Detection method and system of orthokeratology lens

Abstract

The invention relates to the technical field of lens detection, and discloses a detection method and system of an orthokeratology lens, the orthokeratology lens is cleaned, the cleaned orthokeratology lens is subjected to light visual data acquisition to obtain first detection data, the orthokeratology lens is analyzed according to the first detection data, and a detection result is obtained; the method comprises the following steps: generating preliminary detection information, cleaning guide information and detection guide information, cleaning an orthokeratology lens according to the cleaning guide information, acquiring subsequent detection information based on the detection guide information, and performing information correction on the preliminary detection information based on the subsequent detection information to obtain complete detection information of the orthokeratology lens.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of lens detection, and in particular to a detection method and system for orthokeratology lenses. BACKGROUND

[0002] In recent years, the incidence of myopia has been on the rise globally, especially among young people. Orthokeratology lenses have gained popularity among many myopic patients and their parents because they can temporarily change the shape of the cornea when worn at night, allowing clear vision during the day without the need for glasses, and also helping to control the growth of myopia to some extent. The number of users is increasing. Orthokeratology lenses may have some potential defects during production, transportation or use, such as scratches, cracks and deformation. These defects are not obvious at the beginning and are not easily detected by users, but they will gradually worsen over time, affecting the effectiveness and safety of the lenses. Traditional visual observation methods are not effective in detecting subtle defects, and more professional detection methods are needed. SUMMARY

[0003] The present application aims to provide a detection method and system for orthokeratology lenses to address the problem of subtle defects being difficult to detect using visual observation methods in the prior art.

[0004] The present application is implemented as follows. In a first aspect, the present application provides a detection method for orthokeratology lenses, comprising: cleaning the orthokeratology lenses and collecting visual data of light rays from the cleaned orthokeratology lenses to obtain first detection data; analyzing the orthokeratology lenses based on the first detection data to generate preliminary detection information, cleaning guidance information and detection guidance information; cleaning the orthokeratology lenses based on the cleaning guidance information and collecting subsequent detection information based on the detection guidance information; modifying the preliminary detection information based on the subsequent detection information to obtain complete detection information for the orthokeratology lenses.

[0005] In a second aspect, the present application provides a detection system for orthokeratology lenses for implementing the detection method of any one of the first aspect, comprising: a visual detection module for cleaning the orthokeratology lenses and collecting visual data of light rays from the cleaned orthokeratology lenses to obtain first detection data; a detection analysis module for analyzing the orthokeratology lenses based on the first detection data to generate preliminary detection information, cleaning guidance information and detection guidance information; a subsequent detection module configured to clean the orthokeratology lens according to the cleaning guide information and collect subsequent detection information based on the detection guide information; an information correction module configured to correct the preliminary detection information based on the subsequent detection information to obtain complete detection information of the orthokeratology lens.

[0006] The present application provides a detection method for an orthokeratology lens, which has the following advantages: The present application can preliminarily understand the lens condition through cleaning and data collection, generate various guide information according to the first detection data, clean and accurately detect again, correct the preliminary result according to the second detection information, obtain complete detection information, more accurately judge the lens quality, effectively distinguish dirt and potential defects, provide scientific lens maintenance and use suggestions for users according to the complete information, improve the wearing safety and comfort, and prolong the service life of the lens, which solves the problem that some subtle defects are difficult to be found by naked eye observation in the prior art. BRIEF DESCRIPTION OF DRAWINGS

[0007] Figure 1 is a step schematic diagram of a detection method for an orthokeratology lens provided by an embodiment of the present application; Figure 2 is a structural schematic diagram of a detection system for an orthokeratology lens provided by an embodiment of the present application. DETAILED DESCRIPTION

[0008] In order to make the purpose, technical scheme and advantages of the present application clearer, the present application is further described in detail below in combination with the drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and do not limit the present application.

[0009] The implementation of the present application is described in detail below in combination with specific embodiments.

[0010] Referring to Figure 1 , Figure 2 , a preferred embodiment of the present application is provided.

[0011] In a first aspect, the present application provides a detection method for an orthokeratology lens, comprising: S1: cleaning an orthokeratology lens and collecting light visual data of the cleaned orthokeratology lens to obtain first detection data; S2: analyzing the orthokeratology lens according to the first detection data to generate preliminary detection information, cleaning guide information, and detection guide information; S3: cleaning the orthokeratology lens according to the cleaning guide information and collecting subsequent detection information based on the detection guide information; S4: information correction is performed on the preliminary detection information based on the subsequent detection information to obtain complete detection information of the orthokeratology lens.

[0012] Specifically, in step S1 of the embodiments provided in the present application, the execution mode of the cleaning process includes manual processing and automatic processing using a designated cleaning device. Manual processing usually refers to the user using cleaning liquid, care liquid, and cooperating with fingers or special tools (such as lens cleaning rods) to rub, rinse, and other operations on the lens. Automatic processing refers to placing the lens into a designated cleaning device (such as a device with ultrasonic cleaning function) and completing the cleaning according to a preset program by the device. According to the selected cleaning mode, the orthokeratology lens is cleaned according to the corresponding operation specification. If it is manual cleaning, attention should be paid to moderate intensity to avoid scratching the lens. If an automatic cleaning device is used, it is necessary to ensure that the device is running normally and the cleaning parameters are set correctly.

[0013] More specifically, the orthokeratology lens will adsorb proteins, lipids and other substances in the tear fluid, as well as dust, microorganisms and other pollutants in the external environment during daily use. These pollutants will affect the optical performance and wearing comfort of the lens, and may also breed bacteria, posing a threat to eye health. Through cleaning, these pollutants can be effectively removed to ensure the cleanliness of the lens. The presence of pollutants will interfere with the collection of light visual data, resulting in inaccurate data collected, thereby affecting the subsequent analysis and judgment of the lens quality condition. The cleaned lens surface is cleaner and can more truly reflect its own optical properties and surface condition, improving the accuracy of detection.

[0014] More specifically, a handheld detection device or a fixed detection device can be used. The handheld detection device is convenient to carry and flexible to operate, and is suitable for use in different scenarios. The fixed detection device usually has a more stable detection environment and higher detection precision. It has a special detection site for placing the orthokeratology lens. If a fixed detection device is used, the cleaned orthokeratology lens is placed on the detection site. If a handheld detection device is used, the lens needs to be adjusted to a suitable position for data collection. The optical visual data of the orthokeratology lens is obtained, and the spatial positioning information of the lens is analyzed based on these data through a specific algorithm to determine the position and attitude of the lens in three-dimensional space. According to the spatial positioning information, the detection area of the orthokeratology lens is divided and spatially positioned. The lens surface is divided into multiple detection areas, and the area positioning information of each detection area is generated to clearly determine the specific position of each area.

[0015] More specifically, each detection area is taken as a detection object respectively, and according to the area positioning information, the detection object and the adjacent range are respectively subjected to light irradiation of a specified specification, so that the detection object is in a light irradiation environment with light irradiation area distinction from the adjacent range, so as to more clearly observe and collect the characteristics of the lens surface. The corneal molding lens is in a specified light irradiation environment, and optical visual data collection is performed using a detection device to obtain first detection data. These data can include information such as reflected light and transmitted light of the lens surface, reflecting the optical characteristics and surface condition of the lens.

[0016] More specifically, the light visual data contains various characteristic information of the corneal molding lens, such as surface flatness, scratches, deposits, etc. By collecting these data, the quality condition of the lens can be comprehensively understood, providing basic data for subsequent analysis and detection. The first detection data as initial data will be compared and analyzed with the subsequently collected detection information. Through comparison of data at different stages, changes in the quality of the lens can be found in time, and it can be judged whether the lens has potential defects or quality problems. By applying specific light to the corneal molding lens, the contrast and clarity of the lens surface features can be enhanced, making it easier for the detection device to capture subtle defects and changes. The detection area is divided and positioned, and different specifications of light irradiation are applied to each area, which can more targetedly collect data and improve the sensitivity and accuracy of detection.

[0017] Specifically, in step S2 of the embodiments provided in the present application, historical detection records of the corneal molding lens to be detected are retrieved from the detection device for performing optical visual data collection. These historical records contain the detection data and detection results of the lens in the past. The historical detection records are an important reference for the quality change of the corneal molding lens. By retrieving the historical records, the past quality condition of the lens, the problems that have occurred and the development trend of the problems can be understood, which helps to more accurately evaluate the current state of the lens in this detection and improve the reliability of the detection results. For example, if the historical records show that a certain area of the lens often has a deposit problem, more attention will be paid to this area in this detection, and the judgment of the analysis result will be more accurate.

[0018] More specifically, the corneal molding lens is analyzed for potential defects based on the first detection data, such as checking whether there are scratches, cracks, deposits, etc. on the lens surface. The confidence of the above analysis result is evaluated based on the historical detection records. The historical detection records can reflect the quality change trend and common problems of the lens. By comparing the current analysis result with the historical situation, the reliability of the current detection result can be judged. The results of potential defect analysis and confidence evaluation are combined to generate preliminary detection information composed of several area detection characteristics for the corneal molding lens. These area detection characteristics describe the quality condition of different areas of the lens.

[0019] More specifically, by performing potential defect analysis on the first detection data, the current quality status of the orthokeratology lens can be comprehensively understood, and possible problems can be found out. The confidence evaluation, combined with historical detection records, can quantitatively evaluate the reliability of the analysis results, which helps to avoid false judgments caused by errors or uncertainties of single detection data, and improves the accuracy of preliminary detection information.

[0020] More specifically, the preliminary detection information in each region is subjected to prediction analysis of dirt that is not cleaned. By analyzing some abnormal features of the lens surface in the first detection data, it is determined whether these features are caused by potential defects or not cleaned dirt, and dirt probability features corresponding to each region detection feature are obtained. Based on the analysis of each dirt probability feature, cleaning guidance information is obtained. If the dirt probability of a certain region is high, it is recommended to strengthen the cleaning of that region or use a specific cleaning method.

[0021] More specifically, the dirt probability of different regions is different, indicating that there are differences in the cleaning status of each part of the lens. By generating cleaning guidance information, personalized cleaning recommendations can be provided for different regions, improving the cleaning effect. For example, if the dirt probability of a certain region is high, the user can clean that region more carefully, thereby better maintaining the cleanliness of the lens. Reasonable cleaning guidance information can avoid excessive cleaning or insufficient cleaning of the lens. Excessive cleaning may damage the lens, while insufficient cleaning may not effectively remove contaminants, affecting the use effect and safety of the lens.

[0022] More specifically, the optical visual performance of the orthokeratology lens after cleaning according to the cleaning guidance information is predicted. Considering different cleaning methods and cleaning effects, several possible optical visual performance forms are obtained. Based on various possible optical visual performance forms, detection effectiveness analysis of various optical visual detection forms is performed. The optical visual detection forms include the lighting environment in which the orthokeratology lens is located, and the orientation and angle of optical visual data collection, etc. By analyzing the effectiveness of different detection forms under various possible optical visual performances, detection guidance information is obtained.

[0023] More specifically, different optical visual performance forms require different detection methods to more accurately detect lens problems. By performing detection effectiveness analysis on various possible optical visual performance forms, the best detection form can be provided for subsequent detection, such as appropriate lighting environment, collection orientation and angle, etc., thereby improving the accuracy and efficiency of detection. The optical visual performance of the cleaned lens will change, and the detection guidance information can ensure that the quality status of the lens can still be accurately detected after cleaning, and potential problems can be found out in a timely manner.

[0024] Specifically, in step S3 of the embodiments provided by the present application, the cleaning guidance information indicates whether to use manual processing or automatic processing of the designated cleaning equipment. If manual processing is used, the necessary items for cleaning, such as cleaning solution, care solution, and special lens cleaning rod, need to be prepared. If automatic processing is used, the lens needs to be placed in the designated cleaning equipment.

[0025] More specifically, manual cleaning includes using fingers or a cleaning rod to dip an appropriate amount of cleaning solution and gently rub the surface of the orthokeratology lens according to the operation instructions in the cleaning guidance for manual processing, with special attention to areas with a high probability of contamination detected in the preliminary detection. Then, the lens is rinsed clean with a care solution. Automatic cleaning includes placing the lens in the designated position of the cleaning equipment, starting the equipment, and letting it complete the cleaning process according to the preset program. Different cleaning equipment has different operation procedures, and needs to be operated strictly according to the usage instructions and cleaning guidance information of the equipment.

[0026] More specifically, the cleaning guidance information is generated based on the preliminary detection results, analyzes and predicts the possible contamination that has not been cleaned on the lens, and can more targetedly remove these contaminants, improve the cleanliness of the lens, and reduce the impact of contaminants on the optical performance and wearing comfort of the lens.

[0027] More specifically, the detection guidance information includes the lighting environment in which the orthokeratology lens should be placed, the orientation and angle of optical vision data collection, and other content. According to this information, the lighting parameters of the detection equipment, such as lighting intensity and lighting angle, are adjusted to create a specified lighting environment. At the same time, the orientation and angle of the detection equipment relative to the lens when collecting data are determined. The cleaned orthokeratology lens is placed in the appropriate position of the detection equipment to ensure that it is in an ideal detection state. If a fixed detection equipment is used, the lens is accurately placed on the detection position. If a handheld detection equipment is used, the lens and equipment need to be held steadily to meet the requirements of the collection orientation and angle. Under the condition of meeting the detection conditions, the detection equipment is used to collect optical vision data of the orthokeratology lens to obtain subsequent detection information. During the collection process, the stability and accuracy of data collection need to be ensured to avoid data distortion caused by shaking or other factors.

[0028] More specifically, by collecting subsequent detection information according to the detection guide information, the cleaned lens can be detected under unified and standardized detection conditions, which can accurately determine whether the cleaning operation is effective, whether the suspected stains found in the preliminary detection are removed, and whether the potential defects of the lens still exist or have new changes. The detection guide information specifies specific lighting environments, collection orientations and angles, and other detection conditions, so that the subsequent detection information is comparable to the first detection data. Data collection is performed under the same detection conditions, which facilitates comparative analysis of the two detection results, thereby more accurately identifying changes in the quality of the lens, and providing a reliable basis for subsequent information correction and generation of complete detection information.

[0029] Specifically, in step S4 of the embodiments provided by the present application, the subsequent detection information is compared in detail with the preliminary detection information, and the differences between the two are analyzed. For example, whether the optical visual performance of the same area of the lens in the two detections is different, such as changes in brightness, contrast, texture, etc. Based on the results of the difference analysis, the preliminary detection information is divided, and those parts of the preliminary detection information that disappear or significantly improve in the subsequent detection are confirmed as uncleaned stain parts; and those parts that still exist or have new changes in the subsequent detection are divided into suspected defect parts.

[0030] More specifically, in the preliminary detection, it is difficult to accurately distinguish whether the condition of the lens surface is caused by uncleaned stains or real potential defects. By comparing the subsequent detection information and the preliminary detection information, the two can be distinguished according to the changes before and after cleaning, which helps to more accurately understand the actual quality problems of the lens, avoids misjudging stains as potential defects, or ignoring real potential defects, divides the preliminary detection information into stain parts and defect parts, lays a foundation for further analysis of potential defects, and can concentrate on further identification and evaluation of defect parts, improving the efficiency and accuracy of analysis.

[0031] More specifically, the information part in the subsequent detection information that has consistent relative positioning with the defect part is retrieved, that is, the information corresponding to the position of the defect part divided in the preliminary detection in the subsequent detection is found. The detailed data of the corresponding position in the subsequent detection information is used to identify the defect properties (such as scratches, cracks, bubbles, etc.) and defect amplitudes (such as the size and depth of the defect, etc.) of the defect part. By analyzing the characteristics of the optical visual data and combining relevant identification algorithms or experience judgments, the specific properties and severity of the defect are determined.

[0032] More specifically, it is not enough to only know that the lens has potential defects, but also to understand the specific nature and severity of these defects. By retrieving information about the corresponding positions in the subsequent detection information and conducting detailed analysis, the nature and amplitude of the defects can be accurately identified, which is of great significance for determining whether the lens can continue to be used safely, whether it needs to be repaired or replaced, etc. Accurate defect identification features can provide detailed information about the quality status of the lens.

[0033] More specifically, the identified information consisting of several defect identification features is integrated to form complete detection information of the orthokeratology lens, which describes the specific situation of potential defects on the lens in detail, including the position, nature, amplitude, etc. of the defects, providing an accurate basis for comprehensive evaluation of the quality status of the lens. The complete detection information integrates all detailed information about the potential defects of the lens, which can comprehensively and accurately reflect the quality status of the orthokeratology lens. Compared with the preliminary detection information, it removes the interference of dirt and focuses more on the real problems of the lens, providing a reliable basis for the quality evaluation and management of the lens. The complete detection information provides strong support for subsequent decision-making.

[0034] The present application provides a detection method for orthokeratology lenses, which has the following beneficial effects: YYY.

[0035] Preferably, the execution mode of the cleaning process for the orthokeratology lens includes manual processing and automatic processing using designated cleaning equipment, and the cleaning guide information includes operation instructions for manual processing or automatic processing.

[0036] Specifically, manual processing is that the user uses cleaning liquid, care liquid, and fingers or special tools (such as lens cleaning rods) to rub, rinse, etc. the lens. For example, place the lens in the palm, drop a few drops of cleaning liquid, gently rub the two sides of the lens with fingers, then rinse with care liquid. The user can clean the dirty areas on the lens according to his own feelings and observations, which can better handle some local stubborn stains, does not need to purchase additional complex cleaning equipment, and only needs to use common cleaning liquid and care liquid, thereby reducing the cleaning cost. The effect of manual cleaning depends largely on the user's operation skills and seriousness. If the operation is improper, such as excessive force which can scratch the lens, or incomplete cleaning which cannot effectively remove stains.

[0037] More specifically, the automatic processing is to put the lens into a designated cleaning device (such as a device with ultrasonic cleaning function), and the device completes the cleaning according to the preset program. The device usually uses high-frequency vibration of ultrasonic waves, spraying and other technologies to clean the lens comprehensively. The cleaning device operates according to the preset program and parameters, which can ensure the relative stability of the cleaning effect each time, reduce the influence of human factors, and the user only needs to put the lens into the device and start the switch, and the device will automatically complete the cleaning process without manual operation. It needs to purchase a designated cleaning device, which requires a certain cost, and the device needs to be regularly maintained and maintained, which increases the use cost.

[0038] More specifically, the cleaning guide information includes operation instructions for manual processing or automatic processing. These instructions will give specific operation suggestions for different cleaning methods according to the preliminary detection results of the lens. For example, for manual cleaning, it is suggested to increase the rubbing time and intensity in a certain area; for automatic cleaning, the cleaning mode and time of the device are specified. By providing specific operation instructions, users can more effectively clean the lens to ensure that the lens can effectively remove stains and improve the cleanliness of the lens. Reasonable operation instructions can avoid damage to the lens caused by improper cleaning operation and prolong the service life of the lens. For users who are not familiar with lens cleaning, cleaning guide information can provide clear guidance to reduce the difficulty of cleaning and make it more convenient for users to maintain the lens daily. This technology feature of dividing the cleaning method into manual and automatic and providing corresponding cleaning guide information fully considers the needs and actual situation of different users, aiming to provide a more efficient, convenient and safe solution for the cleaning of orthokeratology lenses.

[0039] Preferably, the execution mode of collecting light visual data of the cleaned orthokeratology lens adopts a handheld detection device or a fixed detection device. The fixed detection device has a detection position for placing the orthokeratology lens for the fixed detection device to collect optical visual data of the orthokeratology lens. The detection device stores historical detection records of the orthokeratology lens to be detected.

[0040] Specifically, the handheld detection device has portability and flexibility, which is convenient for users to detect orthokeratology lenses at any time in different scenarios. Users can freely adjust the position and angle of detection according to actual needs to check each part of the lens in detail, which is suitable for users to perform simple preliminary detection in daily life, such as at home or when going out, to timely understand the general condition of the lens. Due to the instability of handheld operation, it may affect the accuracy and consistency of data collection, and its function and precision are relatively weaker than the fixed detection device.

[0041] More specifically, the fixed detection device usually has a more stable detection environment and higher detection accuracy, and its structure design is more professional, which can provide more accurate light irradiation and data acquisition conditions, reduce the interference of external factors, and is suitable for professional ophthalmic institutions, lens detection centers and other places for more accurate and comprehensive detection. These places have higher requirements for the accuracy of detection results, and the fixed detection device can meet their needs. The device is relatively large in size and is not convenient to carry, and the use scene is relatively fixed.

[0042] More specifically, the detection site is a position specially designed for placing the orthokeratology lens by the fixed detection device. It can ensure that the lens maintains a stable position and posture during the detection process, so that the device can accurately collect optical visual data of the lens. By reasonably designing the shape, size and material of the detection site, the friction and damage between the lens and the detection site can be reduced, while ensuring that the lens is in the best detection position and improving the quality of data collection.

[0043] More specifically, the historical detection record contains the detection data and detection results of the orthokeratology lens to be detected in the past. These data can reflect the quality status of the lens at different time points, such as whether there are scratches, deposits and other problems, and the development trend of the problems. When performing current detection, the historical detection record can be referred to, and the changes of the lens before and after can be compared to more accurately judge the current state of the lens. For example, if the historical record shows that the lens has a slight scratch in a certain area, and this time detection finds that the scratch in that area has a tendency to worsen, appropriate measures can be taken in time.

[0044] More specifically, through the analysis of the historical detection record, the overall quality status and service life of the lens can be evaluated. If the lens frequently has problems in multiple detections, it means that the quality of the lens has hidden dangers, and the lens needs to be replaced. For users, the historical detection record can provide personalized lens use and maintenance suggestions for them. According to the historical situation of the lens, a more suitable care plan can be developed for the user to prolong the service life of the lens.

[0045] Preferably, the step of collecting optical visual data of the orthokeratology lens comprises: applying irradiation of ambient light to the orthokeratology lens so that the orthokeratology lens is in a specified form of light environment, and collecting optical visual data of the orthokeratology lens in the light environment; wherein the step of applying irradiation of ambient light to the orthokeratology lens comprises: obtaining optical visual data of the orthokeratology lens, and analyzing the spatial positioning information of the orthokeratology lens based on the optical visual data; According to the spatial positioning information, the detection area of the orthokeratology lens is divided and spatially positioned to generate the area positioning information of each detection area on the orthokeratology lens. According to the area positioning information, the detection object and the adjacent range are respectively subjected to light irradiation of a specified specification, so that the detection object is in a light irradiation environment with light irradiation degree differentiation from the adjacent range.

[0046] Specifically, the orthokeratology lens is subjected to preliminary optical visual data acquisition using a detection device (such as a handheld or fixed detection device). These data can be information such as the intensity, color, and texture of the reflected light and transmitted light of the lens surface. During the acquisition process, a camera, a sensor, or other devices can be used. Based on the acquired optical visual data, specific algorithms and models are used for analysis to determine the spatial positioning information of the orthokeratology lens in three-dimensional space, such as the spatial coordinates and angles by identifying the edges and feature points of the lens through image recognition technology.

[0047] More specifically, accurate spatial positioning information is the basis for subsequent detection area division and light irradiation. Only when the specific position and attitude of the lens in space are known, can accurate detection and analysis of each part of the lens be ensured, and deviation in the detection results caused by inaccurate positioning can be avoided. Different orthokeratology lenses may have different position and attitude changes during wearing and use. By obtaining real-time spatial positioning information, personalized detection can be performed for each lens to improve the accuracy and pertinence of the detection.

[0048] More specifically, according to the structural characteristics and detection requirements of the orthokeratology lens, the lens surface is divided into multiple detection areas in combination with the obtained spatial positioning information. Common division methods can be based on the concentric areas (such as the central area, the para-central area, and the peripheral area) or the functional areas (such as the optical area and the positioning area) of the lens. The specific position and range of each detection area in the lens space are determined to generate the area positioning information of each detection area. These information can be described by parameters such as coordinates, angles, and radii to accurately position each detection area.

[0049] More specifically, different areas of the orthokeratology lens have different functions and quality requirements. Dividing the lens into multiple detection areas can allow more detailed and in-depth detection of each area. For example, the central optical area has a greater impact on vision correction and requires more accurate detection. The peripheral positioning area mainly focuses on its fit with the cornea. After the lens is divided into multiple detection areas, the detection data of each area can be independently analyzed and processed, which can more clearly understand the quality status of each part of the lens and facilitate the discovery of local problems and defects.

[0050] More specifically, each divided detection area is taken as an independent detection object, and according to the area positioning information of each detection area, a specified specification of light irradiation is applied to each detection object and its adjacent range, including the intensity, color, irradiation angle and other parameters of the light. By adjusting these parameters, the detection object is placed in a lighting environment with obvious light differentiation from the adjacent range. For example, for a certain detection area, a stronger light can be used to irradiate from a specific angle, while the adjacent range is irradiated with weaker light, thereby highlighting the features of the detection area.

[0051] More specifically, placing the detection object in a lighting environment with light differentiation from the adjacent range can enhance the contrast and clarity of the lens surface features. For example, under different lighting conditions, defects such as scratches and deposits on the lens surface will be more obviously visible, facilitating the detection equipment to accurately capture these features and improve the sensitivity and accuracy of the detection. By adjusting the irradiation angle and intensity of the light, the influence of interference factors such as reflected light and scattered light on the lens surface can be reduced. At the same time, using different lighting specifications for the detection object and the adjacent range can effectively distinguish the information of different areas and avoid mutual interference.

[0052] More specifically, in the specified form of the corneal molding lens in the lighting environment, the detection equipment is used to perform formal optical visual data collection, and the collected data will be used for subsequent analysis and evaluation of the lens quality. The collected optical visual data contains various feature information of the corneal molding lens surface, such as flatness, smoothness, defect condition, etc. These data are important basis for evaluating the quality of the lens. Through analysis and processing of the data, it can be judged whether the lens meets the quality standard and whether there are potential problems, providing basic data for subsequent data analysis, comparison and judgment. The data collected this time can be compared with historical detection data to observe the trend of lens quality change; the data of different detection areas can also be comprehensively analyzed to evaluate the overall quality of the lens.

[0053] Preferably, the step of analyzing the corneal molding lens according to the first detection data to generate preliminary detection information, cleaning guidance information and detection guidance information comprises: S21: retrieving historical detection records from the detection equipment used to perform optical visual data collection; S22: analyzing the corneal molding lens for potential defects according to the first detection data, and evaluating the confidence of the analysis result based on the historical detection records to generate preliminary detection information composed of several area detection features for the corneal molding lens; S23: performing prediction analysis on each of the area detection features in the preliminary detection information to determine whether the area detection features are considered as uncleaned dirt, to obtain a dirt probability feature corresponding to each of the area detection features, and to obtain cleaning guidance information based on the analysis of each of the dirt probability features; S24: predicting the optical visual performance of the contact lens after cleaning according to the cleaning guidance information to obtain a plurality of possible optical visual performance forms; S25: performing detection effectiveness analysis of various optical visual detection forms based on the various possible optical visual performance forms to obtain detection guidance information; wherein the optical visual detection forms include the lighting environment in which the contact lens is located, and the orientation and angle of optical visual data collection.

[0054] Specifically, from the detection device used to perform optical visual data collection, the detection data and results of the contact lens to be detected in the past are extracted, and these historical records contain information such as the optical visual features of the lens at different time points, problems found in detection, etc. The historical detection records reflect the quality change trend and common problems of the contact lens. By referring to the historical records, the reliability of the current detection result can be more accurately judged, and misjudgment caused by errors or accidental factors in single detection can be avoided. The use and quality change of each contact lens have certain particularity, and the historical detection records provide personalized reference for the lens, so that the analysis process can better adapt to its unique situation and improve the accuracy and pertinence of evaluation.

[0055] More specifically, according to the first detection data, a specific algorithm and model are used to comprehensively check the contact lens and identify potential defects such as scratches, cracks, deposits, and deformation. In the analysis process, attention is paid to the changes in the optical visual features of each area of the lens to determine whether there are abnormal conditions. In combination with the historical detection records, the reliability of the results of the potential defect analysis is evaluated. If similar problems have occurred in this area multiple times in the historical detection, or the current detection result is consistent with the historical trend, the confidence of the analysis result is high; otherwise, the confidence is low. The results of the potential defect analysis and the confidence evaluation are combined to generate preliminary detection information composed of a plurality of area detection features for the contact lens. Each area detection feature describes the quality status of the area in detail, including whether there is a potential defect, the type of the defect, and the confidence, etc.

[0056] More specifically, through the analysis of the first detection data, potential defects of the orthokeratology lens can be found, providing basic information for subsequent processing, and the confidence evaluation further enhances the reliability of the analysis results, enabling more confident judgment of the existence and severity of the problem. The regional detection features in the preliminary detection information provide clear targets and directions for subsequent cleaning guidance and detection guidance generation. Subsequent analysis can be conducted for the specific circumstances of each region, improving the relevance and effectiveness of processing.

[0057] More specifically, the regional detection features in the preliminary detection information are analyzed in depth to predict which features may be caused by uncleaned dirt. By comparing the optical visual features of different detection regions, referring to historical cleaning conditions, and analyzing the performance characteristics of common dirt, the dirt probability characteristics corresponding to each regional detection feature are calculated. Based on each dirt probability characteristic, the regions that need to be cleaned intensively and the appropriate cleaning methods and intensity are determined. For example, if the dirt probability of a certain region is high, a more effective cleaning solution or increased cleaning time may be recommended. For different types of dirt, specific cleaning tools or methods are recommended.

[0058] More specifically, accurate prediction of uncleaned dirt can help users clean more targetedly, avoiding resource waste and possible lens damage caused by blind cleaning. Cleaning guidance information provides specific cleaning recommendations, which can help improve lens cleanliness, improve lens optical performance and wearing comfort. According to the dirt probability characteristics of different regions, appropriate cleaning methods and intensity can be selected to effectively remove dirt while minimizing damage to the lens and prolonging the service life of the lens.

[0059] More specifically, according to the cleaning guidance information, the optical visual performance of the orthokeratology lens after cleaning according to the guidance is simulated, considering different cleaning effects and possible remaining problems. Several possible optical visual performance forms are predicted, such as the existence of some potential defects or the appearance of new optical feature changes due to slight damage during the cleaning process. The optical visual performance of the cleaned lens may change. Predicting these changes can prepare different detection strategies in advance, ensuring that the true quality condition of the lens can be accurately detected after cleaning, avoiding the influence of optical feature changes caused by the cleaning process on the accuracy of the detection results. By predicting the various optical visual performance forms that may appear after cleaning, the most suitable detection parameters can be determined in advance, reducing unnecessary detection attempts and improving detection efficiency.

[0060] More specifically, for various possibilities of optical visual manifestations, the various optical visual detection forms (including the lighting environment in which the orthokeratology lens is located, the orientation and angle of optical visual data collection) are evaluated, the detection effect and accuracy of different detection forms under each manifestation form are analyzed, and the most suitable detection parameters such as lighting environment, data collection orientation and angle are determined according to the results of detection effectiveness analysis, and detection guide information is generated to ensure that the optical visual data reflecting the true quality condition of the lens can be accurately collected after cleaning. For various possibilities of optical visual manifestations, the various optical visual detection forms (including the lighting environment in which the orthokeratology lens is located, the orientation and angle of optical visual data collection) are evaluated, the detection effect and accuracy of different detection forms under each manifestation form are analyzed, and the most suitable detection parameters such as lighting environment, data collection orientation and angle are determined according to the results of detection effectiveness analysis, and detection guide information is generated to ensure that the optical visual data reflecting the true quality condition of the lens can be accurately collected after cleaning.

[0061] Preferably, the step of modifying the preliminary detection information based on the subsequent detection information to obtain the complete detection information of the orthokeratology lens comprises: S41: difference analysis is performed on the subsequent detection information and the preliminary detection information, and the preliminary detection information is divided based on the results of difference analysis to obtain a dirt part confirmed as not cleaned and a defect part suspected as a potential defect; S42: the information part with consistent relative positioning with the defect part in the subsequent detection information is retrieved, and the defect part is identified in terms of defect nature and defect amplitude to obtain complete detection information composed of a plurality of defect identification features.

[0062] Specifically, the subsequent detection information and the preliminary detection information are compared in a comprehensive and detailed manner. Specifically, the differences in optical visual features such as brightness, contrast, texture, shape, etc. of the lens in each region are compared, and according to the comparison results, it is judged which differences are caused by cleaning operation and which differences imply potential problems of the lens. If there is an abnormal feature in a certain region in the preliminary detection, but the feature disappears or significantly improves in the subsequent detection, then the abnormality of this region is likely caused by uncleaned dirt. On the contrary, if the feature still exists or has new changes, then the region may have a potential defect. Based on the above judgment, the preliminary detection information is divided into two parts, one part is the dirt part confirmed as not cleaned, and the other part is the defect part suspected as a potential defect.

[0063] More specifically, in the preliminary detection, it is difficult to accurately distinguish whether the abnormalities on the lens surface are caused by uncleaned dirt or real potential defects. By comparing the subsequent detection information and the preliminary detection information, the two can be clearly distinguished according to the changes before and after cleaning, which helps to more accurately understand the actual quality problems of the lens, avoid misjudging dirt as potential defects, or ignoring real potential defects, divide the preliminary detection information into dirt and defect parts, so that the subsequent analysis can focus on the defect part of the potential defect for in-depth research, which can improve the efficiency and accuracy of the analysis and avoid wasting time and resources in the area that has been cleaned.

[0064] More specifically, from the subsequent detection information, the information part with consistent relative positioning with the defect part divided in the preliminary detection information is accurately retrieved, that is, the detailed data corresponding to the same position of the lens in the subsequent detection is found, and the detailed data of the corresponding position in the subsequent detection information is used to identify the defect properties of the defect part in combination with professional knowledge and algorithms. Determine whether the defect is a scratch, crack, bubble, precipitate or other type of defect. In addition to identifying the nature of the defect, it is also necessary to determine the amplitude of the defect, i.e. the size, depth, severity, etc. of the defect. This can be achieved by analyzing characteristic parameters in optical vision data such as area, length, gray value, etc., combined with relevant standards and models. The identification results of the nature and amplitude of the defect are combined to form a complete detection information composed of several defect identification features, which describe the specific situation of potential defects on the lens in detail and provide accurate basis for comprehensive evaluation of the quality of the lens.

[0065] More specifically, it is not enough to know that the lens has potential defects, but also to understand the specific nature and severity of these defects. By retrieving the information of the corresponding position in the subsequent detection information and conducting detailed analysis, the nature and amplitude of the defect can be accurately identified, which is of great significance for determining whether the lens can continue to be used safely, whether it needs to be repaired or replaced, etc. Accurate defect identification features can provide detailed information about the quality of the lens.

[0066] Preferably, it also includes: S51: integrating each defect identification feature to generate a defect identification matrix, and based on the defect identification matrix, performing information expansion analysis on each specific position of the orthokeratology lens to obtain a quality condition expression matrix corresponding to the orthokeratology lens; S52: performing dimensionality reduction on the quality condition expression matrix by linear discriminant analysis method to obtain a main feature matrix; S53: evaluating the quality status of each specific position of the orthokeratology lens based on the pre-set quality standard, and expressing the evaluation result in a graphical form to obtain a quality status scatter plot; S54: analyzing the daily use mode of the orthokeratology lens and the quality damage characteristics caused by the daily use mode of the orthokeratology lens according to the quality status scatter plot; S55: analyzing the maintenance scheme and the optimal use mode of the orthokeratology lens according to the quality damage characteristics and the daily use mode, to obtain lens maintenance and use guide information for the user.

[0067] Specifically, the previously obtained various defect recognition features are integrated, which include information such as the position, nature (such as scratches, cracks, precipitates, etc.), amplitude (size, depth, etc.) of the defects, and the features are organized according to certain rules to generate a defect recognition matrix. Each row or column of the matrix can represent a specific feature dimension, and the elements in the matrix correspond to the values of the features. Based on the defect recognition matrix, information expansion analysis is performed on each specific position of the orthokeratology lens, which involves considering factors such as the structural characteristics of the lens, the functional importance of different positions, and the mutual influence between defects. Through this analysis, a quality status expression matrix corresponding to the orthokeratology lens is obtained, which more comprehensively reflects the quality status of each position of the lens. The defect recognition features are scattered and complex, and by integrating them into a matrix, these information can be systematized for subsequent analysis and processing. Information expansion analysis can take into account various factors of the lens, making the quality status expression matrix more comprehensively reflect the actual quality status of the lens, providing a basis for accurate evaluation of the lens quality.

[0068] More specifically, a linear discriminant analysis (LDA) method is used to reduce the dimension of the quality status expression matrix. LDA is a supervised dimension reduction technique that can preserve the discrimination information between different categories while reducing the dimension of the data. According to the algorithm principle of LDA, the eigenvectors and projection directions of the quality status expression matrix are calculated, and the high-dimensional quality status expression matrix is projected into a low-dimensional space to obtain a main feature matrix. The main feature matrix after dimension reduction not only reduces the complexity of the data, but also highlights the most important feature information for lens quality evaluation. The quality status expression matrix usually has a high dimension and contains a large amount of feature information. High-dimensional data not only increases the complexity of calculation, but also may cause overfitting and other problems. Through dimension reduction processing, the dimension of the data can be reduced, and the efficiency and accuracy of the analysis can be improved. The LDA method can preserve the discrimination information between different quality statuses while reducing the dimension, so that the main feature matrix highlights the most important features for lens quality evaluation, which is convenient for subsequent quality evaluation and analysis.

[0069] More specifically, each element in the main feature matrix is analyzed according to pre-set quality standards to evaluate the quality status of each specific position on the orthokeratology lens, which can be established by the lens manufacturer, eye care professionals or relevant industry standards to determine whether the lens meets safety and usage requirements. The results of the quality evaluation are expressed in a graphical form to generate a quality status scatter plot, in which each point represents a specific position on the lens, and the coordinates of the point can be determined according to the feature values in the main feature matrix. The attributes such as color, size or shape of the point can represent the quality status of the position (e.g. good, general, poor, etc.).

[0070] More specifically, by carefully observing the quality status scatter plot and analyzing the quality distribution pattern of different positions on the orthokeratology lens, combined with the design characteristics of the lens and the stress conditions, contact environment and other factors during normal use, the user's daily use mode can be inferred. For example, if flaws frequently occur in a certain area of the lens, it may indicate that the user often touches that area when putting on or taking off the lens, or that area is more susceptible to external contaminants. According to the daily use mode and the quality status scatter plot, the quality damage features of the orthokeratology lens caused by daily use are determined, which include the type of flaws, the frequency of occurrence of the position, the severity of damage, etc. They reflect the specific impact of daily use on the quality of the lens. By carefully observing the quality status scatter plot and analyzing the quality distribution pattern of different positions on the orthokeratology lens, combined with the design characteristics of the lens and the stress conditions, contact environment and other factors during normal use, the user's daily use mode can be inferred. According to the daily use mode and the quality status scatter plot, the quality damage features of the orthokeratology lens caused by daily use are determined, which include the type of flaws, the frequency of occurrence of the position, the severity of damage, etc. They reflect the specific impact of daily use on the quality of the lens.

[0071] More specifically, according to the quality damage features and the daily use mode, the orthokeratology lens is analyzed in depth, and a maintenance plan and optimal use mode suitable for the lens are developed. The maintenance plan includes suggestions on cleaning methods, cleaning frequency, storage conditions, etc. The optimal use mode involves guidance on the correct method of putting on and taking off the lens, usage duration, usage environment, etc. The analyzed maintenance plan and optimal use mode are organized into clear and understandable lens maintenance guide information and lens use guide information, which are provided to the user to help them better maintain and use the orthokeratology lens. The lens maintenance guide information and lens use guide information can guide the user to correctly maintain and use the orthokeratology lens, prolong the service life of the lens, ensure the optical performance and safety of the lens, provide detailed usage and maintenance suggestions for the user, help improve the user's wearing comfort and visual effect, and at the same time reduce eye health problems caused by improper use or maintenance, and improve the overall experience of the user.

[0072] Referring toFigure 2 In the second aspect, the present application provides a system for detecting a corneal molding lens, which is used to implement the method for detecting a corneal molding lens according to any one of the first aspect, and comprises: a visual detection module, configured to clean the corneal molding lens, collect light visual data of the cleaned corneal molding lens, and obtain first detection data; a detection analysis module, configured to analyze the corneal molding lens according to the first detection data, and generate preliminary detection information, cleaning guidance information, and detection guidance information; a subsequent detection module, configured to clean the corneal molding lens according to the cleaning guidance information, and collect subsequent detection information based on the detection guidance information; an information correction module, configured to correct the preliminary detection information based on the subsequent detection information, so as to obtain complete detection information of the corneal molding lens.

[0073] In the embodiment, the specific implementation of each module in the system embodiment is described above, and will not be repeated here.

[0074] The above only describes the preferred embodiments of the present application and should not be used to limit the present application. Any modification, equivalent replacement and improvement made within the spirit and principle of the present application should be included in the protection scope of the present application.

Claims

1. A method for detecting orthokeratology lenses, characterized in that, include: The orthokeratology lens was cleaned, and light and visual data were collected from the cleaned orthokeratology lens to obtain the first test data; The orthokeratology lens is analyzed based on the first detection data to generate preliminary detection information, cleaning instructions, and testing instructions. The orthokeratology lens is cleaned according to the cleaning guidelines, and subsequent detection information is collected based on the detection guidelines. The preliminary detection information is corrected based on the subsequent detection information to obtain the complete detection information of the orthokeratology lens.

2. The method for detecting orthokeratology lenses as described in claim 1, characterized in that, The cleaning process for orthokeratology lenses can be performed manually or automatically using designated cleaning equipment. The cleaning guidance information includes operating instructions for either manual or automatic processing.

3. The method for detecting orthokeratology lenses as described in claim 1, characterized in that, The acquisition of light and visual data for the cleaned orthokeratology lenses is performed using either a handheld or fixed testing device. The fixed detection device has a detection position for placing the orthokeratology lens, so that the fixed detection device can collect optical visual data from the orthokeratology lens. The testing equipment stores historical testing records of the orthokeratology lenses to be tested.

4. The method for detecting orthokeratology lenses as described in claim 1, characterized in that, The steps for acquiring light and visual data for orthokeratology lenses include: Ambient light is applied to the orthokeratology lens to place it in a specified lighting environment, and optical visual data is collected from the orthokeratology lens in the lighting environment. The step of applying ambient light to the orthokeratology lens includes: The spatial positioning information of the orthokeratology lens is obtained, and the detection area of ​​the orthokeratology lens is divided and spatially positioned according to the spatial positioning information to generate the regional positioning information of each detection area on the orthokeratology lens. Each of the aforementioned detection areas is taken as a detection object. According to the area positioning information, light of a specified specification is applied to the detection object and its adjacent range to make the detection object be in a lighting environment with light differentiation from the adjacent range.

5. The method for detecting orthokeratology lenses as described in claim 1, characterized in that, The steps of analyzing the orthokeratology lens based on the first detection data to generate preliminary detection information, cleaning instructions, and testing instructions include: Retrieve historical inspection records from the inspection equipment used to perform optical vision data acquisition; Based on the first detection data, the potential defects of the orthokeratology lens are analyzed, and the confidence level of the analysis results is evaluated based on the historical detection records, so as to generate preliminary detection information for the orthokeratology lens consisting of detection features of several regions. The detection features of each area in the preliminary detection information are subjected to predictive analysis to determine if they are uncleaned, so as to obtain the dirt probability features of each area detection feature, and cleaning guidance information is obtained based on the dirt probability features. Based on the cleaning guidance information, the optical visual performance of the orthokeratology lens after cleaning is predicted to obtain several possible optical visual performance forms. Based on various possible optical visual manifestations, the effectiveness of various optical visual detection methods is analyzed to obtain detection guidance information; wherein, the optical visual detection methods include the lighting environment in which the orthokeratology lens is located, as well as the orientation and angle of optical visual data acquisition.

6. The method for detecting orthokeratology lenses as described in claim 1, characterized in that, The steps of correcting the preliminary detection information based on the subsequent detection information to obtain the complete detection information for the orthokeratology lens include: A difference analysis is performed between the subsequent detection information and the preliminary detection information, and the preliminary detection information is divided based on the results of the difference analysis to obtain the parts of dirt that are confirmed to be uncleaned and the parts of defects that are suspected to be potential defects. The information portion with the same relative positioning as the defective part in the subsequent detection information is retrieved, and the defective part is identified in terms of defect nature and defect amplitude to obtain complete detection information composed of several defect identification features.

7. The method for detecting orthokeratology lenses as described in claim 6, characterized in that, Also includes: The defect identification features are integrated to generate a defect identification matrix, and information expansion analysis is performed on the specific locations of the orthokeratology lens based on the defect identification matrix to obtain the quality status expression matrix of the orthokeratology lens. The quality status expression matrix is ​​reduced in dimensionality using linear discriminant analysis to obtain the main feature matrix; Based on pre-set quality standards, the quality status of the corneal reshaping lens at various specific locations is evaluated using the main feature matrix, and the evaluation results are expressed in a graphical form to obtain a scatter plot of quality status. The daily usage patterns of the orthokeratology lenses and the quality damage characteristics caused to the lenses were obtained based on the scatter plot analysis of the quality status. Based on the quality damage characteristics and the daily usage patterns, an analysis of the maintenance plan and optimal usage mode for the orthokeratology lenses is conducted to obtain lens maintenance guidance information and lens usage guidance information for users.

8. A detection system for orthokeratology lenses, characterized in that, A method for detecting an orthokeratology lens according to any one of claims 1-7, comprising: The visual inspection module is used to clean the orthokeratology lens and collect light visual data from the cleaned orthokeratology lens to obtain the first inspection data. The detection and analysis module is used to analyze the orthokeratology lens based on the first detection data and generate preliminary detection information, cleaning instructions, and detection instructions. The subsequent detection module is used to clean the orthokeratology lens according to the cleaning guidance information, and to collect subsequent detection information based on the detection guidance information; The information correction module is used to correct the preliminary detection information based on the subsequent detection information to obtain the complete detection information of the orthokeratology lens.

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