical solutions in the present application will be described clearly and completely with reference to the accompanying drawings, and it should be understood that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments of the present application, and the present application is not limited to the exemplary embodiments described herein. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present application without making any creative effort, shall fall within the protection scope of the present application. It should be further noted that, for the convenience of description, only some but not all of the relevant portions of the present application are shown in the drawings.
Example one
As shown in fig. 1, the present application provides a method for quality inspection of a coating layer of a medical tube, the method comprising:
s100: obtaining the model of a first medical tube, and determining first implantation environment information;
in particular, medical tubes are commonly used in various medical scenes, and many types of surgical tubes are clinically used, and parameters such as medical tube materials for different purposes, such as artificial blood vessels, postoperative drainage tubes, and the like, are different. If the drainage tube after operation just includes the pipeline of latex tube, silicone tube and other materials preparation. The drainage tube is generally used by implanting the tube into a corresponding part and guiding pus, exuded blood, tissue fluid and other liquids accumulated between tissues or in a body cavity to the outside of the body by a siphon or negative pressure suction principle. In order to avoid problems such as rejection, blood coagulation and anaphylaxis during use, the medical tube needs to be coated with a film or protein coating, and the like, and the medical tube is very likely to have serious consequences when the surface coating of the medical tube is damaged. Therefore, by acquiring the model of the first medical tube, which is the medical tube to be detected in the embodiment, information of the medical tube is acquired. And determining first implantation environment information which is environment information of the medical tube implantation.
S200: performing feature extraction on the first implantation environment to generate first environment feature information;
s300: matching a first structure threshold characteristic according to the first environment characteristic information;
specifically, the characteristics of the implantation environment of the medical tube are extracted, and the characteristics of the implantation environment such as the implantation position and the implantation depth of the medical tube are acquired. For example, the medical tube is used as a blood vessel substitute for repairing and replacing a diseased blood vessel, structural information of the site such as an application environment of the site, an implantation depth, and a size of the implantation site is acquired, and peripheral structural characteristic information of the implantation site, that is, first environmental characteristic information is generated. The characteristic information of the peripheral structure of the implantation position is obtained according to the first environment characteristic information, and the matching of the structural threshold characteristic of the medical tube is carried out. When the feature information of the peripheral structure is matched with the structural threshold feature, a structural feature-structural threshold feature database of the implantation position can be constructed through the clinical experience of experts, and the corresponding structural threshold feature is matched through the structural feature of the implantation position. The structural threshold characteristics are preset structural threshold characteristics of the medical tube at the implantation position, and include a medical tube surface roughness threshold, a medical tube surface aperture size threshold, distribution position and arrangement mode information among components and the like.
S400: conveying the first medical tube to a first image acquisition module to obtain a first image acquisition result;
specifically, the first medical tube is transported to a first image capturing module, wherein the first image capturing module is an image capturing device, and wherein the first image capturing module is capable of capturing macroscopic features and microscopic molecular structures. And acquiring a final image acquisition result, namely a first image acquisition result, wherein the first image acquisition result comprises a macroscopic image acquisition result and a microscopic image acquisition result. The first image acquisition module is used for acquiring the image of the outer surface of the first medical tube to acquire a macro image and a micro image of the outer surface, wherein the macro image of the coating on the outer surface of the first medical tube is supposed to embody macro characteristics of the coating on the outer surface of the first medical tube, such as surface roughness of the medical tube, surface aperture size of the medical tube and other macro characteristics. The microscopic image of the coating on the outer surface of the first medical tube should represent the microscopic features of the coating on the outer surface of the first medical tube, such as the distribution position and arrangement of the components of the coating on the medical tube.
S500: performing feature extraction on the first image acquisition result to generate a first structural feature, wherein the first structural feature and the first structural threshold feature are in one-to-one correspondence;
specifically, the feature extraction is performed on the obtained first image acquisition result, and the macro-level feature embodied in the macro-image in the first image acquisition is extracted, where the macro-image is the acquisition result of the macro-level of the first medical tube acquired by the first image acquisition module, and the macro-level of the first medical tube may include information of the macro-level, such as the surface roughness of the medical tube, the surface aperture of the medical tube, and the like. And extracting microscopic level features embodied in the microscopic images in the first image acquisition, wherein the microscopic images are acquired by the first image acquisition module on a microscopic level of the first medical tube, and the microscopic level of the first medical tube can include information on the microscopic level such as distribution position and arrangement mode among components of a coating on the surface of the medical tube. The macro and micro features extracted in the above manner constitute a first structural feature together, and the first structural feature extracted by the first image acquisition result should correspond to the first structural threshold feature one to one. The first structural threshold characteristic is a structural characteristic of a predetermined medical tube surface matched by the implant location structural information, i.e., the first environmental characteristic information.
S600: determining whether the first structural feature satisfies the first structural threshold feature;
s700: and if so, obtaining a first structural quality inspection qualified instruction, and adding a first quality inspection result.
Specifically, whether the acquired structural characteristics of the outer surface of the medical tube coating meet preset structural characteristics, namely first structural threshold characteristics, of the medical tube surface matched by the implantation position structural information is judged. When judging whether the first structural feature meets the first structural threshold feature, the judgment can be carried out through the corresponding relation between the macroscopic features and the microscopic features of the first structural feature and the first structural threshold feature, firstly, whether the macroscopic feature in the first structural feature meets the macroscopic feature threshold value in the first structural threshold feature is judged, and when the macroscopic feature in the first structural feature meets the first structural threshold feature, whether the microscopic feature in the first structural feature meets the microscopic feature threshold value in the first structural threshold feature is further judged. If the macroscopic feature of the first structural feature does not satisfy the macroscopic feature threshold of the first structural threshold feature, the macroscopic feature of the outer surface of the medical tube coating may not satisfy the actual implantation environment, and a medical accident may be caused because the coating requirement may not satisfy the actual implantation environment. And when the macroscopic features and the microscopic features in the first structural features both meet the macroscopic feature threshold value in the first structural threshold feature, the medical tube coating quality is qualified, the requirements of various aspects of the actual implantation environment can be met, a first structural quality inspection qualified instruction is further obtained and used for indicating that the medical tube coating quality is qualified, and the first structural quality inspection qualified instruction is added into the first quality detection result to output a final detection result.
As shown in fig. 2, the method step S600 provided in the embodiment of the present application includes:
s610: acquiring a first macroscopic image acquisition result and a first microscopic image acquisition result according to the first image acquisition result;
s620: performing feature extraction on the first macroscopic image acquisition result to generate a first macroscopic structure feature;
s630: performing feature extraction on the first microscopic image acquisition result to generate a first microscopic structure feature;
s640: obtaining a first macro-structure threshold feature and a first micro-structure threshold feature according to the first structure threshold feature;
s650: determining whether the first macro-structure feature satisfies the first macro-structure threshold feature;
s660: and if so, judging whether the first microstructure characteristic meets the first microstructure threshold characteristic or not.
Specifically, macro and micro collected images are obtained according to the obtained first image collecting result, wherein the macro image of the outer surface coating of the first medical tube, that is, the first macro image collecting result, should embody macro characteristics of the outer surface coating of the first medical tube, such as macro characteristics of surface roughness of the medical tube, surface pore size of the medical tube, and the like. The microscopic image of the coating on the outer surface of the first medical tube, i.e. the first microscopic image acquisition result, should represent the microscopic features of the coating on the outer surface of the first medical tube, such as the distribution position and arrangement of the components of the coating of the medical tube. By extracting the features of the macro image acquisition result and the micro image acquisition result, the macro features in the macro image, such as the macro features of the surface roughness of the medical tube, the surface aperture size of the medical tube and the like, and the micro features in the micro image, such as the micro features of the distribution position, the arrangement mode and the like among the components of the medical tube coating are extracted. And then acquiring a first macro-structure threshold characteristic and a first micro-structure threshold characteristic according to the first structure threshold characteristic, wherein the first structure threshold characteristic comprises macro-structure and micro-structure threshold characteristics of the medical pipeline coating in the current implantation environment, and the first structure threshold characteristic and the first structure characteristic are in one-to-one correspondence, so that whether the first macro-structure characteristic and the first micro-structure characteristic in the first structure characteristic meet the requirement of the first structure threshold characteristic can be judged through the first structure threshold characteristic. And determining whether the macroscopic features of the appearance layer of the medical pipeline meet the macroscopic feature threshold requirements of the current implantation environment on the medical pipeline by judging whether the first macroscopic feature meets the first macroscopic structure threshold feature. And when the first microstructure threshold characteristic is met, further judging the first microstructure characteristic, and judging whether the first microstructure characteristic meets the first microstructure threshold characteristic. Judge first macrostructure characteristic and first microstructure characteristic in first structural feature through first structural threshold value characteristic, detect medical tube coating quality jointly from macroscopic and microcosmic angle, generate more accurate medical tube coating quality testing result, realized the technical effect to medical tube coating quality more accurate more comprehensive evaluation.
The method provided by the embodiment of the present application includes step S650:
s651: loading a first threshold matching channel to obtain a first macro structure threshold matching layer and a first microstructure threshold matching layer;
s652: after the first environmental characteristic information is input into the first threshold matching channel:
s653: inputting the first environmental characteristic information into the first macro structure threshold matching layer to obtain the first macro structure threshold characteristic;
s654: inputting the first environmental characteristic information into the first microstructure threshold matching layer to obtain the first microstructure threshold characteristic;
s655: adding the first macro-structure threshold feature and the first micro-structure threshold feature into the first structure threshold feature.
Specifically, the macro structure threshold matching layer and the microstructure threshold matching layer are obtained through the threshold matching channel and are used for conducting macro structure threshold matching and microstructure threshold matching according to structural feature information of the implantation portion. Wherein the macrostructure threshold match is used to match macrofeatures of the medical tube coating, the macrostructure threshold comprising macrofeatures of the medical tube coating such as surface roughness, particulate distribution density, pore size distribution uniformity, and the like. The microstructure threshold includes microscopic features such as microscopic components, distribution positions among components, pore sizes, arrangement modes and the like. The first environmental characteristic information is input into the first microstructure threshold matching layer, the first microstructure threshold characteristic corresponding to the first environmental characteristic information is matched, namely the microstructure threshold characteristic matched with the implantation information is matched, for example, when the artificial blood vessel is implanted, the artificial blood vessel needs to meet the requirement of physical and chemical properties stability, so that the microstructure characteristic needs to meet the threshold value of the physical and chemical properties stability, the first environmental characteristic information is input into the microstructure threshold matching layer to obtain the final first microstructure threshold characteristic, and the first microstructure threshold characteristic is a selected threshold value of the microstructure layer of the medical pipeline coating. First macro structure threshold features corresponding to the first environmental feature information are then matched by inputting the first environmental feature information into the first macro structure threshold matching layer. Illustratively, still taking the artificial blood vessel as an example, the macro level of the artificial blood vessel needs to be suitable for the mesh size, and the surface roughness cannot be too rough, so as to match the first environmental characteristic information with the suitable first macro structure threshold characteristic. The acquired first macro-structure threshold characteristic and the acquired first micro-structure threshold characteristic are added into the first structure threshold characteristic, so that the structure threshold characteristic of the medical pipeline coating is matched through the first environment characteristic information, and support is provided for subsequent judgment of the quality of the medical pipe coating.
Step S655 of the method provided in the embodiment of the present application includes:
s655-1: performing feature extraction on the first implantation environment to obtain first physiological feature information, wherein the first physiological feature information comprises first blood feature information and first chemical feature information;
s655-2: when the first structural quality inspection qualified instruction is obtained, conveying the first medical tube to a first XRD diffraction device to obtain first XRD diffraction pattern characteristics;
s655-3: activating a first biocompatible evaluation layer according to the first threshold matching channel;
s655-4: inputting the first blood characteristic information, the first chemical characteristic information, the first structural characteristic, and the first XRD diffraction pattern characteristic into the first biocompatibility assessment layer to obtain a first degree of compatibility;
s655-5: and when the first compatibility meets a first compatibility threshold, obtaining a first compatibility quality inspection qualified instruction, and adding the first compatibility quality inspection qualified instruction into the first quality inspection result.
Specifically, the first implantation environment is subjected to feature extraction, wherein the first implantation environment features comprise implantation environments such as implantation positions and implantation depths of medical tubes. The method comprises the steps of obtaining physiological characteristic information in a first implantation environment, and obtaining the physiological characteristic information in the first implantation environment, namely first physiological characteristic information through an implantation position, wherein the first physiological characteristic information comprises first blood characteristic information and first chemical characteristic information, the first blood characteristic information comprises platelet number, blood protein content, blood pressure and blood type characteristic information, and the first chemical characteristic information is information such as pH value and temperature of the implantation environment. When the first structure quality inspection qualification command is obtained, the medical tube coating structure is qualified, and then the first medical tube is conveyed to the first XRD diffraction device, and first XRD diffraction pattern characteristics are obtained, wherein the first XRD diffraction pattern characteristics are the pattern characteristics obtained when the first medical tube is conveyed to the first XRD diffraction device, diffraction peaks are obtained through the first XRD diffraction pattern characteristics to determine the component characteristics, the component types, the molecular weight and the like of the medical tube coating structure. Activating a first biocompatibility evaluating layer through a first threshold matching channel, wherein the first biocompatibility evaluating layer is used for evaluating whether the first medical tube coating XRD diffraction pattern characteristics can be applied to a first implantation environment, and judging whether the first blood characteristic information, the first chemical characteristic information, the obtained first medical tube coating XRD diffraction pattern characteristics and the obtained first structural characteristics in the first implantation environment are biocompatible, wherein the biocompatibility refers to that materials cause appropriate reactions at a specific part of a body, and a final compatibility, namely the first compatibility, is obtained. The first biocompatibility evaluation layer can be obtained through training of a neural network model, and the model is used for outputting the final compatibility. By artificially setting a compatibility threshold, when the first compatibility meets the first compatibility threshold, the compatibility of the medical tube coating in a human body is better, a compatibility quality inspection qualified instruction, namely the first compatibility quality inspection qualified instruction, is obtained, and the result is added to the first quality detection result. The quality of the medical tube coating is evaluated in multiple directions by evaluating the compatibility of the medical tube coating in a human body, so that the technical effect of more accurately and comprehensively evaluating the quality of the medical tube coating is realized.
Step S655-4 of the method provided in the embodiment of the present application includes:
s655-41: obtaining a first biocompatibility assessment index, wherein the first biocompatibility assessment index includes a chemical compatibility index and a blood compatibility index;
s655-42: constructing a first node network according to the chemical compatibility index and first historical experimental data;
s655-43: constructing a second node network according to the blood compatibility index and second historical experimental data;
s655-44: inputting the first chemical characteristic information, the first structural characteristic and the first XRD diffraction pattern characteristic into the first node network to generate a chemical compatibility degree;
s655-45: inputting the first blood characteristic information, the first structural characteristic and the first XRD diffraction pattern characteristic into the second node network to generate blood compatibility;
s655-46: adding the chemical compatibility and the blood compatibility into the first compatibility.
Specifically, a biocompatibility evaluation index is obtained, and the biocompatibility evaluation index includes a chemical compatibility index and a blood compatibility index, that is, the compatibility index is judged by the chemical compatibility index and the blood compatibility index. And training the neural network model by taking the chemical compatibility index and historical chemical compatibility experimental data, namely first historical experimental data, as input data to obtain the trained neural network model, namely a first node network, wherein the first node network is used for obtaining the chemical compatibility through chemical characteristic information, structural characteristics and XRD diffraction pattern characteristics. And training the neural network model by taking the blood compatibility index and historical blood compatibility degree experimental data, namely second historical experimental data, as input data to obtain the trained neural network model, namely a second node network, wherein the second node network is used for obtaining the blood compatibility degree through blood characteristic information, structural characteristics and XRD diffraction pattern characteristics. Inputting the first chemical characteristic information, the first structural characteristic and the first XRD diffraction pattern characteristic into a first node network to generate chemical compatibility, and inputting the first blood characteristic information, the second structural characteristic and the first XRD diffraction pattern characteristic into the first node network to generate blood compatibility. And adding the finally obtained blood compatibility and chemical compatibility into the first compatibility to finish the generation of the first compatibility.
As shown in fig. 3, step S700 of the method provided in the embodiment of the present application includes:
s710: performing feature extraction on the first implantation environment to obtain first biological feature information, wherein the first biological feature information comprises a strain type and a strain quantity;
s720: obtaining an antibacterial property index according to the first biocompatibility evaluation index;
s730: constructing a third node network according to the antibacterial property index and third history experimental data;
s740: obtaining first crystal phase structural feature information according to the first structural feature;
s750: obtaining first component characteristic information according to the first XRD diffraction pattern characteristic;
s760: inputting the first crystal phase structure characteristic information, the first component characteristic information and the first biological characteristic information into the third node network to obtain an antibacterial property evaluation result;
s770: adding the antibacterial property evaluation result into the first compatibility.
Specifically, feature extraction is performed on the implantation environment, and biological feature information of the implantation environment, namely first biological feature information, is obtained, wherein the first biological feature information includes a strain type and a strain number. And obtaining an antibacterial property index according to the biocompatibility evaluation index, training the antibacterial property index and experimental data of a historical antibacterial test, namely third history experimental data, as input data to a neural network model, and obtaining a trained neural network, namely a third node network, wherein the third node network is used for obtaining an antibacterial property evaluation result through biological characteristic information, namely strain type and strain quantity, component characteristics and crystal phase structure characteristic information characteristics. Obtaining first crystalline phase structural feature information based on the microstructure features of the first structural features, wherein the crystalline phase structural feature is a crystalline structural feature of the medical tube coating, and then obtaining first composition feature information, i.e., a composition of the medical tube coating, based on the first XRD diffraction pattern features. The first crystal phase structure characteristic information, the first component characteristic information and the first biological characteristic information are input into the third node network, a final antibacterial property evaluation result is obtained, and the generated antibacterial property evaluation mechanism is added into the first compatibility, so that the technical effect of more accurately and more comprehensively evaluating the quality of the medical tube coating is achieved.
Step S655-5 of the method provided in the embodiment of the present application includes:
s655-51: when the first compatibility quality inspection qualified instruction is obtained, a first safety inspection instruction is obtained;
s655-52: according to the first safety detection instruction, sampling and delivering the first medical tube to a preset position for biological safety detection to obtain first feedback information;
s655-53: and when the first feedback information has qualified detection information, obtaining a first biological safety detection qualified instruction, and adding the first quality detection result.
Specifically, when the command for evaluating the quality of the medical tube coating and obtaining the qualified compatibility quality inspection is obtained, the system already evaluates the quality of the medical tube coating in multiple aspects and meets the preset requirements, and at the moment, a first safety detection command is obtained and used for sampling and delivering the medical tube to a preset position for biological safety detection. Because the biological safety needs to be detected by a regular authoritative biological safety authentication mechanism, after the content is detected, the content is transmitted to a specified mechanism for detection, and the final feedback information, namely the first feedback information, is obtained. When the medical tube detection qualified information exists in the first feedback information, a first biological safety detection qualified instruction is obtained, and the first biological safety detection qualified instruction is added to a first quality detection result, so that the technical effect of more accurate and more comprehensive evaluation on the quality of the medical tube coating is realized.
In summary, the method provided by the embodiment of the present application determines the implantation environment information by acquiring the model number of the medical tube. And performing feature extraction on the implantation environment to generate first environment feature information. And matching the first structural threshold characteristic according to the first environmental characteristic information. The medical tube is subjected to image acquisition. The collected image features are extracted to generate first structural features of the medical tube. Determining whether the first structural feature satisfies the first structural threshold feature. The quality of the medical tube coating is evaluated from multiple aspects such as macroscopic microstructure, compatibility, antibacterial property and the like, and finally, a more accurate detection result of the quality of the medical tube coating is obtained. The technical problem that the quality of the medical tube coating cannot be accurately measured due to the fact that a medical tube coating quality detection method is lacked in the prior art is solved. The comprehensive and accurate quality detection result of the medical tube is generated, and the technical effect of evaluating the quality of the medical tube coating more accurately and comprehensively is realized.
Example two
Based on the same inventive concept as that of the method for detecting the coating quality of the medical tube in the previous embodiment, as shown in fig. 4, the present application provides a system for detecting the coating quality of the medical tube, the system being communicatively connected to an image capturing module, the system comprising:
a first obtaining unit 11, configured to obtain a model of a first medical tube, and determine first implantation environment information;
a first generating unit 12, configured to perform feature extraction on the first implantation environment to generate first environment feature information;
a first matching unit 13, configured to match a first structure threshold characteristic according to the first environmental characteristic information;
a second obtaining unit 14, configured to deliver the first medical tube to the first image capturing module, so as to obtain a first image capturing result;
the first processing unit 15 is configured to perform feature extraction on the first image acquisition result to generate a first structural feature, where the first structural feature and the first structural threshold feature are in one-to-one correspondence;
a first judging unit 16, configured to judge whether the first structural feature satisfies the first structural threshold feature;
and a third obtaining unit 17, configured to, if the first quality inspection result is satisfied, obtain a first structural quality inspection qualified instruction, and add the first quality inspection result to the first structural quality inspection qualified instruction.
Further, the system further comprises:
a fourth obtaining unit, configured to obtain a first macro image acquisition result and a first micro image acquisition result according to the first image acquisition result;
the second generation unit is used for extracting the characteristics of the first macroscopic image acquisition result to generate first macroscopic structure characteristics;
the third generation unit is used for performing feature extraction on the first microscopic image acquisition result to generate a first microscopic structure feature;
a fifth obtaining unit, configured to obtain a first macro-structure threshold feature and a first microstructure threshold feature according to the first structure threshold feature;
a second determining unit, configured to determine whether the first macro-structure feature satisfies the first macro-structure threshold feature;
and the third judging unit is used for judging whether the first microstructure characteristic meets the first microstructure threshold characteristic or not if the first microstructure characteristic meets the first microstructure threshold characteristic.
Further, the system further comprises:
a sixth obtaining unit, configured to load the first threshold matching channel, and obtain a first macro-structure threshold matching layer and a first microstructure threshold matching layer;
a second processing unit, configured to, after the first environmental feature information is input into the first threshold matching channel:
a seventh obtaining unit, configured to input the first environmental feature information into the first macro-structure threshold matching layer, and obtain the first macro-structure threshold feature;
an eighth obtaining unit, configured to input the first environmental characteristic information into the first microstructure threshold matching layer, and obtain the first microstructure threshold characteristic;
a third processing unit for adding the first macro-structure threshold feature and the first micro-structure threshold feature to the first structure threshold feature.
Further, the system is in communication with an XRD diffraction device, the system further comprising:
a ninth obtaining unit, configured to perform feature extraction on the first implantation environment, and obtain first physiological feature information, where the first physiological feature information includes first blood feature information and first chemical feature information;
a tenth obtaining unit configured to, when the first structural quality inspection approval instruction is obtained, convey the first medical tube to a first XRD diffraction device, and obtain a first XRD diffraction pattern characteristic;
a fourth processing unit for activating a first bio-compatibility evaluation layer according to the first threshold matching channel;
an eleventh obtaining unit, configured to input the first blood characteristic information, the first chemical characteristic information, the first structural characteristic, and the first XRD diffraction pattern characteristic into the first biocompatibility evaluation layer, so as to obtain a first compatibility degree;
and a twelfth obtaining unit, configured to obtain a first compatible quality inspection qualified instruction when the first compatibility satisfies a first compatibility threshold, and add the first compatible quality inspection qualified instruction to the first quality inspection result.
Further, the system further comprises:
a thirteenth obtaining unit configured to obtain a first biocompatibility evaluation index, wherein the first biocompatibility evaluation index includes a chemical compatibility index and a blood compatibility index;
the first construction unit is used for constructing a first node network according to the chemical compatibility index and first historical experimental data;
the second construction unit is used for constructing a second node network according to the blood compatibility index and second historical experimental data;
a fourth generating unit, configured to input the first chemical characteristic information, the first structural characteristic, and the first XRD diffraction pattern characteristic into the first node network, so as to generate a chemical compatibility degree;
a fifth generating unit, configured to input the first blood characteristic information, the first structural characteristic, and the first XRD diffraction pattern characteristic into the second node network, so as to generate a blood compatibility degree;
a fifth processing unit for adding the chemical compatibility and the blood compatibility to the first compatibility.
Further, the system further comprises:
a fourteenth obtaining unit, configured to perform feature extraction on the first implantation environment to obtain first biological feature information, where the first biological feature information includes a strain type and a strain number;
a fifteenth obtaining unit, configured to obtain an antibacterial property index according to the first biocompatibility evaluation index;
the third construction unit is used for constructing a third node network according to the antibacterial property index and third history experimental data;
a sixteenth obtaining unit configured to obtain first crystal phase structural feature information based on the first structural feature;
a seventeenth obtaining unit configured to obtain first component characteristic information according to the first XRD diffraction pattern characteristics;
an eighteenth obtaining unit, configured to input the first crystal phase structure feature information, the first component feature information, and the first biological feature information into the third node network, so as to obtain an antibacterial property evaluation result;
and the sixth processing unit is used for adding the antibacterial property evaluation result into the first compatibility.
Further, the system further comprises:
a nineteenth obtaining unit, configured to obtain a first security detection instruction when the first compatible quality inspection qualified instruction is obtained;
a twentieth obtaining unit, configured to, according to the first safety detection instruction, sample and deliver the first medical tube to a preset position for biosafety detection, so as to obtain first feedback information;
and the seventh processing unit is used for obtaining a first biological safety detection qualified instruction when the first feedback information has detection qualified information, and adding the first biological safety detection qualified instruction into the first quality detection result.
EXAMPLE III
Based on the same inventive concept as the medical tube coating quality detection method in the previous embodiment, the present application further provides a computer-readable storage medium having a computer program stored thereon, which when executed by a processor implements the method in the first embodiment.
Exemplary electronic device
The electronic device of the present application is described below with reference to fig. 5.
Based on the same inventive concept as the medical tube coating quality detection method in the previous embodiment, the present application also provides an electronic device, including: a processor and a memory, the processor coupled with the memory; the memory is used for storing programs, and the processor is used for executing the steps of the method in the embodiment one through calling.
The electronic device 300 includes: processor 302, communication interface 303, memory 301. Optionally, the electronic device 300 may also include a bus architecture 304. Wherein, the communication interface 303, the processor 302 and the memory 301 may be connected to each other through a bus architecture 304; the bus architecture 304 may be a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, or the like. The bus architecture 304 may be divided into an address bus, a data bus, a control bus, and the like. For ease of illustration, only one thick line is shown in FIG. 5, but that does not indicate only one bus or one type of bus.
The communication interface 303 is a system using any transceiver or the like, and is used for communicating with other devices or communication networks, such as ethernet, Radio Access Network (RAN), Wireless Local Area Network (WLAN), wired access network, and the like.
The memory 301 may be, but is not limited to, ROM or other type of static storage device that can store static information and instructions, RAM or other type of dynamic storage device that can store information and instructions, EEPROM, CD-ROM or other optical disk storage, optical disk storage (including compact disk, laser disk, optical disk, digital versatile disk, blu-ray disk, etc.), magnetic disk storage or other magnetic storage devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer. The memory may be self-contained and coupled to the processor through a bus architecture 304. The memory may also be integral to the processor.
The memory 301 is used for storing computer-executable instructions for executing the present application, and is controlled by the processor 302 to execute. The processor 302 is configured to execute the computer-executable instructions stored in the memory 301, so as to implement a method for detecting the coating quality of a medical tube according to the above-mentioned embodiment of the present application.
Those of ordinary skill in the art will understand that: the various numbers of the first, second, etc. mentioned in this application are for convenience of description and are not intended to limit the scope of this application nor to indicate the order of precedence. "and/or" describes the association relationship of the associated object, indicating that there may be three relationships, for example, a and/or B, which may indicate: a exists alone, A and B exist simultaneously, and B exists alone. The character "/" generally indicates that the former and latter associated objects are in an "or" relationship. "at least one" means one or more. At least two means two or more. "at least one," "any," or similar expressions refer to any combination of these items, including any combination of item(s) or item(s). For example, at least one (one ) of a, b, or c, may represent: a, b, c, a-b, a-c, b-c, or a-b-c, wherein a, b, c may be single or multiple.
In the above embodiments, the implementation may be wholly or partially realized by software, hardware, firmware, or any combination thereof. When implemented in software, it may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the processes or functions described in the present application are generated in whole or in part. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable system. The computer instructions may be stored in a computer readable storage medium or transmitted from one computer readable storage medium to another computer readable storage medium, for example, the computer instructions may be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, Digital Subscriber Line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device, including one or more integrated servers, data centers, and the like. The usable medium may be a magnetic medium (e.g., floppy Disk, hard Disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., Solid State Disk (SSD)), among others.
The various illustrative logical units and circuits described in this application may be implemented or operated through the design of a general purpose processor, a digital signal processor, an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other programmable logic system, discrete gate or transistor logic, discrete hardware components, or any combination thereof. A general-purpose processor may be a microprocessor, but in the alternative, the processor may be any conventional processor, controller, microcontroller, or state machine. A processor may also be implemented as a combination of computing systems, e.g., a digital signal processor and a microprocessor, a plurality of microprocessors, one or more microprocessors in conjunction with a digital signal processor core, or any other similar configuration.
The steps of a method or algorithm described in this application may be embodied directly in hardware, in a software element executed by a processor, or in a combination of the two. The software cells may be stored in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art. For example, a storage medium may be coupled to the processor such the processor can read information from, and write information to, the storage medium. In the alternative, the storage medium may be integral to the processor. The processor and the storage medium may reside in an ASIC, which may be disposed in a terminal. In the alternative, the processor and the storage medium may reside in different components within the terminal. These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Although the present application has been described in conjunction with specific features and embodiments thereof, it will be evident that various modifications and combinations can be made thereto without departing from the spirit and scope of the application. Accordingly, the specification and figures are merely exemplary of the application and are intended to cover any and all modifications, variations, combinations, or equivalents within the scope of the application. It will be apparent to those skilled in the art that various changes and modifications may be made in the present application without departing from the scope of the application. Thus, if such modifications and variations of the present application fall within the scope of the present application and its equivalent technology, it is intended that the present application include such modifications and variations.
Claims (9)
1. A medical tube coating quality detection method, wherein the method is applied to a medical tube coating quality detection system, the system is in communication with an image acquisition module, and the method comprises the following steps:
obtaining the model of a first medical tube, and determining first implantation environment information;
performing feature extraction on the first implantation environment to generate first environment feature information;
matching a first structure threshold characteristic according to the first environment characteristic information;
conveying the first medical tube to a first image acquisition module to obtain a first image acquisition result;
performing feature extraction on the first image acquisition result to generate a first structural feature, wherein the first structural feature and the first structural threshold feature are in one-to-one correspondence;
determining whether the first structural feature satisfies the first structural threshold feature;
if so, obtaining a first structural quality inspection qualified instruction, and adding a first quality inspection result;
the determining whether the first structural feature satisfies the first structural threshold feature comprises:
acquiring a first macroscopic image acquisition result and a first microscopic image acquisition result according to the first image acquisition result;
performing feature extraction on the first macroscopic image acquisition result to generate a first macroscopic structure feature;
performing feature extraction on the first microscopic image acquisition result to generate a first microscopic structure feature;
obtaining a first macro-structure threshold feature and a first micro-structure threshold feature according to the first structure threshold feature;
determining whether the first macro-structure feature satisfies the first macro-structure threshold feature;
and if so, judging whether the first microstructure characteristic meets the first microstructure threshold characteristic.
2. The method of claim 1, wherein said matching a first structural threshold feature based on said first environmental feature information comprises:
loading a first threshold matching channel to obtain a first macro structure threshold matching layer and a first microstructure threshold matching layer;
after the first environmental characteristic information is input into the first threshold matching channel:
inputting the first environmental characteristic information into the first macro structure threshold matching layer to obtain the first macro structure threshold characteristic;
inputting the first environmental characteristic information into the first microstructure threshold matching layer to obtain the first microstructure threshold characteristic;
adding the first macro-structure threshold feature and the first micro-structure threshold feature to the first structure threshold feature.
3. The method of claim 2, wherein the method is applied to a medical tube coating quality inspection system, the system further communicatively coupled to an XRD diffraction device, the method further comprising:
performing feature extraction on the first implantation environment to obtain first physiological feature information, wherein the first physiological feature information comprises first blood feature information and first chemical feature information;
when the first structural quality inspection qualified instruction is obtained, conveying the first medical tube to a first XRD diffraction device to obtain first XRD diffraction pattern characteristics;
activating a first biocompatible evaluation layer according to the first threshold matching channel;
inputting the first blood characteristic information, the first chemical characteristic information, the first structural characteristic, and the first XRD diffraction pattern characteristic into the first biocompatibility assessment layer to obtain a first degree of compatibility;
and when the first compatibility meets a first compatibility threshold, obtaining a first compatibility quality inspection qualified command, and adding the first compatibility quality inspection qualified command into the first quality inspection result.
4. The method of claim 3, wherein the method further comprises:
obtaining a first biocompatibility assessment index, wherein the first biocompatibility assessment index includes a chemical compatibility index and a blood compatibility index;
constructing a first node network according to the chemical compatibility index and first historical experimental data;
constructing a second node network according to the blood compatibility index and second historical experimental data;
inputting said first chemical characteristic information, said first structural characteristic, and said first XRD diffraction pattern characteristic into said first nodal network, generating chemical compatibility;
inputting said first blood characteristic information, said first structural characteristic, and said first XRD diffraction pattern characteristic into said second nodal network, generating blood compatibility measures;
adding the chemical compatibility and the blood compatibility into the first compatibility.
5. The method of claim 4, wherein the method further comprises:
performing feature extraction on the first implantation environment to obtain first biological feature information, wherein the first biological feature information comprises a strain type and a strain quantity;
obtaining an antibacterial property index according to the first biocompatibility evaluation index;
constructing a third node network according to the antibacterial property index and third history experimental data;
obtaining first crystalline phase structural characteristic information according to the first structural characteristics;
obtaining first component characteristic information according to the first XRD diffraction pattern characteristic;
inputting the first crystal phase structure characteristic information, the first component characteristic information and the first biological characteristic information into the third node network to obtain an antibacterial property evaluation result;
adding the antibacterial property evaluation result into the first compatibility.
6. The method of claim 5, wherein the method further comprises:
when the first compatibility quality inspection qualified instruction is obtained, a first safety inspection instruction is obtained;
according to the first safety detection instruction, sampling and delivering the first medical tube to a preset position for biological safety detection to obtain first feedback information;
and when the first feedback information has qualified detection information, obtaining a first biological safety detection qualified instruction, and adding the first quality detection result.
7. A medical tube coating quality detection system, the system communicatively coupled to an image acquisition module, the system comprising:
a first obtaining unit, configured to obtain a model of a first medical tube, and determine first implantation environment information;
the first generation unit is used for extracting the characteristics of the first implantation environment and generating first environment characteristic information;
a first matching unit, configured to match a first structure threshold characteristic according to the first environmental characteristic information;
the second obtaining unit is used for conveying the first medical tube to the first image acquisition module to obtain a first image acquisition result;
the first processing unit is used for performing feature extraction on the first image acquisition result to generate a first structural feature, wherein the first structural feature and the first structural threshold feature are in one-to-one correspondence;
a first judging unit configured to judge whether the first structural feature satisfies the first structural threshold feature;
a third obtaining unit, configured to obtain a first structural quality inspection qualified instruction if the first structural quality inspection qualified instruction is met, and add the first quality inspection result to the first obtaining unit;
a fourth obtaining unit, configured to obtain a first macro image acquisition result and a first micro image acquisition result according to the first image acquisition result;
the second generation unit is used for extracting the characteristics of the first macroscopic image acquisition result to generate first macroscopic structure characteristics;
the third generation unit is used for performing feature extraction on the first microscopic image acquisition result to generate a first microscopic structure feature;
a fifth obtaining unit, configured to obtain a first macro-structure threshold feature and a first microstructure threshold feature according to the first structure threshold feature;
a second determining unit, configured to determine whether the first macro-structure feature satisfies the first macro-structure threshold feature;
and the third judging unit is used for judging whether the first microstructure characteristic meets the first microstructure threshold characteristic or not if the first microstructure characteristic meets the first microstructure threshold characteristic.
8. An electronic device, comprising: a processor coupled with a memory, the memory for storing a program that, when executed by the processor, causes a system to perform the method of any of claims 1-6.
9. A computer-readable storage medium, characterized in that the storage medium has stored thereon a computer program which, when being executed by a processor, carries out the method of any one of claims 1-6.
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| CN111444617A (en) * | 2020-03-27 | 2020-07-24 | 贵州中医药大学第一附属医院 | Coating quality online prediction method, system and computer readable storage medium |
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