A corneal refractive surgery system and an integrated corneal refractive surgery device

Abstract

This invention relates to the field of refractive surgery technology, and discloses a corneal refractive surgery system and an integrated corneal refractive surgery device. The system includes: a data acquisition module for acquiring preoperative ocular measurement data; a preoperative multi-source data processing module for converting various sets of preoperative ocular measurement data to the same planned coordinate system and converting them into multiple sets of higher-order aberration height distribution data; and for generating preoperative target correction distribution data based on the multiple sets of higher-order aberration height distribution data and lower-order refractive correction baseline distribution data; an intraoperative data processing module for mapping the preoperative target correction distribution data to the intraoperative execution coordinate system to obtain intraoperative target correction distribution data; and a feedback correction module for acquiring postoperative distribution data and comparing it with the preoperative target correction distribution data, updating preset parameters in the corneal refractive surgery system based on the comparison results. This invention effectively improves the correction accuracy of corneal refractive surgery.

Description

Technical Field

[0001] This invention relates to the field of refractive correction technology, specifically to a corneal refractive surgery system and an integrated corneal refractive surgery device. Background Technology

[0002] Corneal refractive surgery is currently the mainstream ophthalmic treatment technology for correcting refractive errors such as myopia and astigmatism. It is widely used due to its advantages of precision, minimal invasiveness, and rapid recovery. Mainstream procedures include femtosecond LASIK, LASIK, and excimer laser surgery. The surgical process includes preoperative examination, surgical planning, intraoperative laser execution, and postoperative follow-up.

[0003] However, the inventors discovered that existing corneal refractive surgery systems generally suffer from technical flaws such as a fragmented process, lack of data interoperability, and open-loop operation. The inconsistent data standards and varying dimensions of various preoperative testing devices prevent the fusion of multi-source ocular data. This results in high-quality visual parameters such as higher-order aberrations and corneal morphology being used only for preoperative assessment and difficult to incorporate into surgical parameter planning, easily leading to problems such as redundant calculations of low-order corrections and high-order compensations, and correction deviations. Furthermore, existing corneal refractive surgery systems can only perform unidirectional calculations and cannot continuously update planning algorithms and parameters based on postoperative clinical data, making it difficult to form a complete closed loop of preoperative planning, intraoperative execution, and continuous optimization based on postoperative feedback. Summary of the Invention

[0004] This invention provides a corneal refractive surgery system and an integrated corneal refractive surgery device to solve the problem that existing corneal refractive surgery systems cannot achieve collaborative planning of multi-source eye data and lack an integrated closed-loop optimization mechanism for preoperative, intraoperative, and postoperative procedures, resulting in limited accuracy of personalized refractive correction.

[0005] In a first aspect, the present invention provides a corneal refractive surgery system, the system comprising: The data acquisition module is used to collect preoperative ocular measurement data from multiple different preoperative testing devices, with one preoperative testing device corresponding to a set of preoperative ocular measurement data. The preoperative multi-source data processing module is used to convert the preoperative ocular measurement data of each group to the same planned coordinate system, and to convert the preoperative ocular measurement data of each group into multiple groups of high-order aberration height distribution data according to the data type; it is also used to generate preoperative target correction distribution data based on multiple groups of high-order aberration height distribution data and the calculated low-order refractive correction baseline distribution data. The intraoperative data processing module is used to map preoperative target correction distribution data to the intraoperative execution coordinate system through iris biometric matching to obtain intraoperative target correction distribution data; it is also used to determine laser scanning data based on the intraoperative target correction distribution data. The feedback correction module is used to collect postoperative distribution data and compare it with preoperative target correction distribution data, and update the preset parameters in the corneal refractive surgery system based on the comparison results.

[0006] In one optional implementation, the preoperative multi-source data processing module includes: The multi-source coordinate transformation unit is used to transform preoperative ocular measurement data from various groups to the same planned coordinate system by performing transformation operations; The high-order aberration height distribution data generation unit is used to construct two-dimensional spatial distribution functions according to the data type of each set of preoperative ocular measurement data unified under the same planning coordinate system, and remove the low-order refractive components contained in each two-dimensional spatial distribution function to generate multiple sets of high-order aberration height distribution data. The low-order refractive correction baseline distribution data generation unit is used to calculate low-order refractive correction baseline distribution data based on refractive parameters in preoperative ocular measurement data. The preoperative target correction distribution data generation unit is used to fuse multiple sets of high-order aberration height distribution data to determine the fused high-order aberration height distribution data; based on the fused high-order aberration height distribution data, the tissue removal compensation amount is determined; based on the tissue removal compensation amount, the low-order refractive correction basic distribution data, and the preset empirical compensation amount, the preoperative target correction distribution data is determined.

[0007] In one optional implementation, the high-order aberration height distribution data generation unit includes at least one of the following sub-units: The first transformation subunit is used to construct an aspherical surface shape function based on the first data type, and remove the low-order refractive components in the aspherical surface shape function to generate high-order aberration height distribution data of the first data type; the aspherical surface shape function is used as a two-dimensional spatial distribution function; the first data type includes at least one of the following: corneal Q value, conic constant, eccentricity; The second transformation subunit is used to construct a height surface function based on the second data type, and remove the low-order refractive components in the height surface function to generate high-order aberration height distribution data of the second data type; the height surface function is used as a two-dimensional spatial distribution function; the second data type includes at least one of the following: corneal height map, sagittal map, and three-dimensional point cloud of corneal height; The third transformation subunit is used to construct an optical surface shape function based on the third data type, and remove the low-order refractive components in the optical surface shape function to generate high-order aberration height distribution data of the third data type; the optical surface shape function is used as a two-dimensional spatial distribution function; the third data type includes Zernike surface shape coefficients; The fourth transformation subunit is used to construct an equivalent corneal height profile function based on the fourth data type, and to remove low-order refractive components from the equivalent corneal height profile function to generate high-order aberration height distribution data of the fourth data type; the equivalent corneal height profile function is used as a two-dimensional spatial distribution function; the fourth data type includes wavefront aberrations; The fifth transformation subunit is used to generate high-order aberration height distribution data obtained from high-order aspherical sources, based on high-order aspherical surface shape functions and by removing low-order refractive components from the high-order aspherical surface shape functions.

[0008] In one alternative implementation, the intraoperative data processing module includes: The preoperative iris template construction unit is used to acquire preoperative eye images and construct a preoperative iris template based on the first iris biometric features in the preoperative eye images. The iris registration unit is used to acquire intraoperative ocular images and construct an intraoperative iris template based on the second iris biometrics in the intraoperative ocular images. The intraoperative iris template is matched with the preoperative iris template to obtain the ocular transformation relationship. Based on the ocular transformation relationship, the preoperative target correction distribution data is mapped to the intraoperative execution coordinate system to obtain the intraoperative target correction distribution data. The cutting surface generation unit is used to modify the intraoperative target correction distribution data by combining intraoperative corneal deformation information, and generate surgical cutting data and boundary contour data; The scanning point discrete unit is used to discretize the surgical cutting data and boundary contour data to generate laser scanning data.

[0009] In one alternative implementation, the preoperative iris template construction unit includes: The reference point detection subunit is used to acquire preoperative ocular images and detect reference point data from the preoperative ocular images; the reference point data includes the pupil center, limbus center, corneal apex, or corneal reflective point; The center determines the sub-unit, which is used to calculate the preoperative treatment center based on reference point data and a preset weight coefficient, and to establish a preoperative planning coordinate system with the preoperative treatment center as the origin. The preoperative template generation subunit is used to extract iris features from preoperative eye images as the first iris biometric feature to construct a preoperative iris template. The iris normalization subunit is used to map the iris region in the preoperative eye image from Cartesian coordinates to a polar coordinate normalized space to generate a normalized preoperative iris image. The preoperative planning coordinate system and the normalized preoperative iris image are output to the iris registration unit for template matching and coordinate mapping.

[0010] In one alternative implementation, the iris registration unit includes: The intraoperative image acquisition subunit is used to acquire intraoperative ocular images and extract iris features from the intraoperative ocular images as secondary iris biometrics. The intraoperative template generation subunit is used to construct an intraoperative iris template based on the second iris biometrics and to perform polar coordinate normalization on the intraoperative iris region to generate a normalized intraoperative iris image. The transformation subunit is used to match the preoperative iris template corresponding to the normalized preoperative iris image with the intraoperative iris template corresponding to the normalized intraoperative iris image to obtain the eyeball rotation angle, which is then used to determine the eyeball transformation relationship. The distribution mapping subunit is used to construct a coordinate transformation matrix based on the eye rotation angle. Relying on the preoperative planning coordinate system, it maps the preoperative target correction distribution data to the intraoperative execution coordinate system to obtain the intraoperative target correction distribution data.

[0011] In one optional implementation, the iris registration unit further includes at least one of the following sub-units: The correction subunit is used to rotate and correct the preoperatively planned astigmatic axis and the direction angles of higher-order compensation in each direction based on the eye rotation angle, so as to obtain the intraoperative astigmatic axis and the intraoperative higher-order compensation direction angle. The confidence subunit is used to calculate the registration confidence and registration residual of the preoperative iris template and the intraoperative iris template. The safety interlock is triggered when any of the following conditions are met: the registration confidence is lower than the preset minimum registration confidence threshold, the registration residual is higher than the preset maximum allowable registration residual, or the eye rotation angle is higher than the preset maximum allowable eye rotation angle. The error recording and attribution unit is used to collect and store the intraoperative parameter set and bind the intraoperative parameter set with the case data; when refractive deviation occurs after surgery, the postoperative error source is traced based on the stored intraoperative parameter set.

[0012] In one optional implementation, the preoperative target correction distribution data generation unit further includes: The conflict detection subunit is used to calculate the difference between any two sets of high-order aberration height distribution data; when the maximum difference exceeds the preset conflict threshold, it is determined that there is a multi-source data conflict. The conflict handling subunit is used to execute a preset control strategy when a multi-source data conflict is detected. The preset control strategy includes one or more of the following: reducing the weight of low-confidence sources, wavefront priority, corneal height priority, freeform surface priority, and depth priority. The constraint control subunit is used to set the upper limit constraint of the higher-order compensation amplitude and the smoothness constraint of the treatment distribution gradient, so as to limit the maximum value of the final higher-order compensation and the steepness of the distribution. The interactive confirmation subunit is used to display any parameter generated by the corneal refractive surgery system to the user interface; after receiving confirmation instructions from the doctor, it locks all parameters and generates an execution log.

[0013] In one alternative implementation, the feedback correction module includes: The postoperative data acquisition unit is used to collect postoperative distribution data, which includes at least one of the following: postoperative corneal height, postoperative wavefront aberration, postoperative refractive power, and patient's subjective visual quality. The residual calculation unit is used to compare the postoperative distribution data with the preoperative target correction distribution data, calculate the height residual, wavefront residual, and refractive residual, and construct a comprehensive loss function. The parameter iteration update unit is used to update the multi-source data fusion weights, higher-order compensation ratios, and preset empirical compensation amounts in the preoperative multi-source data processing module based on the comprehensive loss function.

[0014] In a second aspect, the present invention provides an integrated corneal refractive surgery device, the device comprising: A corneal refractive surgery system according to the first aspect above or any corresponding embodiment thereof; The laser scanning module communicates with the corneal refractive surgery system to receive laser scanning data output by the system and output a laser beam based on the data.

[0015] The beneficial effects of this invention are as follows: This invention constructs a corneal refractive surgery system comprising a data acquisition module, a preoperative multi-source data processing module, an intraoperative data processing module, and a feedback correction module. It unifies multi-device ocular measurement data into a single planned coordinate system, constructs a basic low-order refractive correction distribution and multiple high-order aberration height distributions, and fuses them to obtain the preoperative target correction distribution. It utilizes iris biometric matching to accurately map the preoperative planned coordinate system to the intraoperative execution coordinate system and introduces postoperative data comparison to achieve iterative optimization of system parameters. This invention overcomes the shortcomings of existing technologies, such as difficulty in interoperating and fusing multi-source detection data, insufficient utilization of high-order aberrations, disconnect between preoperative and intraoperative coordinate systems, limited intraoperative alignment accuracy, and fragmented preoperative-intraoperative-postoperative workflows that prevent closed-loop optimization, effectively improving the corrective accuracy of corneal refractive surgery. Attached Figure Description

[0016] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0017] Figure 1 This is a schematic diagram of the structure of a corneal refractive surgery system according to an embodiment of the present invention; Figure 2 This is another schematic diagram of the corneal refractive surgery system according to an embodiment of the present invention. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0019] It is understood that before using the technical solutions disclosed in the various embodiments of the present invention, users should be informed of the types, scope of use, and usage scenarios of the personal information involved in the present invention and their authorization should be obtained in accordance with relevant laws and regulations through appropriate means.

[0020] The terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this invention, "a plurality of" or "multiple" means two or more, unless otherwise explicitly specified.

[0021] Example 1 Preoperative examinations for patients typically involve multiple devices, including corneal topography, anterior segment OCT, corneal tomography, wavefront aberrometer, iris imaging, and pupil measurement. Different devices output different data types, coordinate centers, sampling apertures, coordinate directions, symbol conventions, units, and confidence levels.

[0022] For example, a corneal topography system can output corneal curvature maps, corneal height maps, Q values, limbal center, pupil center, etc.; anterior segment OCT can output corneal anterior surface height, posterior surface height, corneal thickness maps, central corneal thickness, etc.; a wavefront aberrometer can output whole-eye wavefront aberrations or corneal wavefront aberrations; an iris camera or intraoperative microscopic imaging system can output iris texture, pupil boundary, corneal reflective points, and scleral vascular features.

[0023] However, existing corneal refractive surgery systems suffer from end-to-end technical deficiencies, making it difficult to achieve multi-source data fusion planning, high-precision intraoperative alignment, and closed-loop optimization correction, thus failing to meet the needs of personalized, high-precision surgery. Current surgeries rely solely on conventional low-order refractive parameters to plan correction schemes, failing to effectively integrate multi-source high-order data such as corneal height, asphericity, Zernike facial shape coefficient, and wavefront aberrations. Furthermore, various detection devices lack unified coordinate and quantification transformation mechanisms, resulting in low data utilization and insufficient ability to correct high-order aberrations and freeform surfaces. Simultaneously, traditional intraoperative alignment methods lack a comprehensive coordinate transformation system for preoperative planning and intraoperative execution, relying solely on conventional point positioning, which cannot achieve precise registration of high-order compensation and astigmatism axes, easily leading to intraoperative alignment deviations. Moreover, existing technologies lack differentiated ablation correction logic for different procedures such as femtosecond LASIK, LASIK, and excimer laser, making it difficult to adapt to the deformation compensation requirements of different procedures, and laser scanning execution lacks the ability to adapt to complex curved surfaces. Ultimately, the disconnect between preoperative planning, intraoperative registration, laser execution, and postoperative follow-up data makes it impossible to achieve stratified error tracing and iterative optimization throughout the entire process, severely limiting the personalized corrective accuracy of corneal refractive surgery.

[0024] Therefore, this embodiment provides a corneal refractive surgery system that can realize a complete technical chain from preoperative multi-source detection, personalized correction planning, intraoperative alignment, laser scanning execution to postoperative feedback optimization. Figure 1 This is a schematic diagram of the structure of a corneal refractive surgery system according to an embodiment of the present invention, as shown below. Figure 1 As shown, the system includes: a data acquisition module, a preoperative multi-source data processing module, an intraoperative data processing module, and a feedback correction module, as detailed below.

[0025] The data acquisition module is used to collect preoperative ocular measurement data from multiple different preoperative testing devices, with one preoperative testing device corresponding to a set of preoperative ocular measurement data.

[0026] Preoperative testing equipment includes various devices such as corneal topography, anterior segment OCT, wavefront aberration analyzer, and aspheric parameter measurement equipment. The data acquisition module interfaces with these multiple preoperative testing devices to simultaneously acquire preoperative ocular measurement data output by each device. Each set of preoperative ocular measurement data represents data obtained from different preoperative testing devices examining the same target subject.

[0027] The preoperative multi-source data processing module is used to convert the preoperative ocular measurement data of each group to the same planned coordinate system, and to convert the preoperative ocular measurement data of each group into multiple groups of high-order aberration height distribution data according to the data type; it is also used to generate preoperative target correction distribution data based on multiple groups of high-order aberration height distribution data and the calculated low-order refractive correction baseline distribution data.

[0028] The preoperative multi-source data processing module standardizes and unifies multi-source preoperative ocular measurement data, transforming raw preoperative ocular measurements from different devices and coordinate systems into a unified preoperative planning coordinate system. Simultaneously, it generates multiple sets of independent high-order aberration height distribution data based on data type, covering various high-order features such as corneal height, asphericity, Zernike aberration, wavefront aberration, and freeform surface high-order information. This module also simultaneously calculates low-order refractive correction baseline distribution data, such as myopia, hyperopia, and regular astigmatism data, and fuses and weights these data with multiple sets of high-order aberration height distribution data to ultimately generate preoperative target correction distribution data that balances conventional refractive correction with personalized high-order visual quality optimization, thus completing personalized and precise preoperative planning.

[0029] The intraoperative data processing module is used to map preoperative target correction distribution data to the intraoperative execution coordinate system through iris biometric matching to obtain intraoperative target correction distribution data; it is also used to determine laser scanning data based on intraoperative target correction distribution data.

[0030] The intraoperative data processing module is used to achieve high-precision intraoperative alignment and laser execution data generation. By collecting iris biometrics in the preoperative and intraoperative stages, it constructs the feature matching relationship between the preoperative iris template and the intraoperative iris template, solves the transformation relationship of eyeball translation, rotation, and scaling, and accurately maps the preoperative target correction distribution data under the preoperative planning coordinate system to the intraoperative execution coordinate system to obtain the intraoperative target correction distribution data after posture alignment.

[0031] The feedback correction module is used to collect postoperative distribution data and compare it with preoperative target correction distribution data, and update the preset parameters in the corneal refractive surgery system based on the comparison results.

[0032] The feedback correction module is used to achieve closed-loop optimization and iteration after surgery. It collects postoperative distribution data such as corneal morphology, refractive residuals, higher-order aberrations, and corneal thickness, and performs a comprehensive comparative analysis with preoperative target correction distribution data and intraoperative execution parameters. Based on the comparison results, it dynamically updates preset parameters such as system weight parameters, preset experience compensation amount, higher-order fusion coefficient, and registration threshold, so that the system can continuously iterate and optimize for different ocular features and different surgical procedures, further improving the correction accuracy of subsequent surgeries.

[0033] This invention constructs a corneal refractive surgery system comprising a data acquisition module, a preoperative multi-source data processing module, an intraoperative data processing module, and a feedback correction module. It unifies multi-device ocular measurement data into a single planned coordinate system, separately constructs a low-order refractive correction baseline distribution and multiple high-order aberration height distributions, and fuses them to obtain the preoperative target correction distribution. It utilizes iris biometric matching to accurately map the preoperative planned coordinate system to the intraoperative execution coordinate system and introduces postoperative data comparison to achieve iterative optimization of system parameters. This invention overcomes the shortcomings of existing technologies, such as difficulty in interoperating and fusing multi-source detection data, insufficient utilization of high-order aberrations, disconnect between preoperative and intraoperative coordinate systems, limited intraoperative alignment accuracy, and fragmented preoperative-intraoperative-postoperative workflows that cannot be optimized in a closed loop, effectively improving the corrective accuracy of corneal refractive surgery.

[0034] Example 2 Current corneal refractive surgery suffers from numerous systemic deficiencies across the entire process, from personalized planning and intraoperative alignment to laser execution and postoperative optimization. Current femtosecond LASIK, LASIK, and excimer laser surgery systems primarily rely on low-order refractive parameters such as spherical, cylindrical, and axial dimensions for surgical planning, enabling only routine refractive correction. They fail to fully utilize higher-order aberrations, corneal asphericity, freeform morphology, and wavefront data, resulting in limited personalized correction capabilities. Furthermore, preoperative planning, intraoperative execution, and postoperative recovery are disconnected, lacking a closed-loop iterative optimization mechanism. The corneal topography, anterior segment OCT, and wavefront aberrometers used clinically are mostly independent detection devices. The data lacks unified coordinate transformation, aperture matching, and symbol calibration rules, and a universally applicable intermediate data representation has not been established. Consequently, multi-source detection data is only used for auxiliary diagnosis and cannot be deeply involved in the precise calculation of ablation depth, lens morphology, laser path, and energy distribution, resulting in low data utilization. Furthermore, existing Q-value and aspherical guidance technologies are only suitable for rotationally symmetric corneal morphologies and cannot correct asymmetric higher-order aberrations such as coma and cloverleaf aberrations. They also struggle to separate lower-order refractive components, easily leading to conflicts with basic correction parameters. Traditional wavefront guidance methods suffer from mixed use of physical quantities, failing to accurately convert optical wavefront aberrations into geometric ablation depths. Additionally, the measurement aperture, coordinate center, and surgical planning system are mismatched, easily causing higher-order correction deviations. Regarding intraoperative alignment, existing methods using pupil, corneal reflection points, and simplified iris localization lack a unified coordinate transformation system spanning preoperative examination, planning, and execution. This makes it difficult to meet the high-precision alignment requirements of higher-order compensation, freeform surface correction, and astigmatism axis, and intraoperative registration errors cannot be effectively traced and analyzed. At the laser execution level, traditional scanning paths are only suitable for regular corrected facial features and cannot adapt to complex treatment patterns with localized higher-order compensation and non-uniform energy distribution. They also lack trajectory calibration and error compensation mechanisms adapted to high-speed composite scanning hardware. Meanwhile, the existing system has incomplete intraoperative data recording. Postoperative follow-up data such as refractive residuals, corneal morphology, and visual quality cannot be accurately linked to and traced back to preoperative planning, intraoperative registration, and laser execution logs. It is difficult to differentiate the errors caused by planning, registration, execution, and tissue response, and it is impossible to form a quantifiable and iterative full-process optimization closed loop, which restricts the correction accuracy of refractive surgery and the improvement of postoperative visual quality.

[0035] Therefore, this application also provides an embodiment of a corneal refractive surgery system for processing data from femtosecond LASIK surgeries. Figure 2 This is a schematic diagram of the structure of a corneal refractive surgery system according to an embodiment of the present invention, as shown below. Figure 2 As shown, the system includes: a data acquisition module, a preoperative multi-source data processing module, an intraoperative data processing module, and a feedback correction module, as detailed below.

[0036] The data acquisition module is used to collect preoperative ocular measurement data from multiple different preoperative testing devices, with one preoperative testing device corresponding to a set of preoperative ocular measurement data.

[0037] The anterior corneal surface curvature K1, corneal Q-value Q0, target or measured corneal height map Hraw, limbal center, and pupil center of the target subject are obtained using a corneal topography instrument; the anterior corneal surface height, posterior corneal surface height, corneal thickness map, and central corneal thickness of the target subject are obtained using an anterior segment OCT; the whole-eye wavefront aberration M(x,y) or corneal wavefront aberration of the target subject is obtained using a wavefront aberrometer; and the preoperative iris image of the target subject is obtained using an iris camera.

[0038] The preoperative multi-source data processing module is used to convert the preoperative ocular measurement data of each group to the same planned coordinate system, and to convert the preoperative ocular measurement data of each group into multiple groups of high-order aberration height distribution data according to the data type; it is also used to comprehensively determine the preoperative target correction distribution data based on multiple groups of high-order aberration height distribution data and the calculated low-order refractive correction baseline distribution data.

[0039] In some optional implementations, the preoperative multi-source data processing module includes: a multi-source coordinate transformation unit, a high-order aberration height distribution data generation unit, a low-order refractive correction basic distribution data generation unit, and a preoperative target correction distribution data generation unit.

[0040] The multi-source coordinate transformation unit is used to transform preoperative ocular measurement data from various groups to the same planned coordinate system by performing transformation operations.

[0041] The system first establishes a preoperative planning coordinate system Op-Xp-Yp. Op represents the preoperative planned treatment center, with the Xp and Yp axes located in the tangent plane of the anterior corneal surface, and the Zp axis along the corneal depth direction. The preoperative treatment center O can be determined by the corneal apex, pupil center, corneal reflective point, limbal center, visual axis reference point, doctor-designated point, or a weighted combination thereof.

[0042] Let the diameter of the optical region be S and the radius of the optical region be a, then: ; Where 'a' represents the radius of the optical zone in millimeters, and 'S' represents the diameter of the optical zone in millimeters.

[0043] For any point (x, y), define the radial distance r: ; Where r represents the radial distance from the point to the preoperative treatment center, in millimeters.

[0044] Define normalized aperture coordinates : ; in, Represents the normalized aperture coordinates.

[0045] Define azimuth angle : ; in, The azimuth of the point is represented by atan2(y,x), which represents the arctangent function that takes quadrant information into account.

[0046] Effective computing area Defined as: ; in, This indicates the area within the optical region that participates in the compensation calculation.

[0047] For preoperative ocular measurement data from the i-th type of preoperative testing device (where i represents any type of preoperative testing device capable of providing original coordinates), let its original coordinates be (u i ,v i The preoperative surgical planning coordinates are unified as (x, y). The system unifies them to the Op-Xp-Yp coordinate system through coordinate transformation.

[0048] One form of coordinate transformation is: ; ; in, This represents the scaling factor of the i-th type of data relative to the surgical planning coordinate system; Indicates the rotation angle; Indicates the translation amount in the X direction; This represents the translation amount in the Y direction.

[0049] It can also be written in matrix form: ; The above parameters can be obtained by registering iris texture, scleral vessels, corneal limbus, pupillary boundary, corneal apex, corneal reflective point, visual axis positioning point, or intraoperative image features.

[0050] To read the original preoperative ocular measurements at a unified coordinate point (x, y), the system can also use inverse mapping: ; in, This represents the inverse transformation from the unified preoperative surgical planning coordinate system to the coordinate system of the i-th type of preoperative detection equipment. Through this inverse mapping, the system can interpolate or reconstruct surfaces from the original preoperative ocular measurement data on the unified sampling grid.

[0051] The high-order aberration height distribution data generation unit is used to construct two-dimensional spatial distribution functions according to the data type of each set of preoperative ocular measurement data unified under the same planning coordinate system, and remove the low-order refractive components contained in each two-dimensional spatial distribution function to generate multiple sets of high-order aberration height distribution data.

[0052] In some optional implementations, the high-order aberration height distribution data generation unit includes at least one of the following sub-units: a first transformation sub-unit, a second transformation sub-unit, a third transformation sub-unit, a fourth transformation sub-unit, and a fifth transformation sub-unit.

[0053] The first transformation subunit is used to construct an aspherical surface shape function based on the first data type, and remove the low-order refractive components in the aspherical surface shape function to generate high-order aberration height distribution data of the first data type; the aspherical surface shape function is used as a two-dimensional spatial distribution function; the first data type includes at least one of the following: corneal Q value, conic constant, eccentricity.

[0054] For inputs of Q-value (corneal Q-value, meaning corneal aspheric coefficient), conic constant, or eccentricity, the system first constructs an aspheric sag function f. Q(x,y) Then from f Q(x,y) After removing the lower-order components, we obtain W. Q(x,y) .

[0055] The aspherical elevation function is: ; Where z(r;R,Q) represents the aspherical elevation at a radial distance r; R represents the vertex radius of curvature; Q represents the aspherical Q value; and r represents the radial distance.

[0056] When the input is the conic constant k, the following values ​​can be taken: ; When the input is eccentricity e, the following values ​​can be taken: ; Let the baseline corneal surface parameters be (R0, Q0), and the target corneal surface parameters be (R... t Q t Then, the aspherical surface shape function obtained by the change of Q value is: ; in, This represents the height difference function caused by changes in the Q value, i.e., the aspherical surface shape function; Represents the vertex radius of curvature of the basic corneal surface; The Q value represents the baseline corneal surface area; Represents the vertex radius of curvature of the target corneal surface; This represents the Q value of the target corneal surface.

[0057] To avoid redundant calculations of Q-value compensation and low-order corrections corresponding to spherical, cylindrical, and axis positions, the system... Removal of low-order components ,get: ; in, This represents the high-order aberration height distribution data obtained from Q-values, conic constants, or eccentricity sources; express The lower-order refractive components in the image.

[0058] In this embodiment, the Q value is not directly used as the cutting depth, but is first converted into a two-dimensional height difference function. After deducting the portion equivalent to low-order refractive correction, only the high-order portion truly used for personalized visual quality compensation is retained. .

[0059] The second transformation subunit is used to construct a height surface function based on the second data type, and remove the low-order refractive components in the height surface function to generate high-order aberration height distribution data of the second data type; the height surface function is used as a two-dimensional spatial distribution function; the second data type includes at least one of the following: corneal height map, sagittal map, and three-dimensional point cloud of corneal height.

[0060] For corneal height maps, sag maps, or 3D point cloud data of corneal height as input, the system first obtains the height surface function in a unified coordinate system through coordinate transformation and interpolation resampling. .

[0061] If the original data is a regular grid heightmap Then it can be expressed as: ; in, This represents corneal height map data in the original coordinate system; Indicates the interpolation operator; , () represents the original coordinates obtained by the inverse coordinate transformation; This represents the height surface shape function in a unified coordinate system.

[0062] If the original data is a 3D point cloud The system can be obtained through surface fitting or interpolation: ; in, This represents the j-th 3D point cloud; and Represents the planar coordinates of the point cloud; Represents the point cloud height; SurfaceFit represents the surface fitting function; This indicates the number of point clouds.

[0063] If the system has a target height distribution The height surface function can also be defined as: p; in, Indicates the height distribution of the target cornea; This represents the corneal height distribution measured and mapped to a unified coordinate system.

[0064] System removal lower-order components ,get: ; in, This represents the height distribution data of higher-order aberrations obtained from corneal height maps, sagittal maps, or 3D point clouds. express The lower-order refractive components in the image.

[0065] Height maps, sag maps, or 3D point clouds typically contain information about the overall curvature, tilt, defocus, and astigmatism trends of the cornea, and cannot all be used for higher-order compensation. In this embodiment, the system needs to first map them to a unified coordinate system and then extract higher-order local morphological information from them.

[0066] The third transformation subunit is used to construct an optical surface shape function based on the third data type, and remove the low-order refractive components in the optical surface shape function to generate high-order aberration height distribution data of the third data type; the optical surface shape function is used as a two-dimensional spatial distribution function; the third data type includes Zernike surface shape coefficients.

[0067] For the Zernike surface coefficients (a set of coefficients obtained by fitting the corneal height plane or wavefront phase plane using Zernike polynomials, which can quantitatively characterize various aberration components including defocus, astigmatism, spherical aberration, and coma) input, the system uses normalized aperture coordinates... and azimuth Reconstructing the optical surface shape function: ; in, This represents the surface height function reconstructed from the Zernike surface coefficients; Represents the Zernike surface type coefficient; denoted as Zernike polynomial; n represents the radial order; m represents the angular frequency; N represents the highest expansion order.

[0068] The system can directly retain higher-order surface type terms with n>=3: ; in, This represents the height distribution data of higher-order aberrations obtained from Zernike surface coefficients.

[0069] In another implementation, the system can also first reconstruct the complete optical surface function. Then remove low-level components. : ; in, express The lower-order refractive components in the image.

[0070] If the Zernike surface coefficients are already given according to the standard order, the lower-order terms can be discarded directly; if there are differences in the Zernike definition or normalization method of different detection devices, the limited approach is to first reconstruct the surface and then uniformly use a lower-order projection operator to remove the lower-order components.

[0071] The fourth transformation subunit is used to construct an equivalent corneal height surface function based on the fourth data type, and remove the low-order refractive components in the equivalent corneal height surface function to generate high-order aberration height distribution data of the fourth data type; the equivalent corneal height surface function is used as a two-dimensional spatial distribution function; the fourth data type includes wavefront aberrations.

[0072] For wavefront aberration data, let the original wavefront aberration data be... The system obtains the wavefront aberration distribution in a unified coordinate system through coordinate transformation and interpolation resampling. That is, the equivalent corneal height surface shape function in this embodiment: ; in, This represents the wavefront aberration data in the original coordinate system of the wavefront aberrometer. This represents the wavefront data interpolation operator; This represents the wavefront aberration distribution in the unified surgical planning coordinate system.

[0073] The system from By removing piston, tilt, defocus, and regular astigmatism components, higher-order wavefront aberrations are obtained: ; in, Indicates higher-order wavefront aberrations; This represents the lower-order refractive components in wavefront aberration.

[0074] If it is necessary to convert wavefront aberration into an equivalent height distribution on the anterior corneal surface, the following method can be used: ; in, This represents the height distribution data of higher-order aberrations obtained by converting wavefront aberration data; Indicates the refractive index of corneal tissue; It represents the refractive index of air.

[0075] In one implementation: ; therefore: .

[0076] Wavefront aberration is optical path difference, not geometric height. For corneal anterior surface compensation, the optical path difference can be converted into an equivalent geometric height using the refractive index difference under the paraxial approximation. The negative sign indicates that the wavefront error is offset by height adjustment in the opposite direction. If the positive direction of the height defined by the device or the direction of tissue removal are different, they can be unified by a sign coefficient.

[0077] The fifth transformation subunit is used to generate high-order aberration height distribution data obtained from high-order aspherical sources, based on high-order aspherical surface shape functions and by removing low-order refractive components from the high-order aspherical surface shape functions.

[0078] The system can also be represented using radial higher-order aspherical surfaces: ; in, Represents a higher-order aspherical height function; denoted as the 2p-th order aspherical coefficient; p represents the order index; P represents the highest order; r represents the radial distance.

[0079] In another implementation, higher-order aspherical surfaces can be expressed using a two-dimensional polynomial with angular variations: ; in, express The surface coefficients of the term; p and q represent the polynomial order; This represents the highest y-order corresponding to p.

[0080] The system from Removal of low-order components ,get: ; in, This represents the height distribution data of higher-order aberrations obtained from higher-order aspherical sources. express The low-order refractive components in the image include piston, tilt, defocus, and regular astigmatism components.

[0081] In another implementation, the corneal profile is also represented using a freeform surface model: ; Where: z(x,y) represents the corneal height at coordinate (x,y); x represents the lateral coordinate; y represents the longitudinal coordinate; auv represents the coefficients of the freeform surface polynomial; u represents the order in the x-direction; v represents the order in the y-direction; U represents the highest order in the x-direction; V represents the highest order in the y-direction.

[0082] Therefore, the aspherical shape guidance in this embodiment is not limited to a single Q value, but covers one or more of the following: Q value, conic constant, eccentricity, higher-order aspherical parameters, bimeridian aspherical parameters, angle-dependent aspherical parameters, corneal height map, corneal sagittal map, 3D point cloud, Zernike surface parameters, and freeform surface parameters.

[0083] In one alternative implementation, in order to uniformly process the above f Q f A f H f Z In addition to M(x,y), the system also defines a set of lower-order basis functions. : ; Where 1 represents the piston term; x and y represent the tilt terms in two directions; Indicates the defocused term; 2xy represents the regular astigmatism term.

[0084] For any function f(x,y), the low-order fitting function Defined as: ; in, , , , , and This represents the low-order fitting coefficients.

[0085] Lower-order coefficients can be obtained through weighted least squares: ; in, This represents the j-th sampling point; The sampling point weights can be determined by measurement confidence, image quality, repeatability consistency, or physician settings.

[0086] The height distribution of higher-order aberrations is uniformly defined as: ; in, Representation function The high-order aberration height distribution data obtained after removing low-order components.

[0087] Regardless of the input source, it must first be converted into a two-dimensional function in a unified coordinate system. Thus, the low-order projection method in this embodiment can be used to separate the high-order compensation components.

[0088] The low-order refractive correction baseline distribution data generation unit is used to calculate low-order refractive correction baseline distribution data based on refractive parameters in preoperative ocular measurement data.

[0089] Let the refractive power of the eyeglasses be... If the vertex distance is l, then the corneal plane refractive power is: ; in, Indicates corneal plane refractive power; The value indicates the diopter of the eyeglasses; l indicates the vertex distance, in meters.

[0090] Assume the curvature of the anterior surface of the cornea is The equivalent refractive index of the corneal topometer is Then the radius of curvature of the anterior surface of the cornea is: ; in, This represents the radius of curvature of the anterior surface of the cornea, in millimeters. Indicates the equivalent refractive index of the corneal topometer; It represents the curvature of the anterior surface of the cornea, and the unit is diopters.

[0091] Assume the actual refractive index of the cornea is Then the radius of curvature of the back cut surface corresponding to the lower-order correction is: ; in, Represents the radius of curvature of the back-cut surface or equivalent target surface; This indicates the actual refractive index of the cornea.

[0092] For cases involving cylindrical lenses, let the spherical power be... Cylinder power is The axis is Then the equivalent corrected refractive power in different directions is: ; in, express Equivalent refractive power in the direction; Indicates spherical power; Indicates cylindrical power; Indicates the astigmatic axis; Indicates the current azimuth angle.

[0093] The corresponding direction-dependent radius of curvature is: ; The thickness of the low-order base lens or the base cutting depth can be obtained using the sag-height difference algorithm: ; in, This indicates the thickness of the low-order base lens or the amount of base tissue removed, which is the low-order refractive correction base distribution data in this embodiment. Indicates the Q value of the reference front surface; This represents the Q value of the target surface or the post-cut surface.

[0094] In the case of a cylindrical lens, it can be Replace with .

[0095] The preoperative target correction distribution data generation unit is used to fuse multiple sets of high-order aberration height distribution data to determine the fused high-order aberration height distribution data; based on the fused high-order aberration height distribution data, the tissue removal compensation amount is determined; based on the tissue removal compensation amount, the low-order refractive correction basic distribution data, and the preset empirical compensation amount, the preoperative target correction distribution data is determined.

[0096] The system will obtain multiple higher-order aberration height distribution data: W Q(x,y) W A(x,y) W H(x,y) W Z(x,y) W M(x,y) Unified as: ; Where i represents different data sources, namely the preoperative ocular measurement data output by the i-th preoperative testing device; set up Let the weights of the i-th data source be denoted as , then the fused higher-order aberration height distribution data is: ; in, This indicates the fusion of higher-order aberration height distribution data; This represents the weight of the i-th data source.

[0097] The following factors can be used to determine the accuracy of the results: equipment reliability, image quality, consistency of repeated measurements, patient compliance, corneal coverage, surgeon selection, historical postoperative feedback, and safety strategies.

[0098] Let the fused higher-order aberration height distribution data be W_fusion(x,y). The system converts it into tissue removal compensation: ; in, Indicates the amount of compensation for the removal of higher-order tissues; This represents the compensation ratio coefficient.

[0099] If the height direction, tissue removal direction, or laser propagation direction defined by the device are different, it can also be written as: ; in, For the sign coefficient, It can be +1 or -1.

[0100] Introducing the transition region function A(r): ; Where b represents the width of the transition zone.

[0101] The final treatment distribution is as follows: ; in, This represents the final lens thickness distribution or tissue removal distribution, i.e., the preoperative target correction distribution data in this embodiment; The term represents the empirical nomogram compensation amount, which is the empirical compensation amount in this embodiment. For example, it is a spatial distribution correction term pre-calibrated based on factors such as patient age, corneal thickness, and surgical procedure. It is used to compensate for systematic deviations caused by corneal biomechanical deformation, laser energy loss, etc.

[0102] In some optional implementations, the preoperative target correction distribution data generation unit further includes: a conflict detection subunit, a conflict handling subunit, a constraint control subunit, and an interactive confirmation subunit.

[0103] The conflict detection subunit is used to calculate the difference between any two sets of high-order aberration height distribution data; when the maximum difference exceeds the preset conflict threshold, it is determined that there is a multi-source data conflict.

[0104] If conflicts exist between different sources, then the conflict quantity is defined as follows: ; If the following conditions are met: ;in, This indicates the preset conflict threshold.

[0105] The system then determines that there is a multi-source data conflict at that location.

[0106] The conflict handling subunit is used to execute a preset control strategy when a multi-source data conflict is detected. The preset control strategy includes one or more of the following: reducing the weight of low-confidence sources, wavefront priority, corneal height priority, freeform surface priority, and depth priority.

[0107] Conflict handling methods include: reducing the weight λi of low-confidence sources; employing a wavefront-first strategy when visual quality indicators are significantly abnormal; using a height map or point cloud-first strategy when corneal morphology is significantly abnormal; employing a freeform surface-first strategy when the doctor specifies a target freeform surface; and employing a depth-first strategy when safety boundaries allow and sufficient compensation needs to be ensured. Other methods include doctor-specified source-first strategies, prompting for retesting, or prompting the doctor for confirmation.

[0108] The depth-first strategy can be expressed as: ; ; ; in, represents the amount of tissue removal compensation corresponding to the i-th source; k represents the source number with the largest compensation magnitude.

[0109] The constraint control subunit is used to set upper limit constraints on higher-order compensation amplitude and smoothness constraints on treatment distribution gradient, so as to limit the maximum value of the final higher-order compensation amount and the steepness of the distribution.

[0110] The system can also set upper limit constraints on higher-order compensation amplitude: ; And treatment distribution gradient smoothing constraint: ; in, Indicates the maximum allowable amplitude of higher-order compensation; The gradient representing the final treatment distribution; This represents the maximum allowed gradient.

[0111] The interactive confirmation subunit is used to display any parameter generated by the corneal refractive surgery system to the user interface; after receiving confirmation instructions from the doctor, it locks all parameters and generates an execution log.

[0112] On the user confirmation screen, the system can display at least one of the following parameters: basic distribution data of low-order refractive correction, height distribution data of high-order aberrations, and the source of each height distribution data of high-order aberrations. Fusion results Final treatment distribution or The system records iris registration results, eye rotation angle, treatment center offset, maximum ablation depth, remaining stromal bed thickness, multi-source conflict locations, and the system's recommended strategy. After physician confirmation, the system locks the parameters and generates an execution log.

[0113] The intraoperative data processing module is used to map preoperative target correction distribution data to the intraoperative execution coordinate system through iris biometric matching to obtain intraoperative target correction distribution data; it is also used to determine laser scanning data based on intraoperative target correction distribution data.

[0114] In some optional implementations, the intraoperative data processing module includes: a preoperative iris template construction unit, an iris registration unit, a cutting surface generation unit, and a scanning point discretization unit.

[0115] The preoperative iris template construction unit is used to acquire preoperative eye images and construct a preoperative iris template based on the first iris biometric features in the preoperative eye images.

[0116] In some optional implementations, the preoperative iris template construction unit includes: a reference point detection subunit, a center determination subunit, a preoperative template generation subunit, and an iris normalization subunit.

[0117] The reference point detection subunit is used to acquire preoperative ocular images and detect reference point data from the preoperative ocular images; the reference point data includes the pupil center, the limbus center, the corneal apex, or the corneal reflective point.

[0118] During the preoperative planning stage, the system collects preoperative eye images of the patient. The preoperative ocular image includes iris texture, scleral vessels, limbus, pupillary margin, corneal reflector, corneal apex, or visual axis reference point. The pupil center, limbal center, corneal apex, or corneal reflector can be used as reference points.

[0119] The system first detects the preoperative pupil center. : ; in, Indicates the preoperative pupil center; y_p,pre represents the X coordinate of the preoperative pupil center; y_p,pre represents the Y coordinate of the preoperative pupil center.

[0120] System detection of the preoperative limbal center : ; in, Indicates the preoperative center of the corneal limbus; This indicates the X-coordinate of the preoperative corneal limbus center; The Y-coordinate represents the center of the corneal limbus before surgery.

[0121] System detection of preoperative corneal apex or corneal reflective points : ; in, This indicates the corneal apex, corneal reflective point, or visual axis reference point before surgery.

[0122] The center determines the sub-unit, which is used to calculate the preoperative treatment center based on reference point data and preset weight coefficients, and to establish a preoperative planning coordinate system with the preoperative treatment center as the origin.

[0123] Preoperative treatment center It can be determined by the pupil center, corneal apex, limbal center, visual axis, or a point designated by the doctor: ; in, Indicates the preoperative treatment center; This indicates the doctor has designated a treatment center; and This indicates the weight of sources from different centers.

[0124] The weights can satisfy: ; in, These represent the weights of the pupil center, corneal apex, limbal center, and doctor-specified point, respectively.

[0125] The system is based on Establish a preoperative planning coordinate system with the origin as the coordinate origin.

[0126] The preoperative template generation subunit is used to extract iris features from preoperative eye images as the first iris biometric feature to construct a preoperative iris template.

[0127] After establishing the preoperative planning coordinate system, the iris texture template can be saved. : ; in, This represents the preoperative iris template; This represents the iris texture feature extraction operator; This refers to a preoperative image of the eye.

[0128] Preoperative iris templates may include normalized iris texture, iris phase encoding, iris key points, local descriptors, circular sampling sequences, or depth feature vectors.

[0129] The iris normalization subunit is used to map the iris region in the preoperative eye image from Cartesian coordinates to a polar coordinate normalized space to generate a normalized preoperative iris image. The preoperative planning coordinate system and the normalized preoperative iris image are output to the iris registration unit for template matching and coordinate mapping.

[0130] To reduce the impact of changes in pupil size and shooting distance, the system can expand the iris region from Cartesian coordinates to a polar coordinate normalized space.

[0131] Let the pupil boundary point be The limbus or outer boundary of the iris is Then normalize the iris point It can be represented as: ; in, Represents normalized iris sampling points; Represents the normalized radial coordinates from the pupil boundary to the outer boundary of the iris; Indicates angular coordinates; express The pupil boundary point in the direction; express The outer boundary point of the iris or the limbus boundary point in the direction.

[0132] Based on the above mapping, the normalized preoperative iris image is obtained: ; in, This represents the original preoperative eye image; This represents a normalized preoperative iris image.

[0133] Even if the pupil size differs before and during surgery, the system can compare the same iris texture position in normalized iris coordinates to estimate the eye rotation angle.

[0134] The iris registration unit is used to acquire intraoperative ocular images and construct an intraoperative iris template based on the second iris biometrics in the intraoperative ocular images. The intraoperative iris template is matched with the preoperative iris template to obtain the ocular transformation relationship. Based on the ocular transformation relationship, the preoperative target correction distribution data is mapped to the intraoperative execution coordinate system to obtain the intraoperative target correction distribution data.

[0135] In some optional implementations, the iris registration unit includes: an intraoperative image acquisition subunit, an intraoperative template generation subunit, a transformation subunit, and a distribution mapping subunit.

[0136] The intraoperative image acquisition subunit is used to acquire intraoperative ocular images and extract iris features from the intraoperative ocular images as secondary iris biometrics. The system collects intraoperative ocular images I_intra before, during, and after adsorption, or before laser treatment.

[0137] System detection of pupil center during surgery: ; System detection of the limbal center during surgery: ; The system detects the corneal apex, corneal reflective point, or visual axis reference point during surgery: ; The intraoperative treatment center is calculated by using the intraoperative pupil center, intraoperative limbal center, intraoperative corneal apex, corneal reflective point, or visual axis reference point as reference point data, combined with preset weighting coefficients.

[0138] Systematic extraction of intraoperative iris template: ; in, Indicates the intraoperative iris template; This indicates an intraoperative image of the eye.

[0139] If the iris is partially obscured by the patient's interface, eyelids, eyelashes, air bubbles, or instruments during the procedure, the system can use a visible area mask. : ; in, This indicates the area visible during surgery, which is masked.

[0140] The intraoperative template generation subunit is used to construct an intraoperative iris template based on the biometric features of the second iris, and to perform polar coordinate normalization on the intraoperative iris region to generate a normalized intraoperative iris image. For details, please refer to the processing procedure for normalized preoperative iris images.

[0141] The transformation subunit is used to match the preoperative iris template corresponding to the normalized preoperative iris image with the intraoperative iris template corresponding to the normalized intraoperative iris image to obtain the eyeball rotation angle, which is then used to determine the eyeball transformation relationship.

[0142] The system calculates the ocular rotation angle by comparing preoperative and intraoperative iris templates. Normalized cross-correlation, phase correlation, keypoint matching, or deep feature matching methods can be used.

[0143] The rotation estimation formula based on angular cross-correlation can be: ; in, This represents the estimated eye rotation angle; This represents a normalized preoperative iris image; This represents a normalized intraoperative iris image; Indicates the visible area mask; and Indicates the radial range of the iris involved in the matching.

[0144] If feature point matching is used, let the preoperative feature point be p_k and the intraoperative feature point be q_k, then the rotation and translation can be solved by minimizing the matching error: ; Among them, R Represents the optimal rotation matrix; Represents the optimal translation vector; This represents the k-th preoperative feature point; This represents the k-th intraoperative feature point; This represents the weight of the k-th matching point; This indicates the number of matched feature points.

[0145] A two-dimensional rotation matrix can be represented as: .

[0146] The distribution mapping subunit is used to construct a coordinate transformation matrix based on the eye rotation angle. Relying on the preoperative planning coordinate system, it maps the preoperative target correction distribution data to the intraoperative execution coordinate system to obtain the intraoperative target correction distribution data.

[0147] After determining the eye rotation angle, the system establishes a similarity transformation from the preoperative planning coordinate system to the intraoperative execution coordinate system: ; in, Indicates the coordinates for preoperative planning; Indicates the coordinates used during the operation; represents the rotation matrix obtained from iris matching; t represents the translation vector.

[0148] If scaling is taken into account, the similarity transformation becomes: ; Where s represents the scale ratio from preoperative image to intraoperative image.

[0149] The translation vector can be determined by the difference in treatment centers: ; in, Indicates the intraoperative treatment center; This indicates a preoperative treatment center.

[0150] The intraoperative treatment center can be obtained by fusing the intraoperative pupil center, corneal apex, limbal center, and the physician's confirmation point: ; in, This indicates the weight of different centers of origin during the operation.

[0151] The weights can satisfy: .

[0152] In some alternative implementations, the higher-order aberration height distribution obtained by preoperative fusion is as follows: By transforming the coordinates from preoperative to intraoperative, the height distribution of higher-order aberrations in the intraoperative coordinate system can be obtained.

[0153] In order to reach the midpoint of the operation To read the preoperative compensation image, an inverse transformation can be used: ; in, This represents the reverse rotation matrix.

[0154] The intraoperative distribution of higher-order aberrations is as follows: ; in, This indicates the height distribution of higher-order aberrations in the coordinate system used during the procedure.

[0155] Similarly, the final treatment distribution can also be mapped as: ; in, This indicates the final treatment distribution in the intraoperative execution coordinate system; This represents the final treatment distribution within the preoperative planning coordinate system.

[0156] The personalized compensation map planned before the operation is not directly sent to the laser device. Instead, it is first rotated, translated and scaled based on the iris matching results, and then transformed into a treatment pattern in the coordinate system for intraoperative execution.

[0157] In some optional implementations, the iris registration unit further includes at least one of the following sub-units: a correction sub-unit, a confidence sub-unit, and an error recording and factoring unit.

[0158] The correction subunit is used to rotate and correct the preoperatively planned astigmatic axis and the direction angles of higher-order compensation in each direction based on the eye rotation angle, so as to obtain the intraoperative astigmatic axis and the intraoperative higher-order compensation direction angle.

[0159] If the astigmatism axis is in the preoperative planning During the surgery, the eyeball rotation angle was detected to be... The intraoperative execution axis can then be corrected as follows: ; in, This indicates that the astigmatic axis was executed during the procedure; Indicates the preoperative planning axis; This indicates the angle of eye rotation.

[0160] For any directional high-order compensation pattern, if its preoperative directional angle is Then the intraoperative orientation angle is: ; in, Indicates the intraoperative higher-order compensation direction angle; Indicates the preoperative orientation angle.

[0161] This correction is particularly important for astigmatism, coma, cloverleaf aberration, asymmetric freeform surface compensation, and off-center compensation.

[0162] The confidence subunit is used to calculate the registration confidence and registration residual of the preoperative iris template and the intraoperative iris template. The safety interlock is triggered when any of the following conditions are met: the registration confidence is lower than the preset minimum registration confidence threshold, the registration residual is higher than the preset maximum allowable registration residual, or the eye rotation angle is higher than the preset maximum allowable eye rotation angle.

[0163] The registration confidence level can be calculated by combining the matching correlation coefficient, the proportion of effective visible area, the proportion of points within the matching points, and the residuals. : ; in, Indicates the registration confidence level; Indicates the correlation coefficient of iris texture; Indicates the percentage of the effectively visible iris area; Indicates the proportion of inliers in feature matching; Indicates the registration residual; Indicates the weight.

[0164] Registration residuals can be defined as: ; in, This represents the registration residual of feature points; Indicates preoperative feature points; Indicates intraoperative feature points; Indicates the number of feature points.

[0165] The system will not allow the issuance of laser execution parameters if any of the following conditions are met: ; ; ; ; in, Indicates the minimum registration confidence threshold; Indicates the maximum permissible registration residual; Indicates the maximum permissible angle of eye rotation; This indicates the maximum permissible translation amount.

[0166] When the safety interlock is triggered, the system performs at least one of the following operations: re-acquiring images, re-registering, prompting the doctor for confirmation, re-attaching, re-planning, or prohibiting laser emission.

[0167] The error recording and attribution unit is used to collect and store the intraoperative parameter set and bind the intraoperative parameter set with the case data; when refractive deviation occurs after surgery, the postoperative error source is traced based on the stored intraoperative parameter set.

[0168] After completing the mapping from the preoperative planning coordinate system to the intraoperative execution coordinate system, the system not only sends the transformed treatment distribution to the scanning execution module, but also simultaneously records the intraoperative registration parameter set: ; in, This represents the set of intraoperative registration parameters; Indicates the angle of eye rotation; Indicates the translation amount in the X direction; Indicates the translation amount in the Y direction; Indicates the scale ratio from preoperative image to intraoperative image; Indicates the registration confidence level; Indicates the registration residual; It represents the area proportion of the effectively visible iris, scleral vessels, limbus, or other ocular features; This indicates the number of valid matching interior points.

[0169] The system binds and stores the above registration parameters with case data, including case number, preoperative planning data, intraoperative treatment distribution, scan execution log, and postoperative follow-up data. If postoperative residual astigmatism, asymmetric higher-order aberrations, insufficient local off-center compensation, or freeform surface compensation shift occurs, the system can adjust the postoperative residuals with... Perform correlation analysis.

[0170] If the postoperative residual is mainly manifested as an overall angular deviation, and this deviation is related to the intraoperative eyeball rotation angle If the deviation is related to the astigmatism axis correction, the system will preferentially attribute it to the registration layer error; if the postoperative residuals mainly show overall translation or off-center distribution, and are related to... If the error is related, the system will prioritize attributing the deviation to the treatment center or coordinate mapping error. If the intraoperative registration confidence is low or the registration residual is large, the system will not directly increase the higher-order compensation ratio, but will instead prioritize updating the registration threshold, registration image quality requirements, re-registration strategy, or physician confirmation strategy.

[0171] The cutting surface generation unit is used to modify the intraoperative target correction distribution data by combining intraoperative corneal deformation information, and generate surgical cutting data and boundary contour data.

[0172] The cutting surface generation unit is used to generate cutting data for femtosecond lenticule extraction (FMI) corneal stromal lenticule cutting. The surgical cutting data includes the height of the anterior cutting surface and the height of the posterior cutting surface.

[0173] Let the reference corneal surface be in the adsorption state or the patient interface constraint state. .in, It can be determined by intraoperative OCT, patient interface geometry, preoperative corneal facial mapping, or empirical models.

[0174] If we consider adsorption deformation, let the coordinates of the relaxed state be... The adsorption state coordinates are ,but: ; in, This represents the adsorption deformation mapping function.

[0175] Personalized compensation maps are usually derived from preoperative relaxed-state measurements, while femtosecond laser surgery occurs in an adsorbed or flattened state. Therefore, it is necessary to map the preoperative compensation map onto the intraoperative execution coordinate system.

[0176] Let the thickness of the corneal cap be... Then the front cutting surface is: ; in, This indicates the height of the anterior cutting plane; dcap indicates the corneal cap thickness.

[0177] The rear cut surface is: ; in, Indicates the height of the back cut surface; This represents the target correction distribution data.

[0178] Let the radius of the optical region be *a*, the width of the transition region be *b*, and the width of the extra boundary be *[missing information]*. Then the outer boundary radius of the lens can be taken as: ; in, Indicates the radius of the edge cut or the outer boundary of the lens; This refers to the additional radius set by the physician or determined by the equipment's safety boundaries.

[0179] The range of the side cut angle can be expressed as: ; in, Indicates the starting angle of the edge cut; Indicates the angle at which the cut ends.

[0180] The scanning point discrete unit is used to discretize the surgical cutting data and boundary contour data to generate laser scanning data.

[0181] The system will , Discretize the boundary contour data (edge ​​cut curve) into a sequence of scan points: ; Among them, P k x represents the k-th laser scanning point; k Indicates position in the X direction; y k Indicates position in the Y direction; z k Indicates the depth of focus; t k Indicates the pulse trigger time; E k This indicates pulse energy.

[0182] For the front cutting face: ; For the back-cut surface: .

[0183] In some optional implementations, the scan point discrete unit includes a femtosecond safety constraint subunit, which is used to trigger a preset safety adjustment strategy when the preset safety constraint is not met.

[0184] The system determines the preset security constraints: ; ; ; in, Indicates the maximum permissible lens thickness or maximum tissue removal; CCT indicates central corneal thickness. This indicates the minimum remaining substrate bed thickness.

[0185] If any condition is not met under the security constraint, the system will degrade. Reduce the optical zone, adjust the transition zone, and prompt the doctor to confirm or refuse to generate surgical parameters.

[0186] The feedback correction module is used to collect postoperative distribution data and compare it with preoperative target correction distribution data, and update the preset parameters in the corneal refractive surgery system based on the comparison results.

[0187] In some optional implementations, the feedback correction module includes: a postoperative data acquisition unit, a residual calculation unit, and a parameter iteration update unit.

[0188] The postoperative data acquisition unit is used to collect postoperative distribution data, which includes at least one of the following: postoperative corneal height, postoperative wavefront aberration, postoperative refractive power, and patient subjective visual quality.

[0189] The residual calculation unit is used to compare the postoperative distribution data with the preoperative target correction distribution data, calculate the height residual, wavefront residual, and refractive residual, and construct a comprehensive loss function.

[0190] The parameter iteration update unit is used to update the multi-source data fusion weights, higher-order compensation ratios, and preset empirical compensation amounts in the preoperative multi-source data processing module based on the comprehensive loss function.

[0191] Let the postoperative target corneal height be... The actual corneal height after surgery was Then the height residual is: ; in, This indicates a high level of postoperative residual.

[0192] Let the postoperative target wavefront be The actual wavefront after surgery was Then the wavefront residual is: ; in, This indicates the postoperative wavefront residual.

[0193] The system can establish a comprehensive loss function: ; Where L represents the comprehensive loss function; Indicates postoperative refractive residual; This indicates a patient's subjective visual quality error or score loss; Indicates the weight.

[0194] The system can be updated based on postoperative residuals. , and : ; ; in, This indicates the updated higher-order compensation ratio; This indicates the higher-order compensation ratio before the update; This represents the updated weight of the i-th source category; This represents the weight of the i-th source class before the update; and This indicates the update step size. Higher-order compensation ratios are the compensation ratio coefficients used to determine the amount of tissue removal compensation.

[0195] In clinical applications, the system may not automatically update parameters, but instead generate recommended update values, which are then reviewed by doctors, engineers, or clinical experts before being incorporated into the next version of the nomogram.

[0196] In this way, the iris registration module is not only used for intraoperative ocular rotation correction, but also for intraoperative coordinate mapping of complex high-order compensation maps, free-form surface compensation maps and local mutation ablation maps, and provides a basis for the hierarchical attribution of postoperative deviations and subsequent parameter updates.

[0197] In some alternative implementations, the feedback correction module further includes: The error stratified attribution unit receives the full-process stored logs, categorizes the deviations present in the logs to the target level, distinguishes the sources of various deviations, and evaluates the effectiveness of data on the height distribution of different higher-order aberrations. The target levels include: measurement layer, coordinate layer, higher-order transformation layer, planning layer, registration layer, execution layer, organizational response layer, and subjective visual layer. It can perform reverse evaluation of the effectiveness of various sources of higher-order aberration height distributions during the feedback phase and update their fusion weights, improving the accuracy of the next preoperative planning.

[0198] Among them, measurement layer errors include measurement errors of corneal topography, OCT, wavefront aberration meter, and iris images; Coordinate layer errors include differences in coordinate center, rotation angle, scaling ratio, and aperture between different devices; Higher-order conversion layer errors, including Conversion error and low-order removal error; Planning layer error includes low-order correction model, high-order compensation ratio, fusion weight and nomogram compensation amount; Registration layer errors include eye rotation, translation, scaling, registration confidence, and treatment center offset; Execution layer errors include those related to the galvanometer, voice coil, piezoelectric element, Z-axis focus, pulse triggering, and energy output. Tissue response layer errors, including differences in corneal biomechanics, adsorption deformation, tissue recovery, and healing; Subjective visual layer errors include glare, halo, night vision, satisfaction, and doctor's evaluation.

[0199] By classifying postoperative residuals into multi-level error sources, the source of deviations can be precisely located, avoiding general attribution. Furthermore, targeted adjustments to multi-source fusion weights, higher-order compensation ratios, and empirical compensation amounts can effectively improve the accuracy of iterative optimization.

[0200] This invention constructs a complete closed-loop system encompassing preoperative detection, planning, intraoperative alignment, laser execution, and postoperative iterative optimization. It unifies multi-source heterogeneous data such as corneal Q-value, height map, and wavefront aberrations into a high-order aberration height distribution, achieving decoupled calculations for low-order correction and high-order compensation, avoiding redundant ablation. Simultaneously, wavefront and visual quality indicators are integrated into the treatment distribution generation, enabling multi-objective collaborative control. Iris feature registration completes the coordinate mapping of the treatment pattern, reducing placement deviations caused by body position changes. It supports the conversion of complex freeform surfaces into various types of high-speed scanning commands, adapting to ablation in abrupt regions. The system retains execution logs throughout the process and possesses security interlocks, enabling stratified error tracing of postoperative deviations and dynamic updates of various compensation parameters. This invention provides protection at the system, hardware, and method levels, effectively improving the accuracy, safety, and postoperative visual quality of refractive surgery.

[0201] Example 3 This application also provides an embodiment of a corneal refractive surgery system for processing data from femtosecond LASIK surgeries. The system includes: a data acquisition module, a preoperative multi-source data processing module, an intraoperative data processing module, and a feedback correction module, as detailed below.

[0202] The data acquisition module is used to collect preoperative ocular measurement data from multiple different preoperative testing devices, with each device corresponding to a set of preoperative ocular measurement data. See the previous implementation method for details. Further elaboration will not be repeated here.

[0203] The preoperative multi-source data processing module is used to convert preoperative ocular measurement data from various groups to the same planned coordinate system, and to convert the preoperative ocular measurement data into multiple sets of higher-order aberration height distribution data according to data type. It is also used to comprehensively determine the preoperative target correction distribution data based on the multiple sets of higher-order aberration height distribution data and the calculated lower-order refractive correction baseline distribution data. See the previous embodiment for details. Further elaboration is omitted here.

[0204] The intraoperative data processing module is used to map preoperative target correction distribution data to the intraoperative execution coordinate system through iris biometric matching to obtain intraoperative target correction distribution data; it is also used to determine laser scanning data based on intraoperative target correction distribution data.

[0205] Unlike the previous embodiment, which is applied to data processing in femtosecond LASIK surgery, the intraoperative data processing module in femtosecond LASIK or excimer laser surgery mode further includes: a cutting depth calculation subunit, a laser conversion subunit, and a feedback correction module.

[0206] The cutting depth calculation subunit is used to determine the intraoperative cutting depth distribution data in the execution coordinate system based on the intraoperative target correction distribution data.

[0207] Intraoperative cutting depth distribution data can be represented as: ; in, This indicates the distribution of cutting depth in the intraoperative coordinate system; Indicates the low-order basic cutting depth in the intraoperative coordinate system; This indicates the amount of higher-order compensated tissue removed in the intraoperative coordinate system; This indicates the nomogram compensation amount in the intraoperative coordinate system.

[0208] In one implementation, the system may use the Munnerlyn formula as an initial estimate: ; in, Indicates the center cutting depth, usually in micrometers; It represents the corneal planar refractive power; S represents the diameter of the optical zone.

[0209] This formula can be used for initial estimation, but it is ultimately preferable to use the accurate sag difference algorithm together with the higher-order aberration height distribution to generate the cutting depth.

[0210] For femtosecond LASIK combined with excimer laser surgery, let the corneal flap thickness be... Then it must satisfy: ; ; ; in, Indicates the maximum permissible depth of cut; This indicates the thickness of the corneal flap.

[0211] For surface cutting, it can be Set to 0 or replace with epithelial treatment depth, safety reserve depth, or other surface treatment parameters.

[0212] The laser conversion subunit is used to determine the number of laser pulses or the laser energy deposition distribution corresponding to each coordinate position based on the intraoperative cutting depth distribution data.

[0213] Let the equivalent tissue removal amount of a single pulse at the k-th position be . The number of pulses required at this position is: ; in, This indicates the number of pulses required for the k-th position; This indicates the equivalent removal amount per pulse.

[0214] If the device is controlled by energy distribution, it can be written as: ; in, Indicates the distribution of energy deposition; This represents the conversion coefficient from cutting depth to energy deposition.

[0215] The feedback correction module is used to collect postoperative distribution data and compare it with preoperative target correction distribution data. Based on the comparison results, it updates the preset parameters in the corneal refractive surgery system. See the previous implementation method for details. Further elaboration is omitted here.

[0216] This embodiment targets femtosecond LASIK and excimer laser surface ablation procedures. The system calculates the intraoperative ablation depth distribution based on intraoperative target correction distribution data and uses nomogram compensation to correct the ablation amount. A laser conversion unit generates control commands that directly drive the scanning hardware. Simultaneously, a feedback correction mechanism continuously iterates and compensates parameters based on postoperative clinical data. This embodiment improves data processing efficiency, ablation accuracy, reduces the risk of postoperative refractive residue, and enhances postoperative visual quality while ensuring personalized high-order correction capabilities.

[0217] Example 4 This application also provides an integrated corneal refractive surgery device, which includes the corneal refractive surgery system described in any of the above embodiments, and further includes a laser scanning module. The laser scanning module works in conjunction with the corneal refractive surgery system to achieve closed-loop control of the entire process, including preoperative measurement, personalized planning, intraoperative alignment, laser scanning execution, and postoperative feedback optimization.

[0218] The corneal refractive surgery system includes: a data acquisition module, a preoperative multi-source data processing module, an intraoperative data processing module, and a feedback correction module, which are installed inside the device body together with the laser scanning module.

[0219] The laser scanning module is communicatively connected to the corneal refractive surgery system to receive laser scanning data output by the system and output a laser beam based on the data. The laser scanning module includes at least one of the following light sources: a femtosecond laser source, an excimer laser source, a solid-state laser source, or other corneal tissue remodeling energy sources. The device itself includes: The integrated measurement host has a built-in data acquisition module. The integrated measurement host includes at least one of the following: Placido corneal topography module, anterior segment OCT module, wavefront measurement module, iris imaging module, and pupil measurement module. Each module is used to acquire preoperative ocular measurement data output from the corresponding preoperative testing device. The data acquisition module is used to uniformly acquire multiple sets of preoperative ocular measurement data. The treatment planning host has a built-in preoperative multi-source data processing module, which is used to convert the preoperative ocular measurement data of each group to the same planning coordinate system, generate multiple sets of high-order aberration height distribution data, and combine them with low-order refractive correction basic distribution data to comprehensively solve the preoperative target correction distribution data; the intraoperative image and iris registration module works with the treatment planning host to realize the iris feature matching and coordinate mapping functions of the intraoperative data processing module; The composite high-speed scanning module includes a high-speed X / Y galvanometer, a voice coil motor, a piezoelectric ceramic, a fast Z-axis focus adjustment unit, a scanning objective, an energy modulator, and a position feedback unit; the intraoperative data processing module generates laser scanning data based on the intraoperative target correction distribution data and sends it to the composite high-speed scanning module for execution; The patient interface and negative pressure adsorption module are used for intraoperative eyeball positioning and negative pressure fixation. The doctor interaction and feedback input module, the instrument's internal feedback database, and the model update module together constitute the feedback correction module, which is used to collect postoperative distribution data, compare it with preoperative target correction distribution data, trace errors hierarchically, and update the system's preset parameters.

[0220] The complete workflow of the integrated device is as follows: the data acquisition module collects multi-source preoperative ocular measurement data and sends it to the treatment planning host; the preoperative multi-source data processing module completes coordinate unification, decoupling of high and low order components, and fusion of multi-source data to obtain preoperative target correction distribution data; the intraoperative image and iris registration module solves the ocular transformation relationship through iris biometric matching, maps the preoperative target correction distribution to the intraoperative execution coordinate system, obtains intraoperative target correction distribution data, and converts it into laser scanning data; the laser scanning module works with the composite high-speed scanning module to complete personalized corneal ablation; postoperatively, follow-up examination data is entered through the doctor interaction and feedback input module, and error analysis and system parameter iteration are completed by the instrument's internal feedback database and model update module.

[0221] This embodiment integrates functional modules into a single unit, embedding a corneal refractive surgery system. It avoids data conversion deviations caused by interconnecting multiple external devices. Relying on a closed-loop end-to-end continuous optimization planning model and compensation parameters, it can improve the corrective accuracy and clinical safety of personalized refractive surgery.

[0222] Example 5 This application also provides an embodiment of a corneal refractive surgery system linked to an external measuring device, which can be connected to the hospital's existing ophthalmological measuring equipment without the need to replace the hardware. The core difference between this embodiment and Embodiments 1, 2, and 3 is that the system does not carry integrated built-in measuring hardware, but relies on a communication interface to connect to the third-party preoperative measuring equipment already deployed in the hospital.

[0223] The corneal refractive surgery system linked to the external measurement device in this embodiment includes a data acquisition module, a preoperative multi-source data processing module, an intraoperative data processing module, and a feedback correction module. The data acquisition module is equipped with a standardized universal data communication interface, a data parsing unit, and a coordinate conversion unit. The communication interface supports at least one of Ethernet, USB, DICOM, and custom serial port protocols, enabling connection to external preoperative testing equipment such as the Placido corneal topography system, anterior segment OCT device, wavefront aberration analyzer, and external iris scanner. The data acquisition module receives raw ocular measurement data from external devices via the interface. Subsequent processes reuse any implementation method from Examples 1-3.

[0224] This embodiment eliminates the need to purchase integrated equipment, making full use of existing ophthalmic measurement equipment in hospitals. It achieves unified and standardized processing of multi-source ophthalmic measurement data while significantly reducing the investment in equipment upgrades for medical institutions. This ensures personalized refractive planning, precise intraoperative alignment, and closed-loop optimization capabilities throughout the entire process. It is adaptable to the existing equipment conditions of different hospitals and has a wide range of clinical applications.

[0225] Although embodiments of the invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the invention, and such modifications and variations all fall within the scope defined by the appended claims.

Claims

1. A corneal refractive surgery system, characterized in that, The system includes: The data acquisition module is used to collect preoperative ocular measurement data from multiple different preoperative testing devices, wherein one of the preoperative testing devices corresponds to a set of the preoperative ocular measurement data. The preoperative multi-source data processing module is used to convert the preoperative ocular measurement data of each group to the same planned coordinate system, and to convert the preoperative ocular measurement data of each group into multiple groups of high-order aberration height distribution data according to data type; it is also used to generate preoperative target correction distribution data based on the multiple groups of high-order aberration height distribution data and the calculated low-order refractive correction baseline distribution data. The intraoperative data processing module is used to map the preoperative target correction distribution data to the intraoperative execution coordinate system through iris biometric matching to obtain intraoperative target correction distribution data; it is also used to determine laser scanning data based on the intraoperative target correction distribution data; The feedback correction module is used to collect postoperative distribution data and compare it with the preoperative target correction distribution data, and update the preset parameters in the corneal refractive surgery system based on the comparison results. The preoperative multi-source data processing module includes: A multi-source coordinate transformation unit is used to transform the preoperative ocular measurement data of each group to the same planned coordinate system by performing a transformation operation. The high-order aberration height distribution data generation unit is used to construct two-dimensional spatial distribution functions according to the data type of each set of preoperative ocular measurement data unified under the same planning coordinate system, and remove the low-order refractive components contained in each two-dimensional spatial distribution function to generate multiple sets of high-order aberration height distribution data. The low-order refractive error correction baseline distribution data generation unit is used to calculate the low-order refractive error correction baseline distribution data based on the refractive parameters in the preoperative ocular measurement data. The preoperative target correction distribution data generation unit is used to fuse multiple sets of high-order aberration height distribution data to determine the fused high-order aberration height distribution data; based on the fused high-order aberration height distribution data, to determine the tissue removal compensation amount; and based on the tissue removal compensation amount, the low-order refractive correction basic distribution data, and the preset empirical compensation amount, to determine the preoperative target correction distribution data. The higher-order aberration height distribution data generation unit includes at least one of the following sub-units: The first transformation subunit is used to construct an aspherical surface shape function based on a first data type, and remove the low-order refractive components in the aspherical surface shape function to generate high-order aberration height distribution data of the first data type; the aspherical surface shape function is used as the two-dimensional spatial distribution function; the first data type includes: corneal Q value, conic constant, and eccentricity; The second transformation subunit is used to construct a height profile function based on the second data type, and remove the low-order refractive components in the height profile function to generate high-order aberration height distribution data of the second data type; the height profile function is used as the two-dimensional spatial distribution function; the second data type includes at least one of corneal height map, sagittal map, and three-dimensional corneal height point cloud; The third transformation subunit is used to construct an optical surface shape function based on the third data type, and remove the low-order refractive components in the optical surface shape function to generate high-order aberration height distribution data of the third data type; the optical surface shape function is used as the two-dimensional spatial distribution function; the third data type includes Zernike surface shape coefficients; The fourth transformation subunit is used to construct an equivalent corneal height profile function based on the fourth data type, and remove the low-order refractive components in the equivalent corneal height profile function to generate high-order aberration height distribution data of the fourth data type; the equivalent corneal height profile function is used as the two-dimensional spatial distribution function; the fourth data type includes wavefront aberration; The fifth transformation subunit is used to construct a higher-order aspherical surface shape function based on higher-order aspherical parameters, and remove the low-order refractive components in the higher-order aspherical surface shape function to generate higher-order aberration height distribution data obtained from higher-order aspherical sources. The feedback correction module includes: The postoperative data acquisition unit is used to collect the postoperative distribution data; the postoperative distribution data includes at least one of postoperative corneal height, postoperative wavefront aberration, postoperative refractive power, and patient subjective visual quality. The residual calculation unit is used to compare the postoperative distribution data with the preoperative target correction distribution data, calculate the height residual, wavefront residual, and refractive residual, and construct a comprehensive loss function. The parameter iteration update unit is used to update the multi-source data fusion weights, higher-order compensation ratios, and preset empirical compensation amounts in the preoperative multi-source data processing module in reverse based on the comprehensive loss function.

2. The system according to claim 1, characterized in that, The intraoperative data processing module includes: The preoperative iris template construction unit is used to acquire preoperative eye images and construct a preoperative iris template based on the first iris biometric features in the preoperative eye images. The iris registration unit is used to acquire intraoperative ocular images and construct an intraoperative iris template based on the second iris biometric features in the intraoperative ocular images; the intraoperative iris template is matched with the preoperative iris template to obtain the eyeball transformation relationship; based on the eyeball transformation relationship, the preoperative target correction distribution data is mapped to the intraoperative execution coordinate system to obtain the intraoperative target correction distribution data. The cutting surface generation unit is used to modify the intraoperative target correction distribution data by combining intraoperative corneal deformation information, and generate surgical cutting data and boundary contour data; The scanning point discretization unit is used to discretize the surgical cutting data and the boundary contour data to generate the laser scanning data.

3. The system according to claim 2, characterized in that, The preoperative iris template construction unit includes: The reference point detection subunit is used to acquire the preoperative ocular image and detect reference point data from the preoperative ocular image; the reference point data includes the pupil center, the limbus center, the corneal apex, or the corneal reflective point; The center determines the sub-unit, which is used to calculate the preoperative treatment center based on the reference point data and combined with the preset weight coefficient, and to establish a preoperative planning coordinate system with the preoperative treatment center as the origin. The preoperative template generation subunit is used to extract iris features from the preoperative eye image as the first iris biofeature and construct the preoperative iris template. The iris normalization subunit is used to map the iris region in the preoperative eye image from Cartesian coordinates to a polar coordinate normalization space to generate a normalized preoperative iris image; wherein, the preoperative planning coordinate system parameters and the normalized preoperative iris image are output to the iris registration unit for template matching and coordinate mapping.

4. The system according to claim 3, characterized in that, The iris registration unit includes: The intraoperative image acquisition subunit is used to acquire the intraoperative eye images and extract the iris features from the intraoperative eye images as the second iris biometric feature; The intraoperative template generation subunit is used to construct the intraoperative iris template based on the second iris biometrics and perform polar coordinate normalization processing on the intraoperative iris region to generate a normalized intraoperative iris image. The transformation subunit is used to match the preoperative iris template corresponding to the normalized preoperative iris image with the intraoperative iris template corresponding to the normalized intraoperative iris image to obtain the eyeball rotation angle, and the eyeball rotation angle is used to determine the eyeball transformation relationship; The distribution mapping subunit is used to construct a coordinate transformation matrix based on the eye rotation angle, and to map the preoperative target correction distribution data to the intraoperative execution coordinate system based on the preoperative planning coordinate system to obtain the intraoperative target correction distribution data.

5. The system according to claim 4, characterized in that, The iris registration unit further includes at least one of the following sub-units: The correction subunit is used to rotate and correct the preoperatively planned astigmatic axis and the direction angles of each directional higher-order compensation based on the eyeball rotation angle, so as to obtain the intraoperative astigmatic axis and the intraoperative higher-order compensation direction angle. The confidence subunit is used to calculate the registration confidence and registration residuals of the preoperative iris template and the intraoperative iris template. The safety interlock is triggered when any of the following conditions are met: the registration confidence level is lower than the preset minimum registration confidence threshold, the registration residual is higher than the preset maximum allowable registration residual, and the eye rotation angle is higher than the preset maximum allowable eye rotation angle. The error recording and attribution unit is used to collect and store the intraoperative parameter set and bind the intraoperative parameter set with the case data for storage; when refractive deviation occurs after surgery, the postoperative error source is traced based on the stored intraoperative parameter set.

6. The system according to claim 1, characterized in that, The preoperative target correction distribution data generation unit further includes: The conflict detection subunit is used to calculate the difference between any two sets of high-order aberration height distribution data; when the maximum difference exceeds the preset conflict threshold, it is determined that there is a multi-source data conflict. The conflict handling subunit is used to execute a preset control strategy when a multi-source data conflict is detected. The preset control strategy includes one or more of the following: a strategy to reduce the weight of low-confidence sources, a wavefront priority strategy, a corneal height priority strategy, a freeform surface priority strategy, and a depth priority strategy. The constraint control subunit is used to set the upper limit constraint of the higher-order compensation amplitude and the smoothness constraint of the treatment distribution gradient, so as to limit the maximum value of the final higher-order compensation and the steepness of the distribution. The interactive confirmation subunit is used to display any parameter generated by the corneal refractive surgery system to the user interface; after receiving confirmation instructions from the doctor, it locks all parameters and generates an execution log.

7. An integrated corneal refractive surgery device, characterized in that, The device includes: The corneal refractive surgery system as described in any one of claims 1-6; The laser scanning module is communicatively connected to the corneal refractive surgery system and is used to receive the laser scanning data output by the corneal refractive surgery system and output a laser beam based on the laser scanning data.

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