A medical auxiliary imaging detection method, system, and storage medium

Abstract

This application belongs to the field of medical auxiliary equipment, and discloses a medical auxiliary imaging detection method, system and storage medium. The method includes: obtaining the ambient light intensity collected by the user according to the environmental detection prompt instruction, and selecting the backlight direction as the user-facing direction according to the ambient light intensity; obtaining the measurement light intensity by converting according to the ambient light intensity; measuring the current distance between the human eye and the screen, and converting measurement parameters according to the current distance between the human eye and the screen and the measurement light intensity; displaying a black background, and displaying white light points on the black background for testing; receiving the characteristic pattern drawn by the user on the black background, and performing patient visual field quantization reduction by multiplying the size data of the characteristic pattern by the quantization reduction coefficient, where the quantization reduction coefficient is obtained from the measurement parameters, and the accuracy of auxiliary imaging detection can be improved.

Description

Technical Field

[0001] The present application relates to the technical field of medical auxiliary devices, and in particular, to a medical auxiliary imaging detection method, system, and storage medium. Background Art

[0002] Traditional single-focal intraocular lenses can only provide a single focal point. After such cataract surgery, patients can only choose to see near or far, and need to wear glasses for correction at other times. Multifocal intraocular lenses (MIOLs), on the other hand, distribute incident light to two or more focal points. According to the perceptual principle of the brain, they automatically ignore the blurrier images at different distances, thus meeting the visual acuity requirements for far, medium, and near distances. Therefore, MIOLs are favored by more and more cataract patients. Although MIOLs can provide full-range vision for patients, they are also accompanied by varying degrees of visual interference phenomena, such as halos, glare, and starbursts. In the past, the visual interference situation of patients after MIOL implantation was mostly obtained through questionnaires, which had recall bias and lacked objective indicators; although visual quality analyzers can provide objective visual quality results after surgery, they cannot intuitively display the subjective visual interference phenomena of patients. Therefore, visual imaging auxiliary devices for assisting in detecting the vision of patients after MIOL implantation, such as visual quality analyzers, have emerged.

[0003] Modulation transfer function (MTF), point spread function (PSF), and Strehl ratio (SR) in existing visual quality analyzers are indicators for evaluating objective visual quality, but not direct visual interference indicators; although their function of simulating the E-shaped visual acuity chart can partially display the visual effects of patients, it cannot fully represent the real visual interference situation and cannot directly and completely reproduce the visual interference image. The lack of more direct and complete visual interference indicators and the lack of real measurement of the external light environment lead to low accuracy in assisting patient imaging detection. Summary of the Invention

[0004] To this end, embodiments of the present application provide a medical auxiliary imaging detection method, system, and storage medium, which can solve the technical problem of low accuracy of existing auxiliary imaging detection devices. The specific technical solution is as follows:

[0005] In a first aspect, an embodiment of the present application provides a medical auxiliary imaging detection method, the method including:

[0006] Receiving an instruction to enter a test environment and generating an environment detection prompt instruction;

[0007] Obtaining the ambient light intensity collected by the user according to the environment detection prompt instruction, and selecting the backlight direction as the user-facing direction according to the ambient light intensity;

[0008] Convert the measured light intensity according to the ambient light intensity;

[0009] Determine the current measurement scene type;

[0010] If the current measurement scene is a close - range visual effect quantization detection, measure the distance between the current human eye and the screen, and convert the measurement parameters according to the distance between the current human eye and the screen and the measured light intensity;

[0011] Display a black background and display white light points on the black background for testing;

[0012] Receive the characteristic pattern drawn by the user on the black background, and perform patient visual field quantization restoration by multiplying the size data of the characteristic pattern by the quantization restoration coefficient, where the quantization restoration coefficient is obtained from the measurement parameters.

[0013] Preferably, the receiving the characteristic pattern drawn by the user on the black background and performing patient visual field quantization restoration by multiplying the size data of the characteristic pattern by the quantization restoration coefficient obtained from the measurement parameters includes:

[0014] Obtain the adjustment instruction for the user to adjust the white light point, adjust the white light point, and generate a light intensity adjustment parameter according to the adjustment instruction;

[0015] Receive the characteristic pattern drawn by the user on the black background, and perform patient visual field quantization restoration by multiplying the size data of the characteristic pattern by the quantization restoration coefficient obtained from the measurement parameters and the light intensity adjustment parameter.

[0016] Preferably, the receiving the characteristic pattern drawn by the user on the black background includes:

[0017] Switch the test mode of the black background according to the user selection instruction, and display the basic template corresponding to the test mode, where the test mode includes halo, glare, and starburst;

[0018] Receive the characteristic pattern drawn by the user on the black background.

[0019] Preferably, the converting the measured light intensity according to the ambient light intensity includes:

[0020] Calculate the measured light intensity according to the ambient light intensity and the light intensity quantization constant, where the light intensity quantization constant is the ratio of the ambient light intensity to the measured light intensity obtained through experiments.

[0021] Preferably, the method further includes:

[0022] If the current measurement scenario is a long-distance visual effect quantization detection, generate position prompt information to prompt to adjust the distance between the human eye and the screen to a preset distance;

[0023] Display a white ring on the screen for testing, obtain the size of the white ring after the user's adjustment, and calculate the telescopic focusing distance of the user as the calculated distance between the human eye and the screen according to the preset distance and the size of the white ring.

[0024] Preferably, if the current measurement scenario is a short-distance visual effect quantization detection, measure the current distance between the human eye and the screen, and convert the measurement parameters according to the current distance between the human eye and the screen and the measured light intensity, including:

[0025] Measure the current distance between the human eye and the screen, and calculate the test customized light intensity and the customized feature length according to the ratio of the current distance between the human eye and the screen to the multifocal lens design distance, the preset standard quantization feature length, and the measured light intensity.

[0026] Preferably, the method further includes:

[0027] Obtain the adjustment instruction for the user to adjust the white light spot, and adjust the customized feature length according to the adjustment instruction with the light intensity adjustment constant to generate the secondary customized feature length.

[0028] Preferably, the patient's visual field is quantitatively restored by multiplying the size data of the feature pattern by the quantization reduction coefficient, and the quantization reduction coefficient is obtained from the measurement parameters and the light intensity adjustment parameters, including:

[0029] The patient's visual field is quantitatively restored by multiplying the size data of the feature pattern by the quantization reduction coefficient, and the quantization reduction coefficient is calculated by the ratio of the reciprocal of the ratio of the current distance between the human eye and the screen to the multifocal lens design distance to the light intensity adjustment constant.

[0030] In a second aspect, an embodiment of the present application provides a medical auxiliary imaging detection system, and the system includes:

[0031] An environment testing module, configured to receive an instruction to enter the test environment and generate an environment detection prompt instruction;

[0032] A first calculation module, configured to obtain the ambient light intensity collected by the user according to the environment detection prompt instruction, and select the backlight direction as the user-facing direction according to the ambient light intensity;

[0033] A second calculation module, configured to convert the ambient light intensity to obtain the measured light intensity;

[0034] A judgment module, configured to judge the type of the current measurement scenario;

[0035] A third calculation module, configured to measure the distance between the current human eye and the screen if the current measurement scenario is a close - range visual effect quantization detection, and convert measurement parameters according to the distance between the current human eye and the screen and the measured light intensity;

[0036] A drawing module, configured to display a black background, and display white light points on the black background for testing;

[0037] A fourth calculation module, configured to receive the feature pattern drawn by the user on the black background, and perform patient visual field quantization restoration by multiplying the size data of the feature pattern by a quantization restoration coefficient, where the quantization restoration coefficient is obtained from the measurement parameters.

[0038] In a third aspect, an embodiment of the present application provides a computer - readable storage medium, where the computer - readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the medical - assistance imaging detection method described in any one of the foregoing are implemented.

[0039] In summary, compared with the prior art, the beneficial effects brought by the technical solution provided by the embodiment of the present application at least include:

[0040] Through the feature images corresponding to the halos, glares, and starbursts drawn by the user on the black background, the image seen by the patient can be restored by multiplying the size data of the feature pattern by the quantization restoration coefficient. The setting of the present application adds ambient light as an influencing parameter, which can assist in drawing the feature image seen by the patient, facilitating the objective analysis of clinical adverse visual phenomena and improving the accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 FIG. is a schematic flowchart of a medical - assistance imaging detection method provided by one embodiment of the present application.

[0042] Figure 2 FIG. is one of the schematic flowcharts of a medical - assistance imaging detection method provided by another embodiment of the present application.

[0043] Figure 3 FIG. is an imaging diagram of a halo in a medical - assistance imaging detection method provided by one embodiment of the present application.

[0044] Figure 4 FIG. is a schematic diagram of the principle of glare in a medical - assistance imaging detection method provided by one embodiment of the present application.

[0045] Figure 5 FIG. is an imaging diagram of glare in a medical - assistance imaging detection method provided by one embodiment of the present application.

[0046] Figure 6It is an imaging diagram of a starburst in a medical assisted imaging detection method provided by one embodiment of the present application.

[0047] Figure 7 It is the second schematic flowchart of a medical assisted imaging detection method provided by another embodiment of the present application.

[0048] Figure 8 It is a brightness ratio curve of a medical assisted imaging detection method provided by one embodiment of the present application.

[0049] Figure 9 It is a schematic diagram of the telescopic focusing distance in a medical assisted imaging detection method provided by one embodiment of the present application. Detailed implementation manners

[0050] This specific embodiment is only an explanation of the present application, and it does not limit the present application. Those skilled in the art can make modifications without creative contributions to this embodiment after reading this specification, but as long as they are within the scope of the claims of the present application, they are protected by the patent law.

[0051] To make the objectives, technical solutions, and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are some, but not all, of the embodiments of the present application. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present application without making creative efforts belong to the scope of protection of the present application.

[0052] In addition, the term "and / or" in the present application is only a description of the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B may represent: A exists alone, A and B exist simultaneously, and B exists alone. In addition, the character " / " in the present application generally represents an "or" relationship between the associated objects before and after, unless otherwise specified.

[0053] The terms "first", "second", etc. in the present application are used to distinguish the same items or similar items with basically the same functions. It should be understood that there is no logical or chronological dependency between "first", "second", and "nth", nor are the quantity and execution order limited.

[0054] The term "at least one" in the present application means one or more, and the meaning of "multiple" is three or more. For example, multiple first positions refer to three or more first positions.

[0055] The embodiments of the present application will be further described in detail below with reference to the accompanying drawings of the specification.

[0056] In the prior art, the methods for investigating the pre-operative and post-operative visual imaging phenomena of patients undergoing cataract surgery with multifocal intraocular lenses (MIOL) generally include: 1. Questionnaire survey; 2. Analysis using a visual quality analyzer. The prior art has the following disadvantages:

[0057] 1) There are many types of questionnaires and they are highly subjective.

[0058] Regarding the adverse visual phenomena after implanting MIOL, questionnaire forms are mostly used for investigation, analysis and statistics. There are a wide variety of questionnaires on the market and the standards are inconsistent. Common questionnaires include QoV, PRO, VFQ-25, etc. In addition, the questionnaire forms are highly subjective and there is recall bias, which cannot objectively prove the errors in the patients' adverse visual conditions and visual quality inspection results.

[0059] 2) Lack of more direct and complete visual interference indicators.

[0060] The modulation transfer function (MTF), point spread function (PSF), Strehl ratio (SR), etc. in the visual quality analyzer are indicators for evaluating objective visual quality, but they are not direct visual interference indicators; although its function of simulating the E-shaped visual acuity chart can partially show the patients' visual effects, it cannot fully represent the real visual interference situation. It is unable to directly and completely reproduce the visual interference image, which brings obstacles to doctor-patient communication.

[0061] 3) Lack of real measurement of the external light environment.

[0062] The degree of visual interference of patients after MIOL implantation is different in different external light environments. Studies have found that strong light irradiation in a dark environment will bring more obvious adverse visual phenomena. In the past, patients were exposed to a specific light source and the actual light phenomena were evaluated through a glare meter, but this method cannot classify the adverse visual phenomena into different types such as glare, halo or starburst. Therefore, it is necessary to accurately measure the real light environment and analyze the characteristic graphics of different types in various light environments.

[0063] 4) The screen-eye distance and the intensity of the test light spot are not standardized.

[0064] The screen-eye distance was not standardized in previous studies. However, patients have a habitual distance when using electronic devices in daily life, and the evaluation of visual quality at the habitual distance is more meaningful. At the same time, considering that too strong light source brightness will cause the characteristic graphics to exceed the screen range, it is necessary to customize the measurement of light intensity according to the patients' habitual screen distance.

[0065] Refer to Figure 1 , in an embodiment of the present application, a medical auxiliary imaging detection method is provided, and the main steps of the method are described as follows:

[0066] S1: Receive the instruction to enter the test environment and generate the environment detection prompt instruction;

[0067] S2: Obtaining the ambient light intensity collected by the user according to the environment detection prompt instruction, and selecting the backlight direction as the direction the user is facing according to the ambient light brightness;

[0068] Specifically, a software system is formed according to the medical-assisted imaging detection method of the present application to be installed on the user's electronic device. In this embodiment, the electronic device can be a smart device such as a mobile phone, a computer, or a tablet. When the user uses the software system described in the present application, the user triggers an instruction to enter the test environment. The triggering method includes but is not limited to: opening the software system described in the present application, clicking on the controls preset in the software system of the present application, and placing the electronic device in the corresponding environment according to the triggering conditions of the software system.

[0069] When the user triggers the command to enter the test environment, an environment detection prompt command is generated to guide the user to use the mobile device to detect the ambient light intensity around. The form of the environment detection prompt command includes but is not limited to: pop-up instruction information on the interface of the user's electronic device, voice broadcast instruction information, etc. In this embodiment, taking the pop-up instruction information on the interface of the user's electronic device as an example, after the user triggers the command to enter the test environment, a pop-up message "Please rotate the mobile device 360 ​​degrees horizontally" is popped up on the interface of the user's electronic device, and the mobile phone rotation angle information returned by the hardware such as the horizontal tester or the mobile phone rotation angle sensor in the user's electronic device is received to determine whether the user's operation meets the requirements, and the ambient light intensity collected by the operation that meets the requirements is stored. If the user's operation does not meet the requirements, the environment detection command is popped up again to reduce the inaccuracy of the collected data caused by human operation.

[0070] According to the ambient light intensity, the direction with the most obvious backlight is selected as the facing direction, and then the user is prompted to stand in a position facing the facing direction. The prompt can be in the form of images, text, voice, etc., which will not be elaborated here.

[0071] S3: Calculate the measured light intensity according to the ambient light intensity;

[0072] Specifically, this application is pre-tested in a standard environment set up in the laboratory to obtain standardized data in the standard environment. This application converts the collected environmental light intensity and the measured light intensity. The conversion of the measured light intensity is to make the scale of the optical imaging characteristics basically equivalent to the standard measured in the laboratory. The conversion method can be as follows: by obtaining the luminance ratio curve corresponding to the environmental light intensity measured in a darkroom with different brightness environments and the measured light intensity that can ensure that the scales of three optical imaging characteristics are basically unchanged. When performing the conversion, the light intensity quantization constant is obtained according to the value on the luminance ratio curve corresponding to the value of the environmental light intensity. The measured light intensity is obtained by converting the light intensity quantization constant and the environmental light intensity:

[0073] I = αI 0

[0074] where I is the measured light intensity, I 0 is the environmental light intensity, and α is the light intensity quantization constant.

[0075] In other embodiments of this embodiment, conversion can also be performed by other existing methods, which will not be elaborated here.

[0076] S4: Determine the current measurement scene type;

[0077] Specifically, in this embodiment, the measurement scene types include close-range visual effect quantization detection and long-range visual effect quantization detection.

[0078] S5: If the current measurement scene is close-range visual effect quantization detection, measure the distance between the current human eye and the screen, and convert the measurement parameters according to the distance between the current human eye and the screen and the measured light intensity;

[0079] In this embodiment, when the current measurement scene is close-range visual effect quantization detection, a test prompt message is popped up on the user's interface to guide the user to place the electronic device at the common distance, which is the distance at which the user uses the electronic device. Measure the distance between the screen and the human eye, and convert the measurement parameters from the distance between the current human eye and the screen and the measured light intensity. The measurement parameters are obtained by converting the parameters of the current test scene and the standard scene. The laboratory scene can be restored according to the measurement parameters.

[0080] S6: Display a black background and display white light points on the black background for testing;

[0081] S7: Receive the characteristic pattern drawn by the user on the black background, and perform patient visual field quantization restoration by multiplying the size data of the characteristic pattern by the quantization restoration coefficient, where the quantization restoration coefficient is obtained from the measurement parameters.

[0082] Specifically, by means of the characteristic images corresponding to the halos, glares, and starbursts drawn by the user on a black background, the image seen by the patient can be restored by multiplying the size data of the characteristic pattern by the quantization reduction coefficient. The setting of this application adds ambient light as an influencing parameter, which can assist in drawing the characteristic images seen by the patient and facilitate the objective analysis of clinical adverse visual phenomena.

[0083] Refer to Figure 2 , further, in another embodiment, S7 further includes:

[0084] S71: Obtain the adjustment instruction for the user to adjust the white light point, adjust the white light point, and generate the light intensity adjustment parameter according to the adjustment instruction;

[0085] S72: Receive the characteristic pattern drawn by the user on the black background, and perform quantization reduction of the patient's visual field by multiplying the size data of the characteristic pattern by the quantization reduction coefficient, where the quantization reduction coefficient is obtained from the measurement parameter and the light intensity adjustment parameter.

[0086] Specifically, since the sizes of the three characteristics of halos, glares, and starbursts are positively correlated with the light intensity, and the starburst occupies the largest area among them. Therefore, in the test, the user can adjust the measurement light intensity of the test point according to the image seen by himself, so that the above three characteristics can fall within the screen range, avoiding the situation where the light intensity is too strong and the stripes of the characteristic image exceed the screen range, making it impossible for the user to depict the graph. The user can also actively adjust to make the three characteristics basically fill the entire screen respectively, which is convenient for the user to depict.

[0087] Record the adjustment parameter after adjusting the measurement light intensity, where the adjustment parameter is the ratio of the adjusted measurement light intensity to the test correlation intensity before adjustment.

[0088] Further, in another embodiment, the receiving the characteristic pattern drawn by the user on the black background includes:

[0089] 1. Switch the test mode of the black background according to the user selection instruction, and display the basic template corresponding to the test mode, where the test mode includes halos, glares, and starbursts;

[0090] 2. Receive the characteristic pattern drawn by the user on the black background.

[0091] Specifically, when the user is performing the test, the user can select the test mode of the current test. For example, when the user selects the halo test mode, since the halo is generated by crystal diffraction, a pattern similar to an aperture will be formed (refer to Figure 3 ), so the software system provides a basic template of the aperture pattern, allowing the user to add multiple apertures on the screen and adjust the size, width, and brightness to be as consistent as possible with the pattern seen by the user in the eyes.

[0092] If the user selects the glare test mode, since the crystal cannot focus like the human eye and the MIOL needs to take into account far, medium, and near vision, there will be some light that cannot be perfectly imaged whether the patient is looking near or far (refer to Figure 4 ). Therefore, glare is formed (refer to Figure 5 ). Therefore, the software system will provide a basic template of the glare pattern, allowing the user to smear the glare area on the screen and adjust the size and brightness to match the pattern seen by the user as much as possible.

[0093] If the user selects the starburst test mode, due to the unique mirror structure of the MIOL for generating specific diffraction, when light is incident, reflection will occur, and multiple beams of light reflected at different angles will form a starburst (refer to Figure 6 ). Therefore, the software system will generate a basic template of the starburst pattern when the user touches the screen, allowing the user to adjust the arc, length, width, and brightness of the starburst pattern to match the pattern seen by the user as much as possible.

[0094] Refer to Figure 7 , further, in another embodiment, S3 is S3':

[0095] S3': Calculate the measured light intensity according to the ambient light intensity and the light intensity quantization constant, where the light intensity quantization constant is the ratio of the ambient light intensity to the measured light intensity obtained through experiments.

[0096] Further, in another embodiment, the S5 is S5':

[0097] S5': Measure the current distance between the human eye and the screen, and calculate the test customized light intensity and the customized characteristic length according to the ratio of the current distance between the human eye and the screen to the designed distance of the multifocal crystal, the preset standard quantization characteristic length, and the measured light intensity.

[0098] Specifically, the test customized light intensity and the customized characteristic length are equivalent to the light anomaly characteristic scale obtained by the user during testing in a standard light environment and at a standard test distance. The accuracy calculated according to the test customized light intensity and the customized characteristic length calculated in this embodiment is higher.

[0099] The method further includes S8:

[0100] S8: Obtain the adjustment instruction for the user to adjust the white light spot, and adjust the customized characteristic length with the light intensity adjustment constant according to the adjustment instruction to generate a secondary customized characteristic length.

[0101] Since the user sees different sizes of the white light spot, an adjustment instruction for the white light spot is provided for the user to adjust the customized characteristic length with the light intensity adjustment constant, improving the accuracy of the test.

[0102] Further, in another embodiment, the quantization reduction of the patient's visual field is performed by multiplying the size data of the feature pattern by a quantization reduction coefficient, and the quantization reduction coefficient is obtained from measurement parameters and light intensity adjustment parameters, including: the quantization reduction of the patient's visual field is performed by multiplying the size data of the feature pattern by a quantization reduction coefficient, and the quantization reduction coefficient is calculated as the ratio of the reciprocal of the ratio of the current distance between the human eye and the screen to the multifocal lens design distance to the light intensity adjustment constant.

[0103] Further, in another embodiment, the method further includes:

[0104] S9: If the current measurement scenario is the quantization detection of long-distance visual effect, generate position prompt information to prompt to adjust the distance between the human eye and the screen to a preset distance;

[0105] S10: Display a white ring on the screen for testing, obtain the size of the white ring after the user's adjustment, and calculate the user's telephoto focusing distance as the calculated distance between the human eye and the screen according to the preset distance and the size of the white ring.

[0106] Specifically, in this embodiment, if the current measurement scenario is the quantization detection of long-distance visual effect, the preset distance is the distance between the user and the screen that needs to be moved to. The distance between the human eye and the screen is measured in advance. If the distance between the human eye and the screen is less than the preset distance, in this embodiment, position prompt information is generated to prompt the user to move away from the screen until the measured distance between the human eye and the screen is the preset distance and stop; if the distance between the human eye and the screen is greater than the preset distance, the user is prompted to move closer to the screen until the measured distance between the human eye and the screen is the preset distance and stop. In other embodiments, other methods can be used.

[0107] When the distance between the human eye and the screen is the preset distance, change the test picture on the screen from white dots to a white ring, and equivalent white light spots are formed due to the special structure of the multifocal lens. By adjusting the size of the white ring to make the equivalent light spots seen by the patient relatively clearest, record the size of the white ring at this time and repeat the subsequent process, and calculate the user's telephoto focusing distance as the calculated distance between the human eye and the screen according to the preset distance and the size of the white ring.

[0108] An example of this embodiment is as follows:

[0109] Test scenario: Quantization detection of near-distance visual effect

[0110] Step 1: The software system of the present application will require the user to keep the test environment as dark as possible, and then guide the user to use the electronic device to detect the ambient light intensity, and horizontally rotate and move the device 360 degrees according to the environmental detection prompt instructions to collect the ambient light intensity I0 , select the direction with the most obvious backlight property as the facing direction.

[0111] Step 2: To minimize the impact of the ambient light environment around the electronic device on the test error and ensure that the scales of the three optical imaging features are basically equivalent to the standard quantization feature length S measured in the laboratory environment, it is necessary to calculate the measured light intensity I according to the ambient light intensity I 0 , and convert it to obtain the measured light intensity I:

[0112] I = αI 0

[0113] where α is the light intensity quantization constant, which is the ambient light intensity I obtained by testing in a dark room with different brightness environments 0 and the brightness ratio curve corresponding to the test brightness I that can ensure that the scales of the three optical imaging features remain basically unchanged (see Figure 8 ).

[0114] Step 3: Guide the user to place the electronic device at a common distance, measure the screen-eye distance L (unit: cm) and input it into the software system. Referring to the multi-focal crystal design distance L 0 (60 cm), the test customized light intensity I p and the customized feature length S d can be calculated according to the standard light intensity I and the standard quantization feature length S:

[0115]

[0116] Step 4: Display a white light spot with a test customized light intensity of I p in the center of black, and let the user depict the three features of the seen halo, glare, and starburst with the assistance of the software system respectively.

[0117] Step 5: Since the sizes of the three features of halo, glare, and starburst are positively correlated with the light intensity, and the starburst occupies the largest area, in the software system, the user is allowed to adjust the light intensity of the test light spot so that the above three features can fall within the screen range, avoiding the situation where the brightness is too strong and the feature image stripes exceed the screen range and the user cannot depict the graph, or the user can also actively adjust to make the three features basically fill the entire screen respectively for the convenience of the user to depict. During this process, the light intensity I p will be multiplied by the light intensity adjustment constant β for brightness adjustment. Therefore, the secondary customized feature length S dd is:

[0118] S dd = βS d

[0119] Step 6: When quantifying and restoring the patient's visual field, it is only necessary to multiply the size data of the three characteristic patterns uploaded by the user by the quantification and restoration coefficient γ.

[0120]

[0121] Test scenario: Quantification detection of long-distance visual effect

[0122] Step 1: The same as the quantification detection of near-distance visual effect;

[0123] Step 2: The same as the quantification detection of near-distance visual effect;

[0124] Step 3: The same as the quantification detection of near-distance visual effect;

[0125] Step 4: Require the user to place the screen at a preset distance L 0 (60 cm) from the eyes, and display a white light spot with a light intensity of I in the center of the black background, guiding the user to adjust the radius R of the white light spot so that a relatively clear white light spot can be formed within the visual field. Since the crystal radius R p is known, after finding the clear light spot, the user's telescope focusing distance L 0 can be obtained from the formula: y (m):

[0126]

[0127] Telescope focusing distance L y can be directly uploaded as the performance parameter of the multifocal crystal (see Figure 9 ).

[0128] Step 5: Depict the three characteristics of the seen halo, glare, and starburst with the assistance of the software system respectively. At this time, the light intensity adjustment constant β can also be adjusted. Finally, the standard quantified characteristic length S of the three characteristics in the long-distance scenario can be calculated through the following formula:

[0129]

[0130] (Compared with the quantification detection of near-distance visual effect, the distance L from the human eye to the screen in the formula is changed to the telescope focusing distance L y , that is, the telescope focusing distance L y is the calculated distance L from the human eye to the screen)

[0131] This application has the following advantages:

[0132] 1) Universality: Traditional visual quality analysis methods rely on specific devices and are difficult to promote among the population. This application can be applied to various mobile devices, such as mobile phones, tablets, etc., truly enabling home measurement and effectively reducing labor costs;

[0133] 2) Integration: The software for light environment detection, the software for screen-eye distance measurement, and the mapping system for adverse visual phenomena are integrated. First, the user is guided to use the mobile device to detect the external light intensity, and the measured light intensity is obtained through conversion. Combining with the parameters of the mobile device, the customized distance between the screen and the eyes is standardized, ensuring that the influence of various factors on the mapped characteristic image is minimized, providing a solid foundation for the standardized reproduction of adverse visual phenomena.

[0134] 3) Visualization: Patients can directly map characteristic images using this system, visualizing subjective feelings, avoiding the cumbersome communication process between doctors and patients, and greatly liberating human resources.

[0135] 4) Precise quantification: Traditional questionnaires cannot precisely quantify and analyze the adverse visual phenomena after MIOL implantation. This application automatically converts and outputs the parameters in three modes of halo, glare, and starburst according to the subjective images described by the user, facilitating the objective analysis of clinical adverse visual phenomena.

[0136] It should be understood that the magnitudes of the sequence numbers of the steps in the above embodiments do not mean the order of execution. The order of execution of each process should be determined by its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present invention.

[0137] In an embodiment of the present application, a medical auxiliary imaging detection system is provided, which corresponds one-to-one with the medical auxiliary imaging detection method in the above embodiment. The medical auxiliary imaging detection system includes:

[0138] An environment testing module, configured to receive an instruction to enter a test environment and generate an environment detection prompt instruction;

[0139] A first calculation module, configured to obtain the environmental light intensity collected by the user according to the environment detection prompt instruction, and select the backlight direction as the user-facing direction according to the environmental light intensity;

[0140] A second calculation module, configured to convert the environmental light intensity to obtain the measured light intensity;

[0141] A judgment module, configured to judge the type of the current measurement scene;

[0142] A third calculation module, configured to measure the distance between the current human eye and the screen if the current measurement scene is a close-range visual effect quantification detection, and convert measurement parameters according to the distance between the current human eye and the screen and the measured light intensity;

[0143] A drawing module, configured to display a black background and display white light points on the black background for testing;

[0144] A fourth calculation module, configured to receive a feature pattern drawn by a user on the black background, perform quantization reduction of the patient's visual field by multiplying the size data of the feature pattern by a quantization reduction coefficient, where the quantization reduction coefficient is obtained from measurement parameters.

[0145] Further, the receiving the feature pattern drawn by the user on the black background, performing quantization reduction of the patient's visual field by multiplying the size data of the feature pattern by a quantization reduction coefficient, where the quantization reduction coefficient is obtained from measurement parameters, includes:

[0146] Obtaining an adjustment instruction for the user to adjust the white light spot, adjusting the white light spot, and generating a light intensity adjustment parameter according to the adjustment instruction;

[0147] Receiving the feature pattern drawn by the user on the black background, performing quantization reduction of the patient's visual field by multiplying the size data of the feature pattern by a quantization reduction coefficient, where the quantization reduction coefficient is obtained from the measurement parameters and the light intensity adjustment parameter.

[0148] Further, the receiving the feature pattern drawn by the user on the black background includes:

[0149] Switching the test mode of the black background according to the user selection instruction and displaying a basic template corresponding to the test mode, where the test mode includes halo, glare, and starburst;

[0150] Receiving the feature pattern drawn by the user on the black background.

[0151] Further, the converting the environmental light intensity into the measured light intensity includes:

[0152] Calculating the measured light intensity according to the environmental light intensity and a light intensity quantization constant, where the light intensity quantization constant is the ratio of the environmental light intensity to the measured light intensity obtained through experiments.

[0153] Further, the system further includes a fifth calculation module, configured to, if the current measurement scenario is quantization detection of the long-distance visual effect, generate an indication position prompt message to prompt to adjust the distance between the human eye and the screen to a preset distance; perform a test by displaying a white ring on the screen, obtain the size of the white ring after the user's adjustment, and calculate the user's telephoto focusing distance as the calculated distance between the human eye and the screen according to the preset distance and the size of the white ring.

[0154] Further, if the current measurement scenario is quantization detection of the near-distance visual effect, measuring the current distance between the human eye and the screen, and converting the measurement parameters according to the current distance between the human eye and the screen and the measured light intensity, includes:

[0155] Measure the current distance between the human eye and the screen, and calculate the test customized light intensity and the customized feature length based on the ratio of the current distance between the human eye and the screen to the multifocal lens design distance, the preset standard quantization feature length, and the measured light intensity.

[0156] Further, the system further includes a sixth calculation module, configured to obtain an adjustment instruction for the user to adjust the white light spot, and generate a secondary customized feature length by adjusting the customized feature length according to the adjustment instruction with a light intensity adjustment constant.

[0157] Further, the patient's visual field is quantitatively restored by multiplying the size data of the feature pattern by a quantization reduction coefficient, and the quantization reduction coefficient is obtained from measurement parameters and light intensity adjustment parameters, including:

[0158] The patient's visual field is quantitatively restored by multiplying the size data of the feature pattern by a quantization reduction coefficient, and the quantization reduction coefficient is calculated from the reciprocal of the ratio of the current distance between the human eye and the screen to the multifocal lens design distance and the ratio of the light intensity adjustment constant.

[0159] Each module of the above medical auxiliary imaging detection system can be implemented in whole or in part by software, hardware, and their combination. Each of the above modules can be embedded in or independent of a processor in a computer device in the form of hardware, or stored in a memory in the computer device in the form of software, so that the processor can call and execute the operations corresponding to each of the above modules.

[0160] In an embodiment of the present application, a computer-readable storage medium is provided. The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the medical auxiliary imaging detection method described in the above embodiment are implemented. The computer-readable storage medium includes ROM (Read-Only Memory), RAM (Random-Access Memory), CD-ROM (Compact Disc Read-Only Memory), magnetic disks, floppy disks, etc.

[0161] Those skilled in the art can clearly understand that, for the convenience and simplicity of description, only the above division of each functional unit and module is used as an example. In actual applications, the above functions can be allocated to different functional units and modules according to needs, that is, the internal structure of the system described in the present application is divided into different functional units or modules to complete all or part of the functions described above.

Claims

1. A medical auxiliary imaging detection method, characterized in that, the method includes: Receiving an instruction to enter the test environment and generating an environment detection prompt instruction; Obtaining the ambient light intensity collected by the user according to the environment detection prompt instruction, and selecting the backlight direction as the user-facing direction according to the ambient light intensity; Converting the ambient light intensity to obtain the measured light intensity; Judging the current measurement scene type; If the current measurement scene is a close-range visual effect quantization detection, measure the distance between the current human eye and the screen, and convert the measurement parameters according to the distance between the current human eye and the screen and the measured light intensity; Display a black background, and display white light points on the black background for testing; Receiving the characteristic pattern drawn by the user on the black background, and performing patient visual field quantization restoration by multiplying the size data of the characteristic pattern by the quantization restoration coefficient, where the quantization restoration coefficient is obtained from the measurement parameters.

2. The medical auxiliary imaging detection method according to claim 1, characterized in that, Receiving the characteristic pattern drawn by the user on the black background, and performing patient visual field quantization restoration by multiplying the size data of the characteristic pattern by the quantization restoration coefficient, where the quantization restoration coefficient is obtained from the measurement parameters, includes: Obtaining an adjustment instruction for the user to adjust the white light point, adjusting the white light point, and generating a light intensity adjustment parameter according to the adjustment instruction; Receiving the characteristic pattern drawn by the user on the black background, and performing patient visual field quantization restoration by multiplying the size data of the characteristic pattern by the quantization restoration coefficient, where the quantization restoration coefficient is obtained from the measurement parameters and the light intensity adjustment parameter.

3. The medical auxiliary imaging detection method according to claim 1, characterized in that, Receiving the characteristic pattern drawn by the user on the black background includes: Switching the test mode of the black background according to the user selection instruction and displaying the basic template corresponding to the test mode, where the test mode includes halo, glare, and starburst; Receiving the characteristic pattern drawn by the user on the black background.

4. The medical auxiliary imaging detection method according to claim 1, characterized in that, Converting the ambient light intensity to obtain the measured light intensity includes: Calculating the measured light intensity according to the ambient light intensity and the light intensity quantization constant, where the light intensity quantization constant is the ratio of the ambient light intensity to the measured light intensity obtained through experiments.

5. The medical auxiliary imaging detection method according to claim 1, characterized in that, The method further includes: If the current measurement scene is a long-range visual effect quantization detection, generating an indication position prompt information to prompt to adjust the distance between the human eye and the screen to a preset distance; Displaying a white ring on the screen for testing, obtaining the size of the adjusted white ring by the user, and calculating the user's telephoto focusing distance as the calculated distance between the human eye and the screen according to the preset distance and the size of the white ring.

6. The medical auxiliary imaging detection method according to claim 2, characterized in that, If the current measurement scenario is the quantization detection of the near - distance visual effect, measure the distance between the current human eye and the screen, and convert the measurement parameters according to the distance between the current human eye and the screen and the measured light intensity, including: Measure the distance between the current human eye and the screen, and calculate the test - customized light intensity and the customized feature length according to the ratio of the distance between the current human eye and the screen to the multifocal lens design distance, the preset standard quantization feature length, and the measured light intensity.

7. The medical - assisted imaging detection method according to claim 6, wherein, The method further includes: Obtain the adjustment instruction for the user to adjust the white light spot, and adjust the customized feature length according to the adjustment instruction with the light intensity adjustment constant to generate the secondary - customized feature length.

8. The medical - assisted imaging detection method according to claim 7, wherein, The quantization reduction of the patient's visual field is performed by multiplying the size data of the feature pattern by the quantization reduction coefficient, and the quantization reduction coefficient is obtained from the measurement parameters and the light intensity adjustment parameters, including: The quantization reduction of the patient's visual field is performed by multiplying the size data of the feature pattern by the quantization reduction coefficient, and the quantization reduction coefficient is calculated from the reciprocal of the ratio of the distance between the current human eye and the screen to the multifocal lens design distance and the light intensity adjustment constant.

9. A medical - assisted imaging detection system, wherein, The system includes: An environment - testing module, configured to receive the instruction to enter the test environment and generate an environment - detection prompt instruction; A first calculation module, configured to obtain the environmental light intensity collected by the user according to the environment - detection prompt instruction, and select the backlight direction as the user - facing direction according to the environmental light intensity; A second calculation module, configured to convert the environmental light intensity to obtain the measured light intensity; A judgment module, configured to judge the type of the current measurement scenario; A third calculation module, configured to measure the distance between the current human eye and the screen if the current measurement scenario is the quantization detection of the near - distance visual effect, and convert the measurement parameters according to the distance between the current human eye and the screen and the measured light intensity; A drawing module, configured to display a black background and display a white light spot on the black background for testing; A fourth calculation module, configured to receive the feature pattern drawn by the user on the black background, and perform the quantization reduction of the patient's visual field by multiplying the size data of the feature pattern by the quantization reduction coefficient, and the quantization reduction coefficient is obtained from the measurement parameters.

10. A computer - readable storage medium, wherein, The computer - readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the medical - assisted imaging detection method according to any one of claims 1 to 8 are implemented.

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