Evaluation method of ocular biomechanical properties based on dynamic Scheimpflug imaging technology

Abstract

The present invention relates to a method for evaluating ocular biomechanical properties based on dynamic Scheimpflug imaging technology. The method comprises: capturing a dynamic deformation video of the cornea using a Scheimpflug camera; and evaluating the ocular biomechanical properties of the dynamic deformation video using an evaluation model. The training samples for training the evaluation model include sample corneal data; the sample corneal data includes: sample video data and sample measurement data simultaneously measured during the process of applying pressure to the user's cornea; 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 Scheimpflug camera and the sample measurement data obtained by the corneal ultrasonic biomechanical system, and can more accurately and reliably evaluate ocular biomechanical properties.

Description

Technical Field

[0001] The present invention relates to the technical field of eye property evaluation, and in particular to a method for evaluating eye biomechanical properties 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 eye health, 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 solved

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

[0006] (2) Technical solution

[0007] In order to achieve the above objectives, 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 dynamic deformation videos of the cornea using a high-speed Scheimpflug camera;

[0010] Evaluate ocular biomechanical properties using 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 ultrasound 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 and pressing module, including: ultrasonic printing and pressing 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-receiver, the mechanical amplifier, the motion displacement device and the ultrasonic indentation module to obtain corneal displacement data; and to control the pulse transmitter-receiver, the power amplifier and the shear wave tomography module to obtain corneal shear data;

[0025] A computer is used for obtaining measurement data based on 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, driving the cornea to vibrate through reciprocating motion, generating shear waves; the piezoelectric vibrator transmits the 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 ocular biomechanical properties based on the Young's modulus.

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

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

[0032] 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 through A-ultrasound imaging; where 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 shear wave propagation path.

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

[0036] By formula Reconstruct shear wave velocity images;

[0037] Among them, 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 obtained 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] Based on the results of corneal shear wave tomography, the geometric model of the cornea and the Young's modulus inhomogeneity parameters were established;

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

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

[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] (3) Beneficial effects

[0052] The present invention relates to a method for evaluating ocular biomechanical properties based on dynamic Scheimpflug imaging technology, the method comprising: capturing a dynamic deformation video of the cornea using a high-speed Scheimpflug camera; and evaluating the ocular biomechanical properties of the dynamic deformation video using 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 the 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 ocular biomechanical properties. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Figure 1 A schematic 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 structural diagram 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 methods 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] To address this problem, the present invention relates to a method for evaluating ocular biomechanical properties based on dynamic Scheimpflug imaging technology, the method comprising: capturing a dynamic deformation video of the cornea using a high-speed Scheimpflug camera; and evaluating the ocular biomechanical properties of the dynamic deformation video using 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 ultrasound biomechanics 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 ultrasound biomechanics system, and can more accurately and reliably evaluate ocular biomechanics.

[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 this method is as follows:

[0059] 101, capturing dynamic deformation videos of the cornea using a high-speed Scheimpflug camera.

[0060] 102,Evaluation of ocular biomechanical properties from dynamic deformation 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. Peak distance of knee at maximum concavity (PD): the distance between the two knee points when the cornea is at its maximum concavity.

[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 the cornea is first applanated.

[0066] 5. Second applanation velocity (A2V): The instantaneous velocity of the cornea during the second applanation.

[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 for any user includes sample video data and sample measurement data, which are simultaneously measured during the process of applying pressure to the user's cornea. 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 is sent to their cornea. Throughout this process, the Corvis ST uses Scheimpflug imaging technology to capture the dynamic deformation of the cornea under the influence of the air pressure pulse, thereby generating sample video data. Specifically, the sample video data includes the entire process of the cornea changing from its natural convex shape to its maximum concave shape and then back to its natural convex shape under the influence of the air pressure pulse. This process is completed within 31ms, so the sample video data contains approximately 140 frames of images, recording 4330 frames per second, with each frame being an image of a corneal cross-section with a diameter of 8.5mm. Simultaneously, the pressure of the air pressure pulse and the strain of the cornea are measured using the corneal ultrasound biomechanics system, and shear wave conditions, such as shear wave propagation, are also 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 obtained based on sample measurement data.

[0074] For example, the consistency and repeatability between the assessed ocular biomechanical properties and the measured ocular biomechanical properties are calculated, and the simulation parameters of the assessed ocular biomechanical properties are adjusted based on the assessed ocular biomechanical properties and the measured ocular biomechanical properties, thereby adjusting the accuracy and reliability of the assessment model's assessment results. When the accuracy between the assessed ocular biomechanical properties and the measured ocular biomechanical properties reaches a preset threshold, the adjusted assessment model training is completed. In this way, step 102 can more accurately and reliably assess ocular biomechanical properties.

[0075] The consistency and repeatability calculation process can be as follows: the consistency between the assessed and measured ocular biomechanical properties is evaluated using the Bland-Altman method. The repeatability of the measurement of the new biomechanical parameters is evaluated using the intraclass correlation coefficient (ICC). 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 and measured ocular biomechanical properties are ocular biomechanical properties, that is, the parameters of the two are the same, but the parameter values ​​are obtained through 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 the sample video data and the measured eye biomechanical properties obtained by measuring the sample measurement data. The determination process of the evaluated eye biomechanical properties and the measured eye biomechanical properties are explained below.

[0079] (1) 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 calculates and evaluates the biomechanical properties of the eye.

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

[0082] 201. Obtain corneal shear wave tomography results based on 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 numerical values ​​of the corneal surface pressure distribution, and then obtain the corneal shear wave tomography results based on the corneal contour and corneal area grayscale features and the high-precision numerical values ​​of the 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 machine learning approach was used to train a segmentation network model using preprocessed raw images and Corvis ST dynamic corneal cross-sectional images and Pentacam static corneal cross-sectional images annotated by ophthalmologists. The segmentation network model was then used to quantitatively extract the corneal contour. Image noise patterns were verified using quantile-quantile plots. A Bayesian maximum a posteriori probability method was then used to perform super-resolution reconstruction and simultaneous noise reduction on the corneal contour, overcoming the limitations of low-resolution logarithmic results in image space. A grayscale histogram was then generated for the denoised corneal contour, and a correlation curve was fitted using the grayscale histogram. A set of quantitative parameter features related to the corneal grayscale was then 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 obtaining high-precision numerical values ​​of the corneal surface pressure distribution using quasi-steady fluid dynamics simulation technology in this step 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, by accurately extracting the corneal contour and the grayscale characteristics of the corneal region from sample video data, we can obtain dynamic corneal image contour extraction results at different times. This allows for the rapid generation of high-quality CFD meshes for different corneal surface morphologies, and mesh independence verification is performed to ensure the reliability of the simulation results. We also simulate the flow field of a micro-air pulse jet during Corvis ST measurements, determining the flow field structure and corneal surface pressure distribution patterns as the basis for finite element simulations.

[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, a geometric model of the cornea is established according to the corneal contour using Mimics or SolidWorks software.

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

[0092] 204. Based on the geometric model and the regional heterogeneous 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 in 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 is applied to the central area of ​​the cornea in the geometric model, and the appropriate 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.

[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 during the process of measuring the eye biomechanical properties based on the sample measurement data. The collection process is detailed in the process of measuring the eye biomechanical properties 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 were evaluated based on the range of corneal constitutive relationship parameters.

[0100] The sample video data used in this process consists of 140 images of a corneal cross-section with a horizontal diameter of 8.5 mm captured by the Corvis ST system using Scheimpflug within 31 milliseconds. This data captures the corneal deformation process under constant air pulse pressure. Based on the quantitative information about the corneal deformation process captured in this sample video data, finite element simulations can be used to determine the biomechanical characteristics of the cornea.

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

[0102] (2) 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 biomechanics 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 Shows some components of the corneal ultrasound biomechanics system.

[0105] in,

[0106] The ultrasonic printing and pressing module includes: an ultrasonic printing and pressing 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 to 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 to 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 ring array consisting of 16 ultrasonic transducer units.

[0119] 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 obtain 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, while the ultrasonic transducer can detect the propagation of shear waves.

[0122] 2. Piezoelectric vibrator

[0123] The piezoelectric vibrator is an array of 16 piezoelectric vibrator units. Each unit is connected to a single probe. All probes are placed at the outer edge of the cornea. Their reciprocating motion vibrates the cornea, generating shear waves. The piezoelectric vibrator transmits shear waves.

[0124] 3. Control system

[0125] The control system is used to control the pulse transmitter and receiver, mechanical amplifier, motion displacement device and ultrasonic indentation module to obtain corneal displacement data. It also controls the pulse transmitter and receiver, power amplifier and 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 strain on the overall corneal structure. The pulse transmitter and receiver acquires corneal displacement data measured by the ultrasonic indentation module. The power amplifier is controlled to drive the shear wave tomography module to measure shear wave transmission data in the cornea. The pulse transmitter and receiver acquires corneal shear data measured by the shear wave tomography module.

[0127] The ultrasonic indentation module is implemented as follows: Driven by the motion displacement device, the ultrasonic indentation module measures the strain of the entire corneal structure, thereby obtaining a corneal vertex pressure-displacement curve. The ultrasonic indentation module is both an indentation head that implements the corneal indentation function and a module for measuring corneal displacement. The control system receives the changes in corneal displacement before and after compression through a pulse transmitter and receiver, and a 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 data such as the corneal vertex pressure-displacement curve, pressure changes, corneal displacement, and the tangent modulus of the cornea.

[0128] The propagation speed of shear waves in the cornea is affected by the elasticity of the cornea. The greater the elasticity of the cornea, the faster the shear wave propagation speed. Therefore, the shear wave tomography module can quickly obtain the transmission of shear waves in the cornea. Among them, the power amplifier is used to drive the piezoelectric vibrator to work. 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, thereby generating 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 synchronously to the control system and computer.

[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. It 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 based on the corneal displacement data and the corneal shearing data.

[0132] For example, a computer is used to determine the tangent modulus of the cornea based on 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. Measured ocular biomechanical properties are obtained based on 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 the ultrasonic transducer to the shear wave receiving transducer through A-ultrasound imaging.

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

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

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

[0138] Where 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 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 based on the transit time and the shear wave propagation path.

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

[0142] Among them, 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 the 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. The Young's modulus of the cornea is obtained as E=3ρV 2 .

[0145] The ocular biomechanical properties assessment method based on dynamic Scheimpflug imaging technology provided in this embodiment can more accurately and reliably assess 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 biomechanical properties.

[0148] The ocular biomechanical property evaluation method based on dynamic Scheimpflug imaging technology provided in this embodiment can demonstrate good repeatability and reliability through multiple measurements and consistency evaluations. 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; uses a pre-trained evaluation model to evaluate the ocular biomechanical properties of the dynamic deformation video; 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 ultrasound biomechanics 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 ultrasound biomechanics system, and can more accurately and reliably evaluate the ocular biomechanics.

[0149] It should be understood that the present invention is not limited to the specific configurations and processes described above and illustrated in the figures. For the sake of brevity, a detailed description of known methods is omitted. In the above embodiments, several specific steps are described and illustrated as examples. However, the method of the present invention is not limited to the specific steps described and illustrated. Those skilled in the art may make various changes, modifications, and additions, or change the order of the steps after understanding the spirit of the present invention.

[0150] It should also be noted that the exemplary embodiments described herein describe methods or systems based on a series of steps or devices. However, the present invention is not limited to the order of the steps described above. In other words, the steps may be performed in the order described in the embodiments, or in a different order, or several steps may be performed simultaneously.

[0151] Finally, it should be noted that the embodiments described above are only used to illustrate the technical solutions of the present invention, rather than to limit them. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some or all of the technical features therein. 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 dynamic deformation videos 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 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 ultrasound biomechanics system; 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 indentation module includes: an ultrasonic indentation transducer and a mechanical sensor; The shear wave tomography module includes: 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 sensor 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 sensor, 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 based on the corneal displacement data and the corneal shearing data.

2. The method according to claim 1, 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.

3. The method according to claim 1, characterized in that 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; 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, driving the cornea to vibrate through reciprocating motion, generating shear waves; the piezoelectric vibrator transmits shear waves.

4. The method according to claim 1, wherein 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.

5. The method according to claim 4, characterized in that The corneal ultrasonic biomechanics system further includes: a shear wave receiving transducer; The reconstructing of the shear wave velocity image according to the corneal shear data comprises: Obtaining, 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 time it is emitted from the ultrasonic transducer to the time it reaches the shear wave receiving transducer; wherein x and z are coordinates in a 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.

6. The method according to claim 5, 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; Among them, 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.

7. The method according to claim 4, characterized in that The obtaining of the Young's modulus of the cornea based on the shear wave velocity image comprises: Determining the density ρ of the cornea and the speed V of shear wave propagation in the cornea based on the shear wave velocity image; The Young's modulus of the cornea is obtained as E = 3ρV 2 .

8. The method according to claim 4, 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 ocular biomechanical properties are measured based on the sample measurement data.

9. The method according to claim 8, characterized in that The biomechanical properties of the eye are evaluated by the following steps: Obtaining corneal shear wave tomography results based on the sample video data; Establishing a corneal geometric model and Young's modulus inhomogeneity parameters according to the corneal shear wave tomography results; According to the Young's modulus heterogeneity parameter, a regional heterogeneous corneal biomechanical constitutive relationship model is constructed; Performing finite element simulation of an ultrasonic indentation test process based on the geometric model and the regional inhomogeneity corneal biomechanical constitutive relationship model to obtain deformation information of the corneal vertex; The tangent modulus and the deformation information determine the range of corneal constitutive relationship parameters; The estimated biomechanical properties of the eye are obtained according to the range of the corneal constitutive relationship parameters.

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