Eye biomechanical characteristic evaluation method based on dynamic Scheimpflug imaging technology

Abstract

The invention relates to an eye biomechanical characteristic evaluation method based on a dynamic Scheimpflug imaging technology. The method comprises the following steps: capturing a dynamic deformation video of a cornea through a Scheimpflug camera; performing eye biomechanical characteristic evaluation on the dynamic deformation video through the evaluation model; wherein a training sample of the training evaluation model comprises sample cornea data; the sample cornea data comprises sample video data and sample measurement data which are simultaneously measured in the process of pressing the cornea of the user; sample video data are captured through a high-speed Scheimpflug camera, and sample measurement data are obtained through a cornea ultrasonic biomechanical system. The evaluation model adopted in the method is obtained through training based on sample video data captured by a Scheimpflug camera and sample measurement data obtained through a cornea ultrasonic biomechanical system, and the eye biomechanical characteristics can be evaluated more accurately and reliably.

Description

Technical Field

[0001] The present invention relates to the technical field of eye property evaluation, and in particular to an eye biomechanical property evaluation method based on dynamic Scheimpflug imaging technology. Background Art

[0002] Ocular biomechanical assessment is the evaluation of the biomechanical properties of the eye through a series of tests and measurements. This assessment is important for understanding the health of the eye, predicting potential eye problems, and guiding ophthalmic treatment.

[0003] Existing ocular biomechanics assessment methods mainly rely on devices such as the ocular response analyzer (ORA), which have certain limitations in measurement accuracy, parameter types and real-time dynamic measurement. Summary of the invention

[0004] 1. Technical issues to be resolved

[0005] In order to solve the above problems, the present invention provides a method for evaluating eye biomechanical properties based on dynamic Scheimpflug imaging technology.

[0006] (II) Technical solution

[0007] In order to achieve the above object, the main technical solutions adopted by the present invention include:

[0008] A method for evaluating ocular biomechanical properties based on dynamic Scheimpflug imaging technology, the method comprising:

[0009] Capture the dynamic deformation video of the cornea using a high-speed Scheimpflug camera;

[0010] Evaluate ocular biomechanical properties from dynamic deformation videos using a pre-trained evaluation model;

[0011] Among them, the evaluation model is trained based on the training samples;

[0012] The training samples include sample cornea data of multiple users;

[0013] The sample corneal data of any user includes: sample video data and sample measurement data measured simultaneously during the process of applying pressure to the cornea of ​​any user; the sample video data is captured by a high-speed Scheimpflug camera, and the sample measurement data is obtained by a corneal ultrasonic biomechanics system.

[0014] Optionally, the corneal ultrasound biomechanics system includes: an ultrasound indentation module, a shear wave tomography module, a pulse transmitter-receiver, a power amplifier, a control system, a motion displacement device, and a computer;

[0015] Ultrasonic printing module, including: ultrasonic printing transducer and mechanical sensor;

[0016] A shear wave tomography module, comprising: an ultrasonic transducer and a piezoelectric vibrator;

[0017] The ultrasonic printing module is connected to the motion displacement device and the pulse transmitter and receiver respectively;

[0018] The ultrasonic transducer is connected to the pulse transmitter and receiver;

[0019] The mechanical amplifier and the pulse transmitter-receiver are respectively connected to the control system;

[0020] The piezoelectric vibrator is connected to a power amplifier;

[0021] The power amplifier is connected to the control system;

[0022] The control system is connected to the computer;

[0023] The ultrasonic transducer is connected to the mechanical sensor;

[0024] The control system is used to control the pulse transmitter and receiver, the mechanical amplifier, the motion displacement device and the ultrasonic indentation module to obtain corneal displacement data; and to control the pulse transmitter and receiver, the power amplifier and the shear wave tomography module to obtain corneal shear data;

[0025] A computer is used for obtaining measurement data according to the corneal displacement data and the corneal shearing data.

[0026] Optionally, a control system is used to control the motion displacement device to drive the ultrasonic indentation module to measure the strain of the overall structure of the cornea; obtain the corneal displacement data measured by the ultrasonic indentation module through a pulse transmitter and receiver; control the power amplifier to drive the shear wave tomography module to measure the shear wave transmission data in the cornea; and obtain the corneal shear data measured by the shear wave tomography module through a pulse transmitter and receiver.

[0027] Optionally, the ultrasonic transducer is a water-immersed miniature piezoelectric transducer with a diameter of 1 mm and a frequency of 20 MHz; the ultrasonic transducer is a ring array composed of 16 ultrasonic transducer units; the ultrasonic transducers are arranged in a ring at the inner edge of the cornea; the ultrasonic transducer obtains corneal shear data;

[0028] The piezoelectric vibrator is an array composed of 16 piezoelectric vibrator units; each piezoelectric vibrator unit is connected to a unique probe; all probes are placed at the outer edge of the cornea, and drive the cornea to vibrate through reciprocating motion to generate shear waves; the piezoelectric vibrator sends shear waves.

[0029] Optionally, the computer is used to determine the tangent modulus of the cornea based on the corneal displacement data; reconstruct a shear wave velocity image based on the corneal shear data, and obtain the Young's modulus of the cornea based on the shear wave velocity image; and obtain measured eye biomechanical properties based on the Young's modulus.

[0030] Optionally, the corneal ultrasonic biomechanics system further includes: a shear wave receiving transducer;

[0031] Reconstruct shear wave velocity images based on corneal shear data, including:

[0032] Through A-ultrasound imaging, the arrival time t(x,z) of the shear wave to the shear wave receiving transducer and the transit time of the shear wave from the ultrasonic transducer to the shear wave receiving transducer are obtained; wherein x and z are coordinates in the two-dimensional medium;

[0033] By formula Determine the shear wave propagation path; where σ(x,z) is the slowness, which is the inverse of the shear wave velocity;

[0034] The shear wave velocity image is reconstructed based on the transit time and the shear wave propagation path.

[0035] Optionally, reconstructing a shear wave velocity image according to the transit time and the shear wave propagation path includes:

[0036] By formula Reconstruct shear wave velocity images;

[0037] Where k is the current iteration number, i is the pixel number of the reconstructed image, N is the total number of pixels of the reconstructed image, j is the path number of the shear wave, and p j is the transit time of the shear wave of path j, a ij is the value of each pixel of the i-th image in path j, is the vector of slowness, is the vector of path j.

[0038] Optionally, obtaining the Young's modulus of the cornea based on the shear wave velocity image includes:

[0039] Based on the shear wave velocity image, the density ρ of the cornea and the speed V of shear wave propagation in the cornea are determined;

[0040] The Young's modulus of the cornea is obtained as E = 3ρV 2 .

[0041] Optionally, the evaluation model is trained based on the relationship between the eye biomechanical properties evaluated by the training samples and the measured eye biomechanical properties;

[0042] Among them, the evaluated ocular biomechanical properties are evaluated based on sample video data;

[0043] The measured ocular biomechanical properties are measured based on sample measurement data.

[0044] Optionally, the assessed ocular biomechanical properties are obtained by:

[0045] According to the sample video data, corneal shear wave tomography results are obtained;

[0046] According to the results of corneal shear wave tomography, the geometric model of the cornea and the parameters of Young's modulus inhomogeneity were established;

[0047] According to the Young's modulus inhomogeneity parameter, a constitutive relationship model of regional inhomogeneity corneal biomechanics is constructed;

[0048] Finite element simulation of ultrasonic indentation test process was performed based on geometric model and regional inhomogeneity corneal biomechanical constitutive relationship model to obtain the deformation information of corneal vertex.

[0049] The tangent modulus and deformation information determine the range of parameters of the corneal constitutive relationship;

[0050] The biomechanical properties of the eye were evaluated based on the range of corneal constitutive relationship parameters.

[0051] (III) Beneficial effects

[0052] The present invention relates to an eye biomechanical property evaluation method based on dynamic Scheimpflug imaging technology, the method comprising: capturing a dynamic deformation video of the cornea through a high-speed Scheimpflug camera; evaluating the eye biomechanical property of the dynamic deformation video through a pre-trained evaluation model; wherein the evaluation model is trained based on training samples; the training samples include sample corneal data of multiple users; the sample corneal data of any user includes: sample video data and sample measurement data simultaneously measured during the process of applying pressure to the cornea of ​​any user; the sample video data is captured by a high-speed Scheimpflug camera, and the sample measurement data is obtained by a corneal ultrasonic biomechanical system. The evaluation model used in the method of the present invention is trained based on the sample video data captured by the high-speed Scheimpflug camera and the sample measurement data obtained by the corneal ultrasonic biomechanical system, and can more accurately and reliably evaluate the eye biomechanical properties. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Figure 1 A schematic diagram of a flow chart of a method for evaluating ocular biomechanical properties based on dynamic Scheimpflug imaging technology provided in one embodiment of the present application;

[0054] Figure 2A schematic diagram of the structure of a corneal ultrasonic biomechanical system provided in one embodiment of the present application. DETAILED DESCRIPTION

[0055] In order to better explain the present invention and facilitate understanding, the present invention is described in detail below through specific implementation modes in conjunction with the accompanying drawings.

[0056] Existing ocular biomechanics assessment methods mainly rely on devices such as the ocular response analyzer (ORA), which have certain limitations in measurement accuracy, parameter types and real-time dynamic measurement.

[0057] In order to solve this problem, the present invention relates to a method for evaluating eye biomechanical properties based on dynamic Scheimpflug imaging technology, the method comprising: capturing a dynamic deformation video of the cornea through a high-speed Scheimpflug camera; evaluating the eye biomechanical properties of the dynamic deformation video through a pre-trained evaluation model; wherein the evaluation model is trained based on training samples; the training samples include sample corneal data of multiple users; the sample corneal data of any user includes: sample video data and sample measurement data simultaneously measured during the process of applying pressure to the cornea of ​​any user; the sample video data is captured by a high-speed Scheimpflug camera, and the sample measurement data is obtained by a corneal ultrasonic biomechanical system. The evaluation model used in the method of the present invention is trained based on sample video data captured by a high-speed Scheimpflug camera and sample measurement data obtained by a corneal ultrasonic biomechanical system, and can more accurately and reliably evaluate the eye biomechanical properties.

[0058] See also Figure 1 This embodiment provides a method for evaluating eye biomechanical properties based on dynamic Scheimpflug imaging technology. The implementation process of the method is as follows:

[0059] 101, the dynamic deformation video of the cornea is captured by a high-speed Scheimpflug camera.

[0060] 102,Evaluation of ocular biomechanical properties from dynamically deformed videos via a pre-trained evaluation model.

[0061] Among them, the biomechanical properties of the eye include but are not limited to: maximum deformation amplitude, knee flexion peak distance at maximum concavity, maximum concavity curvature radius, first applanation speed and second applanation speed.

[0062] 1. Maximum deformation amplitude (DA): the vertical distance between the maximum concave state of the cornea and the corneal vertex.

[0063] 2. PD: The distance between the two knee points when the cornea is at its maximum concave shape.

[0064] 3. Maximum concave curvature radius (HCR): The radius of curvature of the cornea when the cornea is in the maximum concave state.

[0065] 4. First applanation velocity (A1V): The instantaneous velocity of the cornea when it is applanated for the first time.

[0066] 5. Second applanation velocity (A2V): The instantaneous velocity of the cornea when the cornea is applanated for the second time.

[0067] In addition, the evaluation model is trained based on the training samples.

[0068] The training samples include sample cornea data of multiple users.

[0069] The sample corneal data of any user includes: sample video data and sample measurement data measured simultaneously during the process of applying pressure to the cornea of ​​any user. The sample video data is captured by a high-speed Scheimpflug camera, and the sample measurement data is obtained by a corneal ultrasound biomechanics system.

[0070] For example, for user A, an air pressure pulse will be sent to his cornea. During the whole process, the Corvis ST is used to capture the dynamic deformation process of the cornea under the action of the air pressure pulse through Scheimpflug imaging technology, thereby forming sample video data. That is, the sample video data includes the whole process of the cornea changing from a natural convex shape to a maximum concave shape and then returning to a natural convex shape under the action of the air pressure pulse. This process is completed within 31ms, so the sample video data contains about 140 frames of images, 4330 frames are recorded per second, and each frame is a corneal cross-sectional image with a diameter of 8.5mm. At the same time, the pressure of the air pressure pulse and the strain of the cornea are measured by the corneal ultrasonic biomechanics system, and the shear wave conditions, such as the shear wave propagation conditions, are obtained.

[0071] The evaluation model is trained based on the relationship between the eye biomechanical properties evaluated by the training samples and the measured eye biomechanical properties.

[0072] The evaluated biomechanical properties of the eye are evaluated based on sample video data.

[0073] The measured ocular biomechanical properties are measured based on sample measurement data.

[0074] For example, the consistency and repeatability between the evaluated eye biomechanical characteristics and the measured eye biomechanical characteristics are calculated, and the simulation parameters of the evaluated eye biomechanical characteristics are adjusted according to the evaluated eye biomechanical characteristics and the measured eye biomechanical characteristics, thereby adjusting the accuracy and reliability of the evaluation results of the evaluation model. When the accuracy between the evaluated eye biomechanical characteristics and the measured eye biomechanical characteristics reaches a preset threshold, the adjustment of the evaluation model training is completed. In this way, step 102 can evaluate the eye biomechanical characteristics more accurately and reliably.

[0075] The consistency and repeatability calculation process can be: using the Bland-Altman method to evaluate the consistency between the evaluated eye biomechanical properties and the measured eye biomechanical properties. The measurement repeatability of the new biomechanical parameters is evaluated by the intraclass correlation coefficient (ICC), and an ICC value greater than 0.75 indicates good repeatability.

[0076] For example, the process of adjusting the simulation parameters of the evaluated eye biomechanical characteristics based on the evaluated eye biomechanical characteristics and the measured eye biomechanical characteristics is: using the difference between the evaluated eye biomechanical characteristics and the measured eye biomechanical characteristics as the objective function, and adjusting the simulation parameters of the evaluation model.

[0077] It should be noted that both the evaluated eye biomechanical properties and the measured eye biomechanical properties are eye biomechanical properties, that is, the parameters of the two are the same, but the parameter values ​​are obtained by different methods, so the parameter values ​​may be the same or different.

[0078] Based on the above analysis, the training of the evaluation model is achieved based on the evaluated eye biomechanical properties obtained by evaluating sample video data and the measured eye biomechanical properties obtained by measuring sample measurement data. The determination process of the evaluated eye biomechanical properties and the measured eye biomechanical properties are explained below, respectively.

[0079] (I) Process of evaluating eye biomechanical properties based on sample video data

[0080] This process is implemented by the evaluation model. During the specific implementation, the sample video data can be imported into the evaluation model through the Matlab program, and the evaluation model can calculate and evaluate the biomechanical properties of the eye.

[0081] The implementation process of this step is as follows:

[0082] 201, obtaining corneal shear wave tomography results according to the sample video data.

[0083] This step can accurately extract the corneal contour and corneal area grayscale features based on the sample video data, apply quasi-steady fluid dynamics simulation technology to obtain high-precision values ​​of corneal surface pressure distribution, and then obtain corneal shear wave tomography results based on the corneal contour and corneal area grayscale features and high-precision values ​​of corneal surface pressure distribution.

[0084] Among them, the process of accurately extracting the corneal contour and corneal area grayscale features from the sample video data is: using machine learning methods to segment each frame of the sample video data, so as to obtain the quantified corneal boundary contour and corneal area grayscale features, providing parameter support for subsequent finite element simulation.

[0085] For example, a segmentation network model is trained using machine learning methods using preprocessed original images and Corvis ST dynamic corneal cross-sectional images and Pentacam static corneal cross-sectional images annotated by ophthalmologists. The corneal contour is quantitatively extracted using the segmentation network model. The image noise pattern is verified using a quantile-quantile map, and then the corneal contour is super-reconstructed and denoised using a Bayesian maximum a posteriori probability method, breaking through the limitations of the numerical results of low-resolution image space. The denoised corneal contour is statistically analyzed using a grayscale histogram, and a related curve is fitted using the grayscale histogram, and then a set of quantitative parameter features related to the grayscale of the cornea is extracted from the curve.

[0086] Under the action of the air pulse jet, the depression on the corneal surface will have a significant impact on the flow field, thereby changing the pressure distribution on the corneal surface. The process of using the quasi-steady fluid dynamics simulation technology to obtain high-precision values ​​of the corneal surface pressure distribution is as follows:

[0087] The corneal shapes at different times were selected to carry out quasi-steady fluid dynamics simulation to obtain the pressure distribution law on the corneal surface. The accuracy of the numerical simulation results was verified by experimental data to provide accurate loading conditions for subsequent finite element simulation.

[0088] For example, the dynamic corneal image contour extraction results at different times are obtained by accurately extracting the corneal contour and the grayscale characteristics of the corneal area based on the sample video data, and the high-quality CFD grids under different corneal surface morphologies are quickly generated, and the grid independence verification is performed to ensure the reliability of the simulation results. The numerical value of the micro air pulse jet flow field in the Corvis ST measurement is simulated to determine the flow field structure and the corneal surface pressure distribution law as the basis for finite element simulation.

[0089] 202. Based on the results of corneal shear wave tomography, the geometric model of the cornea and the Young's modulus inhomogeneity parameters were established.

[0090] For example, based on the results of corneal shear wave tomography, Mimics or SolidWorks software is used to establish a geometric model of the cornea according to the corneal contour.

[0091] 203. Based on the Young's modulus inhomogeneity parameter, a constitutive relationship model of regional inhomogeneous corneal biomechanics is constructed.

[0092] 204. Based on the geometric model and the regional inhomogeneity corneal biomechanical constitutive relationship model, a finite element simulation of the ultrasonic indentation test process was performed to obtain the deformation information of the corneal vertex.

[0093] For example, a rigid indenter with a radius of 2 mm is applied to the central area of ​​the cornea of ​​the geometric model, and a suitable corneal constitutive relationship model and boundary conditions are selected to perform finite element simulation of the ultrasonic indentation test process to obtain the deformation information of the corneal vertex.

[0094] The finite element simulation process is:

[0095] The simulated air pulse pressure was applied to the central area of ​​the cornea in the geometric model, and the appropriate corneal constitutive relationship model and boundary conditions were selected to perform finite element simulation of the ultrasonic indentation test process to obtain the deformation information of the corneal vertex.

[0096] 205, the tangent modulus and deformation information determine the range of corneal constitutive relationship parameters.

[0097] Among them, the tangent modulus is collected by the corneal ultrasonic biomechanical system in the process of measuring the biomechanical properties of the eye based on the sample measurement data. The collection process is detailed in the process of measuring the biomechanical properties of the eye based on the sample measurement data, and is not explained in detail here.

[0098] For example, the tangent modulus and deformation information are compared to further optimize and correct the finite element simulation until the reliability requirements are met, and finally the reasonable range of the corneal constitutive relationship parameters is determined.

[0099] 206, ocular biomechanical properties evaluated based on the range of corneal constitutive relationship parameters.

[0100] The sample video data in this process is 140 corneal cross-sectional images with a horizontal diameter of 8.5 mm collected by the Corvis ST system through Scheimpflug within 31 ms, thereby obtaining information on the deformation process of the cornea under the action of constant air pulse pressure. Based on the quantitative information of the corneal force deformation process represented by the sample video data, the biomechanical characteristic parameters of the cornea can be obtained using finite element simulation.

[0101] The above process can accurately evaluate the corneal biomechanical property parameters of corneal regional heterogeneity.

[0102] (II) The process of measuring the biomechanical properties of the eye based on the sample measurement data

[0103] This process is based on the corneal ultrasound biomechanical system.

[0104] The corneal ultrasound biomechanics system includes: an ultrasound indentation module, a shear wave tomography module, a pulse transmitter and receiver, a power amplifier, a control system, a motion displacement device, and a computer. In addition, the corneal ultrasound biomechanics system also includes a shear wave receiving transducer and a mechanical amplifier. Figure 2 Some components of the corneal ultrasound biomechanics system are shown.

[0105] in,

[0106] The ultrasonic printing module includes: an ultrasonic printing transducer and a mechanical sensor.

[0107] The shear wave tomography module includes an ultrasonic transducer and a piezoelectric vibrator.

[0108] The ultrasonic printing module is connected with the motion displacement device and the pulse transmitter and receiver respectively.

[0109] The ultrasonic transducer is connected to the pulse transmitter and receiver.

[0110] The mechanical amplifier and the pulse transmitter and receiver are respectively connected to the control system.

[0111] The piezoelectric vibrator is connected to a power amplifier.

[0112] The power amplifier is connected with the control system.

[0113] The control system is connected to the computer.

[0114] The ultrasonic transducer is connected to the mechanical sensor.

[0115] In specific implementation, the implementation of each module is as follows:

[0116] 1. Ultrasonic transducer

[0117] The ultrasonic transducer is a water-immersed micro piezoelectric transducer with a diameter of 1 mm and a frequency of 20 MHz.

[0118] The ultrasonic transducer is a circular array consisting of 16 ultrasonic transducer units.

[0119] The ultrasonic transducers are arranged in a ring at the inner edge of the cornea to obtain corneal shear data.

[0120] Ultrasonic transducers can not only achieve excellent sensitivity and high signal-to-noise ratio, but also quickly acquire shear wave signals.

[0121] The ultrasonic transducer and the ultrasonic indentation transducer are independent of each other, but through the control system, the ultrasonic indentation transducer can measure the tangent modulus of the cornea, and the ultrasonic transducer can detect the propagation of the shear wave.

[0122] 2. Piezoelectric vibrator

[0123] The piezoelectric vibrator is an array of 16 piezoelectric vibrator units. Each piezoelectric vibrator unit is connected to a unique probe. All probes are placed at the outer edge of the cornea, and the cornea vibrates through reciprocating motion to generate shear waves. The piezoelectric vibrator sends shear waves.

[0124] 3. Control system

[0125] The control system is used to control the pulse transmitter receiver, the mechanical amplifier, the motion displacement device and the ultrasonic indentation module to obtain corneal displacement data. The control system is used to control the pulse transmitter receiver, the power amplifier and the shear wave tomography module to obtain corneal shear data.

[0126] For example, the control system is used to control the motion displacement device to drive the ultrasonic indentation module to measure the strain of the overall structure of the cornea. The corneal displacement data measured by the ultrasonic indentation module is obtained through the pulse transmitter and receiver. The power amplifier is controlled to drive the shear wave tomography module to measure the shear wave transmission data in the cornea. The corneal shear data measured by the shear wave tomography module is obtained through the pulse transmitter and receiver.

[0127] Among them, the implementation process of the ultrasonic indentation module is as follows: the ultrasonic indentation module, driven by the motion displacement device, measures the strain of the overall structure of the cornea, thereby obtaining the corneal vertex pressure-displacement curve. The ultrasonic indentation module is both an indentation head that realizes the corneal indentation function and a measurement module for corneal displacement. The control system receives the changes in corneal displacement before and after compression through a pulse transmitter and receiver, and the mechanical sensor connected to the ultrasonic transducer records the pressure changes on the cornea in real time. The entire process is collected by the control system. Corneal displacement data includes corneal vertex pressure-displacement curve, pressure change, corneal displacement, corneal tangent modulus and other data.

[0128] The propagation speed of the shear wave in the cornea is affected by the elasticity of the cornea. The greater the elasticity of the cornea, the faster the propagation speed of the shear wave. Therefore, the shear wave tomography module can quickly obtain the transmission of the shear wave in the cornea. Among them, the power amplifier is used to drive the piezoelectric vibrator to work, and its vibration frequency, amplitude and other parameters can be adjusted as needed to optimize the vibration output. The probe is connected to the piezoelectric vibrator and contacts the corneal edge detection point. The probe drives the cornea to vibrate through reciprocating motion to generate shear waves. The pulse transmitter and receiver collects the shear waves propagating in the cornea received by the annular array ultrasonic transducer and transmits them to the control system and computer synchronously.

[0129] In specific implementation, the control system is responsible for the control, data acquisition and processing of each module of the entire corneal ultrasound biomechanics system, which can be based on the Labview program to achieve efficient system integration and program optimization.

[0130] 4. Computer

[0131] A computer is used for obtaining measurement data according to the corneal displacement data and the corneal shearing data.

[0132] For example, a computer is used to determine the tangent modulus of the cornea according to the corneal displacement data, reconstruct a shear wave velocity image according to the corneal shear data, obtain the Young's modulus of the cornea based on the shear wave velocity image, and obtain the measured ocular biomechanical properties according to the Young's modulus.

[0133] Since the corneal ultrasound biomechanics system also includes a shear wave receiving transducer, the implementation process of reconstructing the shear wave velocity image based on the corneal shear data is as follows:

[0134] 301. Obtain the arrival time t(x,z) of the shear wave at the shear wave receiving transducer and the transit time of the shear wave from being emitted by the ultrasonic transducer to arriving at the shear wave receiving transducer through A-ultrasound imaging.

[0135] Where x and z are coordinates in the two-dimensional medium.

[0136] For example, a piezoelectric vibrator generates a shear wave on the corneal surface, the shear wave propagates to the shear wave receiving transducer, a high-frequency receiving transducer is used for A-ultrasound imaging, and the autocorrelation method is used to accurately measure the arrival time of the shear wave, thereby obtaining the transit time from the shear wave excitation ultrasonic transducer to the shear wave receiving transducer.

[0137] 302, through the formula Determine the shear wave propagation path.

[0138] Among them, σ(x,z) is the slowness, which is the inverse of the shear wave velocity.

[0139] For example, during the propagation of shear waves between the ultrasonic transducer and the shear wave receiving transducer, the propagation direction of the shear wave may change due to the uneven distribution of the shear wave propagation velocity on the corneal surface. The shear wave velocity image is used to iteratively track the shear wave propagation path, thereby improving the quality of shear wave velocity image reconstruction. The propagation path tracking is proposed to be solved using the fast marching method. Then the tracking path is solved in reverse based on the arrival time gradient.

[0140] 303, reconstructing a shear wave velocity image according to the transit time and the shear wave propagation path.

[0141] For example, by the formula Reconstruct shear wave velocity images.

[0142] Where k is the current iteration number, i is the pixel number of the reconstructed image, N is the total number of pixels of the reconstructed image, j is the path number of the shear wave, and p j is the transit time of the shear wave of path j, a ij is the value of each pixel of the i-th image in path j, is the vector of slowness, is the vector of path j. By tracing the propagation path between each pair of ultrasonic transducers and shear wave receiving transducers, we can get the vector

[0143] For example, the propagation velocity distribution image of the shear wave on the cornea is iteratively reconstructed using the transit time and propagation path of the shear wave between transducers.

[0144] In addition, the process of obtaining the Young's modulus of the cornea based on the shear wave velocity image is as follows: based on the shear wave velocity image, determine the density ρ of the cornea and the speed V of shear wave propagation in the cornea. Obtain the Young's modulus of the cornea E=3ρV 2 .

[0145] The ocular biomechanical property evaluation method based on dynamic Scheimpflug imaging technology provided in this embodiment can more accurately and reliably evaluate the ocular biomechanical properties of diseases such as keratoconus through high-resolution imaging and analysis of multiple biomechanical parameters.

[0146] The evaluation model used in the eye biomechanical characteristics evaluation method based on dynamic Scheimpflug imaging technology provided in this embodiment is obtained by continuous training by combining sample video data captured by a high-speed Scheimpflug camera and sample measurement data obtained by a corneal ultrasound biomechanics system. The evaluation model obtained through this training can obtain more accurate evaluation results.

[0147] The dynamic deformation video captured by the Scheimpflug camera can record the dynamic deformation process of the cornea in real time. The evaluation model can dynamically evaluate the deformation process and obtain the biomechanical properties.

[0148] The ocular biomechanical property evaluation method based on dynamic Scheimpflug imaging technology provided in this embodiment can show good repeatability and reliability through multiple measurements and consistency evaluation. This embodiment relates to an ocular biomechanical property evaluation method based on dynamic Scheimpflug imaging technology, which uses a high-speed Scheimpflug camera to capture a dynamic deformation video of the cornea; the ocular biomechanical property evaluation of the dynamic deformation video is performed through a pre-trained evaluation model; wherein the evaluation model is trained based on training samples; the training samples include sample corneal data of multiple users; the sample corneal data of any user includes: sample video data and sample measurement data measured simultaneously during the process of applying pressure to the cornea of ​​any user; the sample video data is captured by a high-speed Scheimpflug camera, and the sample measurement data is obtained by a corneal ultrasonic biomechanical system. The evaluation model used in the method of this embodiment is trained based on sample video data captured by a high-speed Scheimpflug camera and sample measurement data obtained by a corneal ultrasonic biomechanical system, and can more accurately and reliably evaluate the ocular biomechanical properties.

[0149] It should be clear that the present invention is not limited to the specific configuration and processing described above and shown in the figures. For the sake of simplicity, a detailed description of the known method is omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method process of the present invention is not limited to the specific steps described and shown, and those skilled in the art can make various changes, modifications and additions, or change the order between the steps after understanding the spirit of the present invention.

[0150] It should also be noted that the exemplary embodiments mentioned in the present invention describe some methods or systems based on a series of steps or devices. However, the present invention is not limited to the order of the above steps, that is, the steps can be performed in the order mentioned in the embodiments, or in a different order from the embodiments, or several steps can be performed simultaneously.

[0151] Finally, it should be noted that the above-described embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some or all of the technical features thereof may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for evaluating ocular biomechanical properties based on dynamic Scheimpflug imaging technology, characterized in that: The method comprises: Capture the dynamic deformation video of the cornea using a high-speed Scheimpflug camera; evaluating eye biomechanical properties of the dynamic deformation video using a pre-trained evaluation model; Wherein, the evaluation model is obtained by training based on training samples; The training samples include sample corneal data of multiple users; The sample corneal data of any user includes: sample video data and sample measurement data measured simultaneously during the process of applying pressure to the cornea of ​​any user; the sample video data is captured by a high-speed Scheimpflug camera, and the sample measurement data is obtained by a corneal ultrasonic biomechanics system.

2. The method according to claim 1, characterized in that The corneal ultrasound biomechanics system includes: an ultrasound indentation module, a shear wave tomography module, a pulse transmitter and receiver, a power amplifier, a control system, a motion displacement device and a computer; The ultrasonic printing module includes: an ultrasonic printing transducer and a mechanical sensor; The shear wave tomography module comprises: an ultrasonic transducer and a piezoelectric vibrator; The ultrasonic printing module is connected to the motion displacement device and the pulse transmitter and receiver respectively; The ultrasonic transducer is connected to the pulse transmitter-receiver; The mechanical amplifier and the pulse transmitter-receiver are respectively connected to the control system; The piezoelectric vibrator is connected to the power amplifier; The power amplifier is connected to the control system; The control system is connected to the computer; The ultrasonic transducer is connected to the mechanical sensor; The control system is used to control the pulse transmitter and receiver, the mechanical amplifier, the motion displacement device and the ultrasonic indentation module to obtain corneal displacement data; and control the pulse transmitter and receiver, the power amplifier and the shear wave tomography module to obtain corneal shear data; The computer is used to obtain measurement data according to the corneal displacement data and the corneal shearing data.

3. The method according to claim 2, characterized in that The control system is used to control the motion displacement device to drive the ultrasonic indentation module to measure the strain of the overall structure of the cornea; obtain the corneal displacement data measured by the ultrasonic indentation module through the pulse transmitter and receiver; control the power amplifier to drive the shear wave tomography module to measure the shear wave transmission data in the cornea; and obtain the corneal shear data measured by the shear wave tomography module through the pulse transmitter and receiver.

4. The method according to claim 2, characterized in that: The ultrasonic transducer is a water-immersed micro piezoelectric transducer with a diameter of 1 mm and a frequency of 20 MHz; the ultrasonic transducer is a ring array composed of 16 ultrasonic transducer units; the ultrasonic transducers are arranged in a ring at the inner edge of the cornea; the ultrasonic transducer obtains corneal shear data; The piezoelectric vibrator is an array composed of 16 piezoelectric vibrator units; each piezoelectric vibrator unit is connected to a unique probe; all probes are placed at the outer edge of the cornea, and drive the cornea to vibrate through reciprocating motion to generate shear waves; the piezoelectric vibrator sends shear waves.

5. The method according to claim 2, characterized in that: The computer is used to determine the tangent modulus of the cornea according to the corneal displacement data; reconstruct a shear wave velocity image according to the corneal shear data, and obtain the Young's modulus of the cornea based on the shear wave velocity image; and obtain measured eye biomechanical properties according to the Young's modulus.

6. The method according to claim 5, characterized in that The corneal ultrasonic biomechanics system further includes: a shear wave receiving transducer; The reconstructing the shear wave velocity image according to the corneal shear data comprises: By A-ultrasound imaging, the arrival time t(x,z) of the shear wave at the shear wave receiving transducer and the transit time of the shear wave from the ultrasonic transducer to the shear wave receiving transducer are obtained; wherein x and z are coordinates in the two-dimensional medium; By formula Determine the shear wave propagation path; wherein σ(x, z) is slowness, and the slowness is the inverse of the wave velocity of the shear wave; A shear wave velocity image is reconstructed according to the transit time and the shear wave propagation path.

7. The method according to claim 6, characterized in that The reconstructing the shear wave velocity image according to the transit time and the shear wave propagation path comprises: By formula Reconstruct shear wave velocity images; Where k is the current iteration number, i is the pixel number of the reconstructed image, N is the total number of pixels of the reconstructed image, j is the path number of the shear wave, and p j is the transit time of the shear wave of path j, a ij is the value of each pixel of the i-th image in path j, is the vector of slowness, is the vector of path j.

8. The method according to claim 5, characterized in that The obtaining of the Young's modulus of the cornea based on the shear wave velocity image comprises: Based on the shear wave velocity image, determining the density ρ of the cornea and the speed V of shear wave propagation in the cornea; The Young's modulus of the cornea is obtained as E = 3ρV 2 .

9. The method according to claim 1, characterized in that: The evaluation model is trained based on the relationship between the eye biomechanical properties evaluated by the training samples and the measured eye biomechanical properties; Wherein, the evaluated eye biomechanical properties are evaluated based on the sample video data; The measured eye biomechanical properties are measured based on the sample measurement data.

10. The method according to claim 9, characterized in that The evaluated ocular biomechanical properties are obtained by the following steps: Obtaining corneal shear wave tomography results according to the sample video data; According to the corneal shear wave tomography results, a geometric model of the cornea and Young's modulus inhomogeneity parameters are established; According to the Young's modulus inhomogeneity parameter, a regional inhomogeneity corneal biomechanical constitutive relationship model is constructed; Based on the geometric model and the regional inhomogeneity corneal biomechanical constitutive relationship model, a finite element simulation of the ultrasonic indentation test process is performed to obtain deformation information of the corneal vertex; The tangent modulus and the deformation information determine the range of corneal constitutive relationship parameters; Estimated ocular biomechanical properties are obtained based on the range of corneal constitutive relationship parameters.

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