Method and device for measuring human eye parameters based on OCT corneal tomographic images

Abstract

The present invention relates to the technical field of image processing, and discloses a method and device for measuring human eye parameters of corneal tomographic images based on OCT. The method includes: scanning a human eye by an OCT device to obtain OCT image information of the human eye; determining position information of a plurality of segmentation lines of the OCT image information based on a preset segmentation algorithm; determining a plurality of human eye-related position information according to the position information of all the segmentation lines; analyzing first-class human eye parameters of the human eye according to all the human eye-related position information; processing the OCT image based on a preset image processing algorithm to measure second-class human eye parameters of the human eye; and determining the first-class human eye parameters and the second-class human eye parameters as the parameter measurement results of the human eye by the OCT device. It can be seen that implementing the present invention can improve the accuracy and richness of the measured human eye biological parameters, and the utilization rate of the OCT device can be improved by as many human eye biological parameters as possible.

Description

Technical Field

[0001] The present invention relates to the technical field of image processing, and in particular, to a method and device for measuring human eye parameters based on OCT corneal tomographic images. Background Art

[0002] Optical Coherence Tomography (OCT) is a non-invasive optical imaging technique. By scanning the reflected light at different depths, OCT can generate high-resolution tissue tomographic images. And existing ophthalmic imaging systems based on OCT devices mainly include a light source module with a swept-frequency laser, a main interferometer module, a reference arm, a sample arm suitable for the fundus mode, a control circuit module, and an acquisition control and analysis system.

[0003] However, it is found in practice that existing ophthalmic imaging systems based on OCT devices usually can only obtain tomographic structure images of the anterior segment of the eye and the fundus retina, and the measured human eye biological parameters are usually only one or a few of many parameters such as axial length of the eye, central corneal thickness, anterior chamber depth, lens thickness, etc., which are not rich enough, and the utilization rate of OCT devices is poor. It can be seen that it is particularly important to provide a new scheme for measuring human eye parameters based on the tomographic images generated by OCT devices to improve the richness of measured human eye biological parameters. Summary of the Invention

[0004] The present invention provides a method and device for measuring human eye parameters based on OCT corneal tomographic images, which can improve the richness of measured human eye biological parameters, and is beneficial to improving the utilization rate of OCT devices by as many human eye biological parameters as possible.

[0005] To solve the above technical problems, in a first aspect, the present invention discloses a method for measuring human eye parameters based on OCT corneal tomographic images, and the method includes:

[0006] Scanning a human eye with an OCT device to obtain OCT image information of the human eye, where the OCT image information includes the brightness value and / or gray value of the OCT image;

[0007] Based on a preset segmentation algorithm, according to the OCT image information, determining the position information of each of a plurality of segmentation lines in the OCT image information, where the segmentation lines are used to divide the OCT image into a plurality of tomographic images, and the tomographic images at least include corneal tomographic images;

[0008] According to the position information of all the segmentation lines, determining a plurality of human eye-related position information, and each human eye-related position information includes one of corneal position information, retinal position information, iris and lens position information, and choroid position information;

[0009] Analyze the first type of human eye parameters of the human eye according to all the human eye related position information;

[0010] Based on a preset image processing algorithm, process the OCT image to measure the second type of human eye parameters of the human eye, where the second type of human eye parameters includes the white-to-white parameter and the pupil diameter parameter;

[0011] Determine the first type of human eye parameters and the second type of human eye parameters as the parameter measurement results of the human eye by the OCT device.

[0012] As an optional implementation manner, in the first aspect of the present invention, the first type of human eye parameters includes one or more combinations of the axial length of the eye, the central corneal thickness, the retinal thickness, the anterior chamber depth, the lens thickness, the vitreous cavity length, and the choroid thickness;

[0013] And, the analyzing the first type of human eye parameters of the human eye according to all the human eye related position information includes:

[0014] According to all the sub-position information included in all the human eye related position information, determine, from all the sub-position information, the characteristic position information required for measuring human eye related parameters and the parameter type that can be measured by the characteristic position information;

[0015] According to the parameter types corresponding to all the characteristic position information, group all the characteristic position information to obtain a plurality of characteristic position information groups, each of the characteristic position information groups corresponds to a parameter type, and each of the characteristic position information groups includes at least one characteristic position information;

[0016] Process all the characteristic position information within each of the characteristic position information groups to obtain the human eye parameters of the parameter type corresponding to the characteristic position information group;

[0017] Determine the human eye parameters of the parameter types corresponding to all the characteristic position information groups as the first type of human eye parameters.

[0018] As an optional implementation manner, in the first aspect of the present invention, each of the characteristic position information groups specifically includes:

[0019] The highest point position on the corneal surface included in the corneal position information and the retinal surface position included in the retinal position information; or,

[0020] The position information on the upper surface of the cornea included in the corneal position information and the position information on the lower surface of the cornea included in the corneal position information; or,

[0021] The position information of the retinal nerve fiber layer included in the retinal position information and the position information of the outer plexiform layer included in the retinal position information; or,

[0022] The position information of the corneal apex included in the corneal position information and the position information of the anterior surface of the lens included in the iris and lens position information; or,

[0023] The vertex position information of the anterior surface of the lens included in the iris and lens position information and the vertex position information of the posterior surface of the lens included in the iris and lens position information; or,

[0024] The position information of the retinal pigment epithelium layer and the position information of the choroidal junction line included in the retinal position information.

[0025] As an alternative implementation manner, in the first aspect of the present invention, processing the OCT image based on a preset image processing algorithm to measure the second type of human eye parameters of the human eye, including:

[0026] Projecting and synthesizing the OCT image to obtain an annular image corresponding to the OCT image, and preprocessing the annular image to obtain a target annular image, where the preprocessing includes smoothing processing or edge modification; and according to the target annular image, searching for the longest distance of the eyeball boundary of the human eye in the target annular image in the horizontal direction to obtain the white-to-white parameter;

[0027] Performing deformation correction on the OCT image to obtain a corrected OCT image; and measuring the pupil diameter parameter of the human eye according to the corrected OCT image.

[0028] As an alternative implementation manner, in the first aspect of the present invention, the projecting and synthesizing the OCT image to obtain an annular image corresponding to the OCT image includes:

[0029] Based on the Canny edge detection algorithm, performing rectangular detection on the OCT image to obtain rectangular feature data of the OCT image;

[0030] Based on the Hough transform or contour detection algorithm, detecting and extracting the boundary information of the rectangular feature data, where the boundary information includes rectangular position information and / or rectangular dimension information;

[0031] According to the rectangular position information and the rectangular dimension information, calculating annular region parameters corresponding to the rectangular feature data, where the annular region parameters include one or more combinations of the inner diameter of the annular region, the outer diameter of the annular region, and the central position of the annular region;

[0032] Based on the perspective transformation or affine transformation method, according to the annular region parameters, transform the shape of the rectangle corresponding to the rectangular feature data so that the rectangle becomes an annular shape, and update the annular shape to the OCT image to replace the rectangle, thereby obtaining the annular image corresponding to the OCT image.

[0033] As an alternative implementation, in the first aspect of the present invention, the segmentation algorithm includes the shortest path Dijkstra algorithm;

[0034] Moreover, based on the preset segmentation algorithm, according to the OCT image information, determining the position information of each of the plurality of segmentation lines of the OCT image information includes:

[0035] Taking the brightness value or grayscale value included in the OCT image information as a pixel value, calculating to obtain a weight map; flattening the weight map to obtain a flattened image, and the flattened image includes a plurality of target layers;

[0036] Based on the shortest path Dijkstra algorithm, determining the starting point or center point of each target layer as a source node, and according to the source node and the remaining nodes selected from the contour of the target layer except the source node, calculating the path length between the source node and each remaining node, and selecting, from all the remaining nodes, a target node with the shortest path length; determining the line segment between the source node and the target node as the segmentation line of the target layer; and determining the position information of the segmentation line of the target layer according to the positions of the source node and the target node in the flattened image.

[0037] Among them, all the segmentation lines of the OCT image information include the segmentation lines of all the target layers.

[0038] As an alternative implementation, in the first aspect of the present invention, the method further includes:

[0039] Obtaining a first segmentation line with the lowest steepness value and a second segmentation line with the highest steepness value from all the segmentation lines;

[0040] According to the first segmentation line and the second segmentation line, fitting the points of the first segmentation line and the points of the second segmentation line into a circular image to calculate the radius parameter of the circular image;

[0041] Based on a preset corneal curvature radius calculation formula, calculating the corneal curvature radius of the human eye according to the radius parameter, and adding the corneal curvature radius to the parameter measurement result of the human eye.

[0042] The second aspect of the present invention discloses a human eye parameter measurement device for corneal tomographic images based on OCT. The device includes:

[0043] A scanning module for scanning the human eye based on an OCT device to obtain OCT image information of the human eye, where the OCT image information includes the brightness value and / or grayscale value of the OCT image;

[0044] A determination module for determining, based on a preset segmentation algorithm and according to the OCT image information, the position information of each of a plurality of segmentation lines in the OCT image information. The segmentation lines are used to divide the OCT image into a plurality of tomographic images, and the tomographic images at least include corneal tomographic images;

[0045] The determination module is further configured to determine a plurality of human eye-related position information according to the position information of all the segmentation lines. Each piece of human eye-related position information includes one of corneal position information, retinal position information, iris and lens position information, and choroid position information;

[0046] An analysis module for analyzing the first type of human eye parameters of the human eye according to all the human eye-related position information;

[0047] A processing module for processing the OCT image based on a preset image processing algorithm to measure the second type of human eye parameters of the human eye. The second type of human eye parameters includes white-to-white parameters and pupil diameter parameters;

[0048] The determination module is further configured to determine the first type of human eye parameters and the second type of human eye parameters as the parameter measurement results of the human eye by the OCT device.

[0049] As an optional implementation manner, in the second aspect of the present invention, the first type of human eye parameters includes one or a combination of more of axial length, central corneal thickness, retinal thickness, anterior chamber depth, lens thickness, vitreous cavity length, and choroid thickness;

[0050] Moreover, the specific manner in which the analysis module analyzes the first type of human eye parameters of the human eye according to all the human eye-related position information includes:

[0051] According to all the sub-position information included in all the human eye-related position information, determine, from all the sub-position information, the characteristic position information required for measuring human eye-related parameters and the parameter types that the characteristic position information can measure;

[0052] Group all the feature position information according to the parameter types corresponding to all the feature position information, to obtain a plurality of groups of feature position information. Each group of feature position information corresponds to a parameter type, and each group of feature position information includes at least one piece of feature position information;

[0053] Process all the feature position information within each group of feature position information to obtain the human eye parameters of the parameter type corresponding to this group of feature position information;

[0054] Determine the human eye parameters of the parameter types corresponding to all the groups of feature position information as the first type of human eye parameters.

[0055] As an optional implementation manner, in the second aspect of the present invention, each group of feature position information specifically includes:

[0056] The highest point position on the corneal surface included in the corneal position information and the retinal surface position included in the retinal position information; or,

[0057] The position information of the upper corneal surface included in the corneal position information and the position information of the lower corneal surface included in the corneal position information; or,

[0058] The position information of the retinal nerve fiber layer included in the retinal position information and the position information of the outer plexiform layer included in the retinal position information; or,

[0059] The position information of the corneal apex included in the corneal position information and the position information of the anterior surface of the lens included in the iris and lens position information; or,

[0060] The vertex position information of the anterior surface of the lens included in the iris and lens position information and the vertex position information of the posterior surface of the lens included in the iris and lens position information; or,

[0061] The position information of the retinal pigment epithelium layer included in the retinal position information and the position information of the choroidal junction line.

[0062] As an optional implementation manner, in the second aspect of the present invention, the manner in which the processing module processes the OCT image based on a preset image processing algorithm to measure the second type of human eye parameters of the human eye specifically includes:

[0063] Project and synthesize the OCT image to obtain an annular image corresponding to the OCT image, and preprocess the annular image to obtain a target annular image, where the preprocessing includes smoothing processing or edge decoration; and according to the target annular image, find the longest distance of the eyeball boundary of the human eye in the target annular image in the horizontal direction to obtain the white-to-white parameter;

[0064] Perform deformation correction on the OCT image to obtain a corrected OCT image; according to the corrected OCT image, measure the pupil diameter parameter of the human eye.

[0065] As an optional implementation manner, in the second aspect of the present invention, the manner in which the processing module projects and synthesizes the OCT image to obtain an annular image corresponding to the OCT image specifically includes:

[0066] Based on the Canny edge detection algorithm, perform rectangular detection on the OCT image to obtain rectangular feature data of the OCT image;

[0067] Based on the Hough transform or contour detection algorithm, detect and extract the boundary information of the rectangular feature data, where the boundary information includes rectangular position information and / or rectangular size information;

[0068] According to the rectangular position information and the rectangular size information, calculate annular region parameters corresponding to the rectangular feature data, where the annular region parameters include one or more combinations of the inner diameter of the annular region, the outer diameter of the annular region, and the central position of the annular region;

[0069] Based on a perspective transformation or an affine transformation method, according to the annular region parameters, transform the shape of the rectangle corresponding to the rectangular feature data so that the rectangle becomes an annular shape, and update the annular shape to the OCT image to replace the rectangle, to obtain an annular image corresponding to the OCT image.

[0070] As an optional implementation manner, in the second aspect of the present invention, the segmentation algorithm includes the shortest path Dijkstra algorithm;

[0071] Moreover, the manner in which the determination module determines the position information of each of the plurality of segmentation lines of the OCT image information based on a preset segmentation algorithm according to the OCT image information specifically includes:

[0072] Take the brightness value or grayscale value included in the OCT image information as a pixel value, calculate to obtain a weight map; flatten the weight map to obtain a flattened image, and the flattened image includes a plurality of target layers;

[0073] Based on the shortest path Dijkstra algorithm, determine the starting point or the center point of each target layer as the source node, and according to the source node and the remaining nodes selected from the contour of the target layer except the source node, calculate the path length between the source node and each remaining node, and select the target node with the shortest path length from all the remaining nodes; determine the line segment between the source node and the target node as the dividing line of the target layer; determine the position information of the dividing line of the target layer according to the positions of the source node and the target node in the flattened image.

[0074] Among them, all the dividing lines of the OCT image information include the dividing lines of all the target layers.

[0075] As an optional implementation manner, in the second aspect of the present invention, the device further includes:

[0076] An acquisition module, configured to acquire a first dividing line with the lowest steepness value and a second dividing line with the highest steepness value from all the dividing lines;

[0077] A fitting module, configured to fit the points of the first dividing line and the points of the second dividing line into a circular image according to the first dividing line and the second dividing line, so as to calculate the radius parameter of the circular image;

[0078] A calculation module, configured to calculate the corneal curvature radius of the human eye based on a preset corneal curvature radius calculation formula according to the radius parameter, and add the corneal curvature radius to the parameter measurement result of the human eye.

[0079] The third aspect of the present invention discloses another human eye parameter measurement device based on an OCT corneal tomographic image, and the device includes:

[0080] A memory storing executable program code;

[0081] A processor coupled to the memory;

[0082] The processor calls the executable program code stored in the memory and executes the human eye parameter measurement method based on an OCT corneal tomographic image disclosed in the first aspect of the present invention.

[0083] The fourth aspect of the present invention discloses a computer storage medium, and the computer storage medium stores computer instructions, which are used to execute the human eye parameter measurement method based on an OCT corneal tomographic image disclosed in the first aspect of the present invention when being called.

[0084] Compared with the prior art, the embodiments of the present invention have the following beneficial effects:

[0085] In an embodiment of the present invention, the human eye is scanned based on an OCT device to obtain OCT image information of the human eye, where the OCT image information includes the brightness value and / or grayscale value of the OCT image; based on a preset segmentation algorithm, according to the OCT image information, the position information of each of the multiple segmentation lines in the OCT image information is determined, and the segmentation lines are used to divide the OCT image into multiple tomographic images, and the tomographic images at least include corneal tomographic images; according to the position information of all the segmentation lines, multiple human-eye related position information is determined, and each piece of human-eye related position information includes one of corneal position information, retinal position information, iris and lens position information, and choroid position information; according to all the human-eye related position information, the first type of human-eye parameters of the human eye is analyzed; based on a preset image processing algorithm, the OCT image is processed to measure the second type of human-eye parameters of the human eye, and the second type of human-eye parameters includes the white-to-white parameter and the pupil diameter parameter; the first type of human-eye parameters and the second type of human-eye parameters are determined as the parameter measurement results of the human eye by the OCT device. It can be seen that implementing the present invention can scan the human eye based on the OCT device to obtain the OCT image information of the human eye; and based on the preset segmentation algorithm, according to the OCT image information, accurately determine the position information of each of the multiple segmentation lines in the OCT image information, and according to the position information of all the segmentation lines, determine multiple human-eye related position information, which can improve the determination accuracy and efficiency of the human-eye related position information in the OCT image based on the segmentation algorithm. According to all the human-eye related position information, analyze the first type of human-eye parameters of the human eye, which can improve the measurement accuracy and efficiency of the first type of human-eye parameters based on the human-eye related position information; and based on the preset image processing algorithm, process the OCT image to measure the second type of human-eye parameters of the human eye, which can improve the measurement accuracy and efficiency of the second type of human-eye parameters based on the image processing algorithm; then determine the first type of human-eye parameters and the second type of human-eye parameters as the parameter measurement results of the human eye by the OCT device. By providing multiple measurement methods for human-eye parameters, the accuracy and richness of the measured human-eye biological parameters can be improved, the utilization rate of the OCT device can be increased by measuring as many human-eye biological parameters as possible, and it is also beneficial to improve the analysis efficiency and analysis accuracy of the subsequent human-eye biological parameters. BRIEF DESCRIPTION OF THE DRAWINGS

[0086] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0087] Figure 1It is a schematic flow chart of a method for measuring human eye parameters of corneal tomographic images based on OCT disclosed in an embodiment of the present invention;

[0088] Figure 2 It is a schematic diagram of a corneal tomographic image based on an OCT device disclosed in an embodiment of the present invention;

[0089] Figure 3 It is a schematic diagram of a lens tomographic image based on an OCT device disclosed in an embodiment of the present invention;

[0090] Figure 4 It is a schematic diagram of a retinal tomographic image based on an OCT device disclosed in an embodiment of the present invention;

[0091] Figure 5 It is a schematic flow chart of another method for measuring human eye parameters of corneal tomographic images based on OCT disclosed in an embodiment of the present invention;

[0092] Figure 6 It is a schematic diagram of an image related to pupil diameter before correction disclosed in an embodiment of the present invention;

[0093] Figure 7 It is a schematic diagram of an image related to pupil diameter after correction disclosed in an embodiment of the present invention;

[0094] Figure 8 It is a schematic structural diagram of a device for measuring human eye parameters of corneal tomographic images based on OCT disclosed in an embodiment of the present invention;

[0095] Figure 9 It is a schematic structural diagram of another device for measuring human eye parameters of corneal tomographic images based on OCT disclosed in an embodiment of the present invention;

[0096] Figure 10 It is a schematic structural diagram of yet another device for measuring human eye parameters of corneal tomographic images based on OCT. Detailed implementation manners

[0097] In order to enable those skilled in the art to better understand the solution of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without making creative efforts shall fall within the protection scope of the present invention.

[0098] In the description, claims, and above-mentioned drawings of the present invention, terms such as "first" and "second" are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, device, product, or terminal that includes a series of steps or units is not limited to the listed steps or units, but may optionally further include steps or units not listed, or may optionally further include other steps or units inherent to these processes, methods, products, or terminals.

[0099] Reference to "embodiment" herein means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the present invention. The phrase appears in various places in the specification and does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment mutually exclusive with other embodiments. Those skilled in the art will explicitly and implicitly understand that the embodiments described herein can be combined with other embodiments.

[0100] The present invention discloses a method and device for measuring human eye parameters based on OCT corneal tomographic images, which can scan the human eye based on an OCT device to obtain OCT image information of the human eye; and based on a preset segmentation algorithm, according to the OCT image information, accurately determine the position information of each segmentation line among a plurality of segmentation lines of the OCT image information, and determine a plurality of human eye-related position information according to the position information of all segmentation lines, which can improve the determination accuracy and efficiency of human eye-related position information in the OCT image based on the segmentation algorithm, analyze the first type of human eye parameters of the human eye according to all human eye-related position information, and can improve the measurement accuracy and efficiency of the first type of human eye parameters based on the human eye-related position information; and based on a preset image processing algorithm, process the OCT image to measure the second type of human eye parameters of the human eye, and can improve the measurement accuracy and efficiency of the second type of human eye parameters based on the image processing algorithm; then determine the first type of human eye parameters and the second type of human eye parameters as the parameter measurement results of the human eye by the OCT device. By providing multiple measurement methods for human eye parameters, the accuracy and richness of the measured human eye biological parameters can be improved, the utilization rate of the OCT device can be increased by measuring as many human eye biological parameters as possible, and it is also beneficial to improve the analysis efficiency and analysis accuracy of subsequent human eye biological parameters. The following will be described in detail respectively.

[0101] Embodiment 1

[0102] Please refer to Figure 1 , Figure 1 which is a schematic flowchart of a method for measuring human eye parameters based on OCT corneal tomographic images disclosed in an embodiment of the present invention. Among them, Figure 1The described method for measuring human eye parameters based on OCT corneal tomographic images can be applied to a device for measuring human eye parameters based on OCT corneal tomographic images. Among them, the device may include a measuring device or a measuring server. Among them, the measuring server may include a cloud server or a local server, which is not limited in the embodiments of the present invention. As Figure 1 shown, the method for measuring human eye parameters based on OCT corneal tomographic images may include the following operations:

[0103] 101. Scan the human eye with an OCT device to obtain OCT image information of the human eye.

[0104] In the embodiments of the present invention, the OCT image information may include the brightness value and / or grayscale value of the OCT image.

[0105] 102. Based on a preset segmentation algorithm, determine the position information of each segmentation line among multiple segmentation lines of the OCT image information according to the OCT image information.

[0106] In the embodiments of the present invention, optionally, the segmentation algorithm may be the shortest path algorithm or other algorithms that can achieve the same segmentation purpose. Among them, the shortest path algorithm calculates by traversing the brightness value / grayscale value on the OCT image to obtain the specific position of the segmentation line. The segmentation line can be used to divide the OCT image into multiple tomographic images. Optionally, the tomographic images may at least include corneal tomographic images, and may also include at least one of retinal tomographic images, iris tomographic images, lens tomographic images, and choroid tomographic images, which is not limited in the embodiments of the present invention. Exemplarily, as Figures 2 - 4 shown, among them, Figure 2 is a schematic diagram of a corneal tomographic image based on an OCT device disclosed in the embodiments of the present invention, Figure 3 is a schematic diagram of a lens tomographic image based on an OCT device disclosed in the embodiments of the present invention, Figure 4 is a schematic diagram of a retinal tomographic image based on an OCT device disclosed in the embodiments of the present invention.

[0107] 103. Determine multiple human eye-related position information according to the position information of all the segmentation lines.

[0108] In an embodiment of the present invention, optionally, each human eye related position information may include one of corneal position information, retinal position information, iris and lens position information, and choroid position information. Among them, the corneal position information may include at least one of the position information of the upper surface of the cornea, the position information of the lower surface of the cornea, the position information of the anterior surface of the cornea, and the position information of the posterior surface of the cornea. The retinal position information may include at least one of the position information of the retinal nerve fiber layer (RNFL), the position information of the outer plexiform layer (OPL), the position information of the inner limiting membrane of the retina, and the position information of the retinal pigment epithelium (RPE) layer. The iris and lens position information may include at least one of the iris position information, the position information of the anterior surface of the lens, the position information of the posterior surface of the lens, and the position information of the posterior capsule of the lens. The choroid position information may include the position information of the choroid / sclera junction, which is not limited in the embodiment of the present invention.

[0109] 104. Analyze the first type of human eye parameters of the human eye based on all the human eye related position information.

[0110] In an embodiment of the present invention, optionally, the first type of human eye parameters may include one or a combination of more of the axial length (Axial length, AXL), central corneal thickness (Central corneal thickness, CCT), retinal thickness (Retinal thickness, RT), anterior chamber depth, lens thickness (Lens thickness, LT), vitreous cavity length (Vitreous thickness, VT), and choroid thickness (choroidal thickness, CT), which is not limited in the embodiment of the present invention.

[0111] 105. Process the OCT image based on a preset image processing algorithm to measure the second type of human eye parameters of the human eye.

[0112] In an embodiment of the present invention, the second type of human eye parameters may include the white to white parameter (White to white, WTW) and the pupil diameter parameter (Pupil diameter, PD).

[0113] In an embodiment of the present invention, there is no sequence preference between step 105 and steps 102 - 104, that is, step 105 may occur before steps 102 - 104, may occur after steps 102 - 104, or may occur simultaneously with steps 102 - 104, which is not limited in the embodiment of the present invention.

[0114] 106. Determine the first type of human eye parameters and the second type of human eye parameters as the parameter measurement results of the human eye by the OCT device.

[0115] In an embodiment of the present invention, optionally, the measured human eye biological parameters can be used as the basis for subsequent analysis of the cause of the human eye, and can also be used as the basis for generating the treatment strategy for the cause of the human eye. The embodiments of the present invention do not make limitations.

[0116] It can be seen that implementing Figure 1 The described method for measuring human eye parameters based on OCT corneal tomographic images can scan the human eye based on the OCT device to obtain the OCT image information of the human eye; and based on a preset segmentation algorithm, according to the OCT image information, accurately determine the position information of each segmentation line among the multiple segmentation lines of the OCT image information, and according to the position information of all segmentation lines, determine multiple human eye-related position information, which can improve the determination accuracy and efficiency of the human eye-related position information in the OCT image based on the segmentation algorithm. According to all human eye-related position information, analyze the first type of human eye parameters, which can improve the measurement accuracy and efficiency of the first type of human eye parameters based on the human eye-related position information; and based on a preset image processing algorithm, process the OCT image to measure the second type of human eye parameters, which can improve the measurement accuracy and efficiency of the second type of human eye parameters based on the image processing algorithm; then determine the first type of human eye parameters and the second type of human eye parameters as the parameter measurement results of the human eye by the OCT device. By providing multiple measurement methods for human eye parameters, the accuracy and richness of the measured human eye biological parameters can be improved, the utilization rate of the OCT device can be increased by measuring as many human eye biological parameters as possible, and it is also beneficial to improve the subsequent analysis efficiency and analysis accuracy of human eye biological parameters.

[0117] In an optional embodiment, the above-mentioned step 104 of analyzing the first type of human eye parameters of the human eye according to all human eye-related position information may include:

[0118] According to all sub-position information included in all human eye-related position information, determine, from all sub-position information, the characteristic position information required for measuring human eye-related parameters and the parameter types that can be measured by the characteristic position information;

[0119] According to the parameter types corresponding to all characteristic position information, group all characteristic position information to obtain multiple groups of characteristic position information. Each group of characteristic position information corresponds to a parameter type, and each group of characteristic position information includes at least one piece of characteristic position information;

[0120] Process all characteristic position information within each group of characteristic position information to obtain the human eye parameters of the parameter type corresponding to the group of characteristic position information;

[0121] Determine the human eye parameters of the parameter type corresponding to all the characteristic position information groups as the first type of human eye parameters.

[0122] Exemplarily, taking the corneal position information as an example, all the relevant position information of the cornea includes the position information of the upper and lower surfaces of the cornea, the position information of the front and back surfaces, and the position information of the intersection points with other tomographic images. Then, determine the position information of the upper and lower surfaces of the cornea and the position information of the front and back surfaces as the characteristic position information for measuring relevant human eye parameters. At this time, the parameter types that can be measured include the axial length type and / or the central corneal thickness.

[0123] It can be seen that this optional embodiment can accurately determine, from all the sub-position information included in all the relevant human eye position information, the characteristic position information required for measuring relevant human eye parameters and the parameter types that the characteristic position information can measure; and group all the characteristic position information according to the parameter types corresponding to all the characteristic position information to obtain multiple characteristic position information groups, which is beneficial to improving the accuracy and reliability of the grouped characteristic position information groups. Subsequently, process all the characteristic position information within each characteristic position information group to obtain the human eye parameters of the parameter type corresponding to this characteristic position information group, and can accurately measure the human eye parameters of the corresponding parameter type based on the accurately grouped characteristic position information groups. Then, determine the human eye parameters of the parameter type corresponding to all the characteristic position information groups as the first type of human eye parameters, which can improve the measurement accuracy and reliability of the first type of human eye parameters based on the segmentation algorithm.

[0124] In this optional embodiment, as an optional implementation manner, each characteristic position information group may specifically include:

[0125] The highest point position of the corneal surface included in the corneal position information and the retinal surface position included in the retinal position information; or,

[0126] The position information of the upper surface of the cornea included in the corneal position information and the position information of the lower surface of the cornea included in the corneal position information; or,

[0127] The position information of the retinal nerve fiber layer included in the retinal position information and the position information of the outer plexiform layer included in the retinal position information; or,

[0128] The position information of the corneal vertex included in the corneal position information and the position information of the anterior surface of the lens included in the iris and lens position information; or,

[0129] The vertex position information of the anterior surface of the lens included in the iris and lens position information and the vertex position information of the posterior surface of the lens included in the iris and lens position information; or,

[0130] The position information of the retina includes the position information of the retinal pigment epithelium layer and the position information of the choroidal junction line.

[0131] In an embodiment of the present invention, specifically, all the characteristic position information in each group of characteristic position information is processed to obtain the human eye parameters of the corresponding parameter type, which may include:

[0132] For each piece of characteristic position information, when the group of characteristic position information includes the highest point position on the corneal surface included in the corneal position information and the retinal surface position included in the retinal position information, a vertical line perpendicular to the corneal surface is drawn at the highest point position, and the vertical line is extended to the retinal surface position, and the length of the vertical line is calculated as the axial length of the human eye; and / or,

[0133] When the group of characteristic position information includes the position information of the upper corneal surface and the position information of the lower corneal surface included in the corneal position information, the position difference between the upper corneal surface and the lower corneal surface is calculated according to the position information of the upper corneal surface and the position information of the lower corneal surface as the central corneal thickness of the human eye; and / or,

[0134] When the group of characteristic position information includes the position information of the retinal nerve fiber layer and the position information of the outer plexiform layer included in the retinal position information, the position difference between the retinal nerve fiber layer and the outer plexiform layer is calculated according to the position information of the retinal nerve fiber layer and the position information of the outer plexiform layer as the retinal thickness of the human eye; and / or,

[0135] When the group of characteristic position information includes the position information of the corneal apex included in the corneal position information and the position information of the anterior surface of the lens included in the iris and lens position information, the position difference between the corneal apex and the anterior surface of the lens is calculated according to the position information of the corneal apex and the position information of the anterior surface of the lens as the anterior chamber depth of the human eye; and / or,

[0136] When the group of characteristic position information includes the position information of the anterior surface of the lens and the position information of the posterior surface of the lens, the position difference between the anterior surface of the lens and the posterior surface of the lens is calculated according to the position information of the anterior surface of the lens and the position information of the posterior surface of the lens as the lens thickness of the human eye; and / or,

[0137] When the group of characteristic position information includes the position information of the posterior capsule of the lens and the position information of the retinal nerve fiber epithelium layer, the retinal nerve fiber epithelium layer is used as the inner limiting membrane of the retina, and the distance between the posterior capsule of the lens and the inner limiting membrane of the retina is calculated according to the position information of the posterior capsule of the lens and the position information of the retinal nerve fiber epithelium layer to obtain the vitreous cavity length of the human eye; and / or,

[0138] When the feature position information group includes the position information of the retinal pigment epithelium layer and the position information of the choroid / sclera junction, according to the position information of the retinal pigment epithelium layer and the position information of the choroid / sclera junction, calculate the position difference between the retinal pigment epithelium layer and the choroid / sclera junction as the choroid thickness of the human eye.

[0139] It can be seen that this optional implementation can improve the measurement accuracy and reliability of the human eye parameters of the parameter type corresponding to each feature position information group by providing a feature position information group with diverse information.

[0140] Embodiment 2

[0141] Please refer to Figure 5 , Figure 5 which is a schematic flowchart of another method for measuring human eye parameters based on OCT corneal tomographic images disclosed in the embodiments of the present invention. Among them, Figure 5 the described method for measuring human eye parameters based on OCT corneal tomographic images can be applied to a device for measuring human eye parameters based on OCT corneal tomographic images. Among them, the device can include a measuring device or a measuring server. Among them, the measuring server can include a cloud server or a local server, which is not limited in the embodiments of the present invention. As Figure 5 shown, the method for measuring human eye parameters based on OCT corneal tomographic images can include the following operations:

[0142] 201. Scan the human eye based on the OCT device to obtain the OCT image information of the human eye.

[0143] In the embodiments of the present invention, the specific manner of scanning the human eye based on the OCT device to obtain the OCT image information of the human eye can be the cross scan mode under the corneal detection mode of the OCT device, and multiple OCT images of the human eye at circular intervals are scanned, such as: 8, 16 or 32 images.

[0144] 202. Based on a preset segmentation algorithm, determine the position information of each segmentation line among the multiple segmentation lines of the OCT image information according to the OCT image information.

[0145] 203. Determine multiple human eye related position information according to the position information of all the segmentation lines.

[0146] 204. Analyze the first type of human eye parameters of the human eye according to all the human eye related position information.

[0147] 205. Project and synthesize the OCT image to obtain a circular image corresponding to the OCT image; and preprocess the circular image to obtain a target circular image.

[0148] In the embodiments of the present invention, the preprocessing includes smoothing processing or edge decoration. Specifically, integral projection is performed on the OCT images in each direction of the circular intervals obtained by scanning to obtain a separated rectangular projection map, and then the rectangular projection map is synthesized into an annular image, and then the annular image is subjected to smoothing processing or edge decoration to obtain a target annular image.

[0149] 206. According to the target annular image, search for the longest distance of the eyeball boundary of the human eye in the target annular image in the horizontal direction to obtain the white-to-white parameter.

[0150] In the embodiments of the present invention, the boundaries of the eyeball and the pupil can be seen on the annular diagram, and the longest distance of the eyeball boundary in the horizontal direction is the white-to-white distance.

[0151] 207. Perform deformation correction on the OCT image to obtain a corrected OCT image; according to the corrected OCT image, measure the pupil diameter parameter of the human eye.

[0152] In the embodiments of the present invention, specifically, deformation correction is performed on the pupil diameter-related image included in the OCT image, so as to measure the pupil diameter parameter of the human eye through the corrected pupil diameter-related image. Exemplarily, as Figures 6 - 7 shown, Figure 6 is a schematic diagram of a pupil diameter-related image before correction disclosed in the embodiments of the present invention, Figure 7 is a schematic diagram of a pupil diameter-related image after correction disclosed in the embodiments of the present invention.

[0153] In the embodiments of the present invention, there is no order between steps 205 - 207 and steps 202 - 204, that is, steps 205 - 207 can occur before steps 202 - 204, can occur after steps 202 - 204, or can occur simultaneously with steps 202 - 204, and the embodiments of the present invention do not make a limitation.

[0154] 208. Determine the first type of human eye parameters and the second type of human eye parameters as the parameter measurement results of the human eye by the OCT device.

[0155] In the embodiments of the present invention, for other descriptions of steps 201 - 204 and step 208, please refer to the detailed descriptions of steps 101 - 104 and step 106 in Embodiment 1, and the embodiments of the present invention will not be repeated.

[0156] It can be seen that the implementation Figure 5The described method for measuring human eye parameters based on OCT corneal tomographic images can scan the human eye using an OCT device to obtain OCT image information of the human eye; and based on a preset segmentation algorithm, according to the OCT image information, accurately determine the position information of each segmentation line among multiple segmentation lines of the OCT image information. According to the position information of all segmentation lines, determine multiple human eye-related position information, which can improve the determination accuracy and efficiency of human eye-related position information in the OCT image based on the segmentation algorithm. According to all human eye-related position information, analyze the first type of human eye parameters, which can improve the measurement accuracy and efficiency of the first type of human eye parameters based on the human eye-related position information; and based on a preset image processing algorithm, process the OCT image to measure the second type of human eye parameters, which can improve the measurement accuracy and efficiency of the second type of human eye parameters based on the image processing algorithm; then determine the first type of human eye parameters and the second type of human eye parameters as the parameter measurement results of the human eye by the OCT device. By providing multiple measurement methods for human eye parameters, it is possible to improve the accuracy and richness of the measured human eye biological parameters, improve the utilization rate of the OCT device by measuring as many human eye biological parameters as possible, and is also conducive to improving the analysis efficiency and analysis accuracy of subsequent human eye biological parameters. In addition, it is also possible to perform various image processing operations such as projection and synthesis on the scanned OCT image to obtain an annular image and perform smoothing processing or edge decoration on it, so as to accurately find the longest distance of the eyeball boundary in the processed target annular image to obtain the white-to-white parameter, which is conducive to improving the accuracy and reliability of the measured white-to-white parameter; and through the image processing operation of deforming and correcting the scanned OCT image, it is possible to accurately measure the pupil diameter parameter of the human eye, and use the white-to-white parameter and the pupil diameter parameter as the second type of human eye parameters, which is conducive to improving the measurement accuracy and reliability of the second type of human eye parameters based on the image processing algorithm.

[0157] In an alternative embodiment, the projection and synthesis of the OCT image in step 205 to obtain the annular image corresponding to the OCT image may include:

[0158] Based on the Canny edge detection algorithm, perform rectangular detection on the OCT image to obtain the rectangular feature data of the OCT image;

[0159] Based on the Hough transform or contour detection algorithm, detect and extract the boundary information of the rectangular feature data, and the boundary information includes rectangular position information and / or rectangular size information;

[0160] According to the rectangular position information and the rectangular size information, calculate the annular region parameters corresponding to the rectangular feature data, and the annular region parameters include one or more combinations of the inner diameter of the annular region, the outer diameter of the annular region, and the central position of the annular region;

[0161] Based on the perspective transformation or affine transformation method, according to the parameters of the annular region, transform the shape of the rectangle corresponding to the rectangular feature data so that the rectangle becomes an annular shape, and update the annular shape to the OCT image to replace the rectangle, obtaining the annular image corresponding to the OCT image.

[0162] In the embodiments of the present invention, specifically, first, use the method based on the Canny edge detection algorithm to detect the rectangle, and then use the Hough transform or contour detection method to detect and extract the boundary of the rectangle. After that, according to the position and size information of the rectangle, calculate the parameters of the corresponding annular region, such as the inner diameter, outer diameter, and center position. Geometric calculation methods can be used, for example, calculate the inner diameter and outer diameter through the size of the rectangle, or calculate the center position through the position of the rectangle, and then use the perspective transformation or affine transformation to transform the shape of the rectangle to make it an annular shape (for example: apply the transformation matrix to perform perspective transformation or affine transformation on the rectangle to make its shape an annular shape). Specifically, the calculation of the parameters of the annular region can be achieved by calibrating the four corner points of the rectangle and the four corresponding corner points of the target annular region. Specifically, when calibrating the rectangular image, the advanced deep learning algorithm is adopted. First, a large number of test and training datasets related to the human eye need to be carefully prepared, and then a convolutional neural network (including VGG network, ResNet network, and MobileNet series, etc.) is selected to comprehensively process this image dataset. Then, according to the output results, the parameters of the model are carefully adjusted to continuously improve the performance of the model. After obtaining the final training parameters, by using the OCT device to capture the human eye image, the white-to-white and pupil ranges can be obtained, and with the help of the position information of the picture, the detailed information of the white-to-white and pupil diameters can be successfully obtained.

[0163] It can be seen that this optional embodiment can detect the rectangle in the OCT image based on the Canny edge detection algorithm, obtain the rectangular feature data of the OCT image, and based on the Hough transform or contour detection algorithm, detect and extract the boundary information of the rectangular feature data. The boundary information includes the rectangular position information and / or the rectangular size information, which can improve the detection accuracy of the rectangular position information and rectangular size information for determining the annular region of the OCT image; then, according to the rectangular position information and rectangular size information, accurately calculate the parameters of the annular region corresponding to the rectangular feature data; and then, based on the perspective transformation or affine transformation method, according to the annular region parameters, transform the shape of the rectangle corresponding to the rectangular feature data so that the rectangle becomes an annular shape, and update the annular shape to the OCT image to replace the rectangle, obtaining the annular image corresponding to the OCT image, which can improve the transformation accuracy and reliability of transforming the OCT image into an annular image based on the perspective transformation and affine transformation.

[0164] In another alternative embodiment, the segmentation algorithm includes the shortest path Dijkstra algorithm. Moreover, based on the preset segmentation algorithm in step 202 above, determining the position information of each segmentation line among multiple segmentation lines of the OCT image information according to the OCT image information may include:

[0165] Taking the luminance value or grayscale value included in the OCT image information as the pixel value, calculating to obtain a weight map; flattening the weight map to obtain a flattened image, and the flattened image includes multiple target layers;

[0166] Based on the shortest path Dijkstra algorithm, determining the starting point or center point of each target layer as the source node, and according to the source node and the remaining nodes other than the source node selected from the contour of the target layer, calculating the path length between the source node and each remaining node, and selecting the target node with the shortest path length from all the remaining nodes; determining the line segment between the source node and the target node as the segmentation line of the target layer; determining the position information of the segmentation line of the target layer according to the positions of the source node and the target node in the flattened image.

[0167] Among them, all the segmentation lines of the OCT image information include the segmentation lines of all the target layers.

[0168] In the embodiments of the present invention, specifically, when calculating the weight map, taking the luminance value as an example, a brighter area may have a higher weight value, while a darker area may have a lower weight value to calculate the weight map. Flattening the weight map to obtain a flattened image may include: flattening the weight map, that is, sorting the pixel points in the image according to the weight value to form a one-dimensional image representation, and rearranging the original OCT image according to the sorted pixel values to form a flattened image.

[0169] Optionally, each target layer may include one of a corneal layer, a retinal layer, an iris layer, a lens layer, and a choroid layer.

[0170] Taking the retinal layer as an example, select the starting point or center point of the retinal layer as the source node, start from the source node, select multiple other nodes from the contour of the retinal layer and gradually expand to other nodes, and select the shortest path by comparing the path lengths, so as to obtain the segmentation line for the retinal layer in the OCT image.

[0171] It can be seen that in this optional embodiment, the brightness value or grayscale value included in the OCT image information can be used as a pixel value, and the weight map can be accurately calculated; then the weight map is flattened to obtain a flattened image, which is beneficial to improving the determination accuracy of the flattened image used as the calculation basis for the shortest path length algorithm; subsequently, based on the shortest path Dijkstra algorithm, the starting point or center point of each target layer is determined as the source node, and according to the source node and the remaining nodes other than the source node selected from the contour of the target layer, the path length between the source node and each remaining node is accurately calculated, and the target node with the shortest path length is selected from all the remaining nodes; the line segment between the source node and the target node is determined as the dividing line of the target layer, which can improve the determination accuracy of the node corresponding to the shortest path length, thereby improving the determination accuracy of the dividing line of each target layer; then, according to the positions of the source node and the target node in the flattened image, the position information of the dividing line of the target layer is determined, which can improve the determination accuracy and reliability of the dividing line position information.

[0172] In yet another optional embodiment, the method may further include:

[0173] Obtain a first dividing line with the lowest steepness value and a second dividing line with the highest steepness value from all the dividing lines;

[0174] According to the first dividing line and the second dividing line, fit the points of the first dividing line and the points of the second dividing line into a circular image to calculate the radius parameter of the circular image;

[0175] Based on a preset corneal curvature radius calculation formula, calculate the corneal curvature radius of the human eye according to the radius parameter, and add the corneal curvature radius to the parameter measurement result of the human eye.

[0176] In the embodiments of the present invention, for the dividing lines in different directions, the dividing line with the lowest steepness value and the dividing line with the highest steepness value are obtained. Then, the least squares fitting method is used to fit the points on these two dividing lines into a circle. The specific fitting method is as follows: Let the equation of the circle be ; where (a, b) is the center coordinate of the circle and r is the radius. For a given series of points (x i , y i ), the sum of the squares of the distances from these points to the fitted circle should be minimized. The error function can be expressed as: , and then the partial derivatives of a, b, and r are calculated respectively and set to 0 to solve for the optimal parameters. By solving the above equations simultaneously, the curvature radius r of the fitted circle can be obtained. The corneal curvature radius calculation formula can be K = (n1 - n2) / r, where n1 represents the refractive index of air and n2 represents the refractive index of corneal aqueous humor. In this way, the corneal curvature radii at different angles can be obtained, such as the flat K value and the steep K value.

[0177] It can be seen that this optional embodiment can obtain the first dividing line with the lowest steepness value and the second dividing line with the highest steepness value from all the dividing lines, and based on the first dividing line and the second dividing line, fit the points of the first dividing line and the points of the second dividing line into a circular image to calculate the radius parameter of the circular image, which can improve the calculation accuracy and reliability of the radius of the circular image; then based on the preset corneal curvature radius calculation formula, according to the radius parameter, accurately calculate the corneal curvature radius of the human eye, and add the corneal curvature radius to the parameter measurement result of the human eye, which can improve the diversity and richness of the measured human eye biological parameters to a certain extent.

[0178] Embodiment III

[0179] Please refer to Figure 8 , Figure 8 which is a schematic structural diagram of a human eye parameter measurement device for OCT-based corneal tomographic images disclosed in an embodiment of the present invention. Among them, Figure 8 the described human eye parameter measurement device for OCT-based corneal tomographic images may include a measurement device or a measurement server. Among them, the measurement server may include a cloud server or a local server, which is not limited in the embodiments of the present invention. As Figure 8 shown, the human eye parameter measurement device for OCT-based corneal tomographic images may include:

[0180] A scanning module 301, configured to scan the human eye based on an OCT device to obtain OCT image information of the human eye, where the OCT image information includes the brightness value and / or grayscale value of the OCT image.

[0181] A determination module 302, configured to determine the position information of each dividing line among a plurality of dividing lines of the OCT image information based on a preset segmentation algorithm, where the dividing line is used to divide the OCT image into a plurality of tomographic images, and the tomographic images at least include corneal tomographic images.

[0182] The determination module 302 is further configured to determine a plurality of human eye-related position information according to the position information of all the dividing lines, and each human eye-related position information includes one of corneal position information, retinal position information, iris and lens position information, and choroid position information.

[0183] An analysis module 303, configured to analyze the first type of human eye parameters of the human eye according to all the human eye-related position information.

[0184] A processing module 304, configured to process the OCT image based on a preset image processing algorithm to measure the second type of human eye parameters of the human eye, and the second type of human eye parameters includes the white-to-white parameter and the pupil diameter parameter.

[0185] The determination module 302 is further configured to determine the first type of human eye parameters and the second type of human eye parameters as the parameter measurement results of the human eye by the OCT device.

[0186] It can be seen that implementing Figure 8 the described human eye parameter measurement device based on OCT corneal tomographic images can scan the human eye based on the OCT device to obtain the OCT image information of the human eye; and based on a preset segmentation algorithm, according to the OCT image information, accurately determine the position information of each segmentation line among the multiple segmentation lines of the OCT image information, and according to the position information of all segmentation lines, determine multiple human eye-related position information, which can improve the determination accuracy and efficiency of human eye-related position information in the OCT image based on the segmentation algorithm. According to all human eye-related position information, analyze the first type of human eye parameters, which can improve the measurement accuracy and efficiency of the first type of human eye parameters based on the human eye-related position information; and based on a preset image processing algorithm, process the OCT image to measure the second type of human eye parameters, which can improve the measurement accuracy and efficiency of the second type of human eye parameters based on the image processing algorithm; then determine the first type of human eye parameters and the second type of human eye parameters as the parameter measurement results of the human eye by the OCT device. By providing multiple measurement methods for human eye parameters, it can improve the accuracy and richness of the measured human eye biological parameters, can improve the utilization rate of the OCT device through as many measured human eye biological parameters as possible, and is also conducive to improving the subsequent analysis efficiency and analysis accuracy of human eye biological parameters.

[0187] In an optional embodiment, the first type of human eye parameters includes one or more combinations of axial length of the eye, central corneal thickness, retinal thickness, anterior chamber depth, lens thickness, vitreous cavity length, and choroid thickness. And the specific way for the analysis module 303 to analyze the first type of human eye parameters according to all human eye-related position information may include:

[0188] According to all sub-position information included in all human eye-related position information, determine from all sub-position information the characteristic position information required for measuring human eye-related parameters and the parameter types that the characteristic position information can measure;

[0189] According to the parameter types corresponding to all characteristic position information, group all characteristic position information to obtain multiple groups of characteristic position information. Each group of characteristic position information corresponds to a parameter type, and each group of characteristic position information includes at least one piece of characteristic position information;

[0190] Process all characteristic position information within each group of characteristic position information to obtain the human eye parameters of the parameter type corresponding to the group of characteristic position information;

[0191] Determine the human eye parameters of the parameter type corresponding to all feature position information groups as the first type of human eye parameters.

[0192] It can be seen that this optional embodiment can accurately determine, from all sub-position information included in all human eye-related position information, the feature position information required for measuring human eye-related parameters and the parameter types that the feature position information can measure; and group all feature position information according to the parameter types corresponding to all feature position information to obtain multiple feature position information groups, which is beneficial to improving the accuracy and reliability of the grouped feature position information groups. Subsequently, process all feature position information within each feature position information group to obtain the human eye parameters of the parameter type corresponding to this feature position information group, and can accurately measure the human eye parameters of the corresponding parameter type based on the accurately grouped feature position information groups. Then determine the human eye parameters of the parameter type corresponding to all feature position information groups as the first type of human eye parameters, which can improve the measurement accuracy and reliability of the first type of human eye parameters based on the segmentation algorithm.

[0193] In this optional embodiment, as an optional implementation manner, each feature position information group may specifically include:

[0194] The highest point position on the corneal surface included in the corneal position information and the retinal surface position included in the retinal position information; or,

[0195] The position information of the upper corneal surface included in the corneal position information and the position information of the lower corneal surface included in the corneal position information; or,

[0196] The position information of the retinal nerve fiber layer included in the retinal position information and the position information of the outer plexiform layer included in the retinal position information; or,

[0197] The position information of the corneal vertex included in the corneal position information and the position information of the anterior surface of the lens included in the iris and lens position information; or,

[0198] The vertex position information of the anterior surface of the lens included in the iris and lens position information and the vertex position information of the posterior surface of the lens included in the iris and lens position information; or,

[0199] The position information of the retinal pigment epithelium layer included in the retinal position information and the position information of the choroidal junction line.

[0200] It can be seen that this optional implementation manner can improve the measurement accuracy and reliability of the human eye parameters of the parameter type corresponding to each feature position information group by providing feature position information groups with diverse information.

[0201] In another optional embodiment, the processing module 304 processes the OCT image based on a preset image processing algorithm. The specific manner of measuring the second type of human eye parameters of the human eye includes:

[0202] Project and synthesize the OCT image to obtain an annular image corresponding to the OCT image, and preprocess the annular image to obtain a target annular image. The preprocessing includes smoothing processing or edge modification; and according to the target annular image, find the longest distance of the eyeball boundary of the human eye in the target annular image in the horizontal direction to obtain the white-to-white parameter;

[0203] Perform deformation correction on the OCT image to obtain a corrected OCT image; according to the corrected OCT image, measure the pupil diameter parameter of the human eye.

[0204] It can be seen that this optional embodiment can perform various image processing operations such as projection and synthesis on the scanned OCT image to obtain an annular image and perform smoothing processing or edge modification on it, so as to accurately find the longest distance of the eyeball boundary in the obtained target annular image to obtain the white-to-white parameter, which is beneficial to improving the accuracy and reliability of the measured white-to-white parameter; and through the image processing operation of performing deformation correction on the scanned OCT image, it is possible to accurately measure the pupil diameter parameter of the human eye, and using the white-to-white parameter and the pupil diameter parameter as the second type of human eye parameters is beneficial to improving the measurement accuracy and reliability of the second type of human eye parameters based on the image processing algorithm.

[0205] In this optional embodiment, as an optional implementation manner, the specific manner in which the processing module 304 projects and synthesizes the OCT image to obtain an annular image corresponding to the OCT image may include:

[0206] Based on the Canny edge detection algorithm, perform rectangular detection on the OCT image to obtain the rectangular feature data of the OCT image;

[0207] Based on the Hough transform or contour detection algorithm, detect and extract the boundary information of the rectangular feature data. The boundary information includes rectangular position information and / or rectangular dimension information;

[0208] According to the rectangular position information and the rectangular dimension information, calculate the annular region parameters corresponding to the rectangular feature data. The annular region parameters include one or more combinations of the inner diameter of the annular region, the outer diameter of the annular region, and the central position of the annular region;

[0209] Based on a perspective transformation or an affine transformation method, according to the annular region parameters, transform the shape of the rectangle corresponding to the rectangular feature data so that the rectangle becomes an annular shape, update the annular shape to the OCT image to replace the rectangle, and obtain the annular image corresponding to the OCT image.

[0210] It can be seen that this optional embodiment can perform rectangular detection on the OCT image based on the Canny edge detection algorithm to obtain the rectangular feature data of the OCT image, and based on the Hough transform or the contour detection algorithm, detect and extract the boundary information of the rectangular feature data. The boundary information includes the rectangular position information and / or the rectangular dimension information, which can improve the detection accuracy of the rectangular position information and the rectangular dimension information for determining the annular region of the OCT image; subsequently, according to the rectangular position information and the rectangular dimension information, accurately calculate the annular region parameters corresponding to the rectangular feature data; and then based on the perspective transformation or the affine transformation method, according to the annular region parameters, transform the shape of the rectangle corresponding to the rectangular feature data so that the rectangle becomes an annular shape, update the annular shape to the OCT image to replace the rectangle, and obtain the annular image corresponding to the OCT image, which can improve the transformation accuracy and reliability of transforming the OCT image into an annular image based on the perspective transformation and the affine transformation.

[0211] In another optional embodiment, the segmentation algorithm includes the shortest path Dijkstra algorithm. Moreover, the manner in which the determination module 302 determines the position information of each segmentation line among the multiple segmentation lines of the OCT image information based on the preset segmentation algorithm may specifically include:

[0212] Take the brightness value or the gray value included in the OCT image information as the pixel value, and calculate to obtain a weight map; flatten the weight map to obtain a flattened image, and the flattened image includes multiple target layers;

[0213] Based on the shortest path Dijkstra algorithm, determine the starting point or the center point of each target layer as the source node, and according to the source node and the remaining nodes selected from the contour of the target layer except the source node, calculate the path length between the source node and each remaining node, and select the target node with the shortest path length from all the remaining nodes; determine the line segment between the source node and the target node as the segmentation line of the target layer; according to the positions of the source node and the target node in the flattened image, determine the position information of the segmentation line of the target layer;

[0214] Among them, all the segmentation lines of the OCT image information include the segmentation lines of all the target layers.

[0215] It can be seen that in this alternative embodiment, the brightness value or grayscale value included in the OCT image information can be used as the pixel value, and the weight map can be accurately calculated; and the weight map is flattened to obtain a flattened image, which is beneficial to improving the determination accuracy of the flattened image used as the calculation basis for the shortest path length algorithm; subsequently, based on the shortest path Dijkstra algorithm, the starting point or center point of each target layer is determined as the source node, and according to the source node and the remaining nodes other than the source node selected from the contour of the target layer, the path length between the source node and each remaining node is accurately calculated, and the target node with the shortest path length is selected from all the remaining nodes; the line segment between the source node and the target node is determined as the dividing line of the target layer, which can improve the determination accuracy of the node corresponding to the shortest path length, thereby improving the determination accuracy of the dividing line of each target layer; then, according to the positions of the source node and the target node in the flattened image, the position information of the dividing line of the target layer is determined, which can improve the determination accuracy and reliability of the dividing line position information.

[0216] In another alternative embodiment, as Figure 9 shown, Figure 9 FIG. is a schematic structural diagram of another human eye parameter measurement device based on OCT corneal tomographic images disclosed in an embodiment of the present invention. Among them, the device may further include:

[0217] An acquisition module 305, configured to acquire a first dividing line with the lowest steepness value and a second dividing line with the highest steepness value from all the dividing lines;

[0218] A fitting module 306, configured to fit the points of the first dividing line and the points of the second dividing line into a circular image according to the first dividing line and the second dividing line, so as to calculate the radius parameter of the circular image;

[0219] A calculation module 307, configured to calculate the corneal curvature radius of the human eye based on a preset corneal curvature radius calculation formula according to the radius parameter, and add the corneal curvature radius to the parameter measurement result of the human eye.

[0220] It can be seen that in this alternative embodiment, the first dividing line with the lowest steepness value and the second dividing line with the highest steepness value can be acquired from all the dividing lines, and according to the first dividing line and the second dividing line, the points of the first dividing line and the points of the second dividing line are fitted into a circular image to calculate the radius parameter of the circular image, which can improve the calculation accuracy and reliability of the circular image radius; then, based on a preset corneal curvature radius calculation formula, according to the radius parameter, the corneal curvature radius of the human eye is accurately calculated, and the corneal curvature radius is added to the parameter measurement result of the human eye, which can improve the diversity and richness of the measured human eye biological parameters to a certain extent.

[0221] Embodiment 4

[0222] Please refer to Figure 10 , Figure 10 which is a schematic structural diagram of another human eye parameter measurement device based on OCT corneal tomographic images disclosed in an embodiment of the present invention. As Figure 10 shown, the human eye parameter measurement device based on OCT corneal tomographic images may include:

[0223] A memory 401 storing executable program code;

[0224] A processor 402 coupled to the memory 401;

[0225] The processor 402 calls the executable program code stored in the memory 401 and executes the steps in the method for measuring human eye parameters based on OCT corneal tomographic images described in Embodiment 1 or Embodiment 2 of the present invention.

[0226] Embodiment Five

[0227] An embodiment of the present invention discloses a computer storage medium storing computer instructions, which are used to execute the steps in the method for measuring human eye parameters based on OCT corneal tomographic images described in Embodiment 1 or Embodiment 2 of the present invention when the computer instructions are called.

[0228] Embodiment Six

[0229] An embodiment of the present invention discloses a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to cause a computer to execute the steps in the method for measuring human eye parameters based on OCT corneal tomographic images described in Embodiment 1 or Embodiment 2.

[0230] The device embodiments described above are merely illustrative. The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical modules, that is, they may be located in one place or distributed to multiple network modules. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. A person of ordinary skill in the art can understand and implement it without creative labor.

[0231] Through the specific descriptions of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on such an understanding, the above technical solutions, in essence, or the parts that contribute to the prior art can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, and the storage medium includes read-only memory (ROM), random access memory (RAM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), one-time programmable read-only memory (OTPROM), electrically-erasable programmable read-only memory (EEPROM), compact disc read-only memory (CD-ROM) or other optical disc memories, magnetic disk memories, tape memories, or any other computer-readable medium that can be used to carry or store data.

[0232] Finally, it should be noted that: the method and device for measuring human eye parameters of corneal tomographic images based on OCT disclosed in the embodiments of the present invention only disclose the preferred embodiments of the present invention, and are only used to illustrate the technical solutions of the present invention, rather than to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for measuring human eye parameters of corneal tomographic images based on OCT, characterized in that, The method includes: Scanning the human eye based on an OCT device to obtain OCT image information of the human eye, where the OCT image information includes the brightness value and / or grayscale value of the OCT image; Based on a preset segmentation algorithm, determining the position information of each of a plurality of segmentation lines in the OCT image information according to the OCT image information, where the segmentation lines are used to divide the OCT image into a plurality of tomographic images, and the tomographic images include corneal tomographic images, retinal tomographic images, iris tomographic images, lens tomographic images, and choroidal tomographic images; Determining a plurality of human eye-related position information according to the position information of all the segmentation lines, where each human eye-related position information includes one of corneal position information, retinal position information, iris and lens position information, and choroidal position information; Analyzing the first type of human eye parameters of the human eye according to all the human eye-related position information; Processing the OCT image based on a preset image processing algorithm to measure the second type of human eye parameters of the human eye, where the second type of human eye parameters includes white-to-white parameters and pupil diameter parameters; Determining the first type of human eye parameters and the second type of human eye parameters as the parameter measurement results of the human eye by the OCT device; Wherein, the first type of human eye parameters includes axial length, central corneal thickness, retinal thickness, anterior chamber depth, lens thickness, vitreous cavity length, and choroidal thickness; And, the analyzing the first type of human eye parameters of the human eye according to all the human eye-related position information includes: Determining, from all the sub-position information included in all the human eye-related position information, the characteristic position information required for measuring human eye-related parameters and the parameter types that can be measured by the characteristic position information; Grouping all the characteristic position information according to the parameter types corresponding to all the characteristic position information to obtain a plurality of characteristic position information groups, where each characteristic position information group corresponds to a parameter type, and each characteristic position information group includes at least one characteristic position information; Processing all the characteristic position information in each characteristic position information group to obtain the human eye parameters of the parameter type corresponding to the characteristic position information group; Determining the human eye parameters of the parameter types corresponding to all the characteristic position information groups as the first type of human eye parameters; Wherein, each characteristic position information group specifically includes: The highest point position on the corneal surface included in the corneal position information and the retinal surface position included in the retinal position information; or, The position information of the upper corneal surface included in the corneal position information and the position information of the lower corneal surface included in the corneal position information; or, The position information of the retinal nerve fiber layer included in the retinal position information and the position information of the outer plexiform layer included in the retinal position information; or, The position information of the corneal apex included in the corneal position information and the position information of the anterior lens surface included in the iris and lens position information; or, The vertex position information of the anterior surface of the lens included in the iris-lens position information and the vertex position information of the posterior surface of the lens included in the iris-lens position information; or, The position information of the posterior capsule of the lens included in the iris-lens position information and the position information of the retinal neuroepithelial layer included in the retinal position information; or, The position information of the retinal pigment epithelium layer included in the retinal position information and the position information of the choroid / sclera junction included in the choroid position information; And, processing all the feature position information within each of the feature position information groups to obtain the human eye parameters of the parameter type corresponding to the feature position information group, including: For each of the feature position information, when the feature position information group includes the highest point position of the corneal surface included in the corneal position information and the retinal surface position included in the retinal position information, draw a vertical line perpendicular to the corneal surface at the highest point position, extend the vertical line to the retinal surface position, and calculate the length of the vertical line as the axial length of the human eye; When the feature position information group includes the position information of the upper surface of the cornea and the position information of the lower surface of the cornea included in the corneal position information, calculate the position difference between the upper surface of the cornea and the lower surface of the cornea as the central corneal thickness of the human eye according to the position information of the upper surface of the cornea and the position information of the lower surface of the cornea; When the feature position information group includes the position information of the retinal nerve fiber layer and the position information of the outer plexiform layer included in the retinal position information, calculate the position difference between the retinal nerve fiber layer and the outer plexiform layer as the retinal thickness of the human eye according to the position information of the retinal nerve fiber layer and the position information of the outer plexiform layer; When the feature position information group includes the position information of the corneal vertex included in the corneal position information and the position information of the anterior surface of the lens included in the iris-lens position information, calculate the position difference between the corneal vertex and the anterior surface of the lens as the anterior chamber depth of the human eye according to the position information of the corneal vertex and the position information of the anterior surface of the lens; When the feature position information group includes the vertex position information of the anterior surface of the lens and the vertex position information of the posterior surface of the lens, calculate the position difference between the anterior surface of the lens and the posterior surface of the lens as the lens thickness of the human eye according to the vertex position information of the anterior surface of the lens and the vertex position information of the posterior surface of the lens; When the feature position information group includes the position information of the posterior capsule of the lens and the position information of the retinal neuroepithelial layer, take the retinal neuroepithelial layer as the inner limiting membrane of the retina, and calculate the distance between the posterior capsule of the lens and the inner limiting membrane of the retina according to the position information of the posterior capsule of the lens and the position information of the retinal neuroepithelial layer to obtain the vitreous cavity length of the human eye; When the feature position information group includes the position information of the retinal pigment epithelium layer and the position information of the choroid / sclera junction, according to the position information of the retinal pigment epithelium layer and the position information of the choroid / sclera junction, calculate the position difference between the retinal pigment epithelium layer and the choroid / sclera junction as the choroid thickness of the human eye.

2. The method for measuring human eye parameters based on OCT corneal tomographic images according to claim 1, characterized in that, Based on a preset image processing algorithm, process the OCT image to measure the second type of human eye parameters of the human eye, including: Perform projection and synthesis on the OCT image to obtain a circular image corresponding to the OCT image, and perform preprocessing on the circular image to obtain a target circular image, where the preprocessing includes smoothing processing or edge modification; and according to the target circular image, find the longest distance of the eyeball boundary of the human eye in the target circular image in the horizontal direction to obtain the white-to-white parameter; Perform deformation correction on the OCT image to obtain a corrected OCT image; according to the corrected OCT image, measure the pupil diameter parameter of the human eye.

3. The method for measuring human eye parameters based on OCT corneal tomographic images according to claim 2, wherein, The performing projection and synthesis on the OCT image to obtain a circular image corresponding to the OCT image includes: Based on the Canny edge detection algorithm, perform rectangular detection on the OCT image to obtain the rectangular feature data of the OCT image; Based on the Hough transform or contour detection algorithm, detect and extract the boundary information of the rectangular feature data, where the boundary information includes rectangular position information and / or rectangular size information; According to the rectangular position information and the rectangular size information, calculate the annular region parameters corresponding to the rectangular feature data, where the annular region parameters include one or more combinations of the inner diameter of the annular region, the outer diameter of the annular region, and the central position of the annular region; Based on the perspective transformation or affine transformation method, according to the annular region parameters, transform the shape of the rectangle corresponding to the rectangular feature data to make the rectangle into a circular ring, and update the circular ring to the OCT image to replace the rectangle to obtain a circular image corresponding to the OCT image.

4. The method for measuring human eye parameters based on OCT corneal tomographic images according to any one of claims 1-3, characterized in that, The segmentation algorithm includes the shortest path Dijkstra algorithm; And, based on a preset segmentation algorithm, according to the OCT image information, determine the position information of each of the multiple segmentation lines of the OCT image information, including: Use the brightness value or gray value included in the OCT image information as the pixel value, calculate to obtain a weight map; flatten the weight map to obtain a flattened image, where the flattened image includes multiple target layers; Based on the shortest path Dijkstra algorithm, determine the starting point or the center point of each of the target layers as the source node, and according to the source node and the remaining nodes selected from the contour of the target layer excluding the source node, calculate the path lengths between the source node and each of the remaining nodes, and select the target node with the shortest path length from all the remaining nodes; determine the line segment between the source node and the target node as the dividing line of the target layer; determine the position information of the dividing line of the target layer according to the positions of the source node and the target node in the flattened image. Among them, all the dividing lines of the OCT image information include the dividing lines of all the target layers.

5. The method for measuring human eye parameters based on OCT corneal tomographic images according to claim 4, characterized in that The method further includes: Obtain the first dividing line with the lowest steepness value and the second dividing line with the highest steepness value from all the dividing lines; According to the first dividing line and the second dividing line, fit the points of the first dividing line and the points of the second dividing line into a circular image to calculate the radius parameter of the circular image; Based on a preset corneal curvature radius calculation formula, calculate the corneal curvature radius of the human eye according to the radius parameter, and add the corneal curvature radius to the parameter measurement results of the human eye.

6. An apparatus for measuring human eye parameters of corneal tomographic images based on OCT, characterized in that, The device includes: A scanning module, configured to scan the human eye based on an OCT device to obtain the OCT image information of the human eye, where the OCT image information includes the brightness value and / or the gray value of the OCT image; A determination module, configured to determine the position information of each dividing line among the multiple dividing lines of the OCT image information based on a preset segmentation algorithm, where the dividing lines are used to divide the OCT image into multiple tomographic images, and the tomographic images include corneal tomographic images, retinal tomographic images, iris tomographic images, lens tomographic images, and choroid tomographic images; The determination module is further configured to determine multiple human eye-related position information according to the position information of all the dividing lines, and each human eye-related position information includes one of corneal position information, retinal position information, iris and lens position information, and choroid position information; An analysis module, configured to analyze the first type of human eye parameters of the human eye according to all the human eye-related position information; A processing module, configured to process the OCT image based on a preset image processing algorithm to measure the second type of human eye parameters of the human eye, where the second type of human eye parameters includes the white-to-white parameter and the pupil diameter parameter; The determination module is further configured to determine the first type of human eye parameters and the second type of human eye parameters as the parameter measurement results of the human eye obtained by the OCT device; Among them, the first type of human eye parameters includes axial length, central corneal thickness, retinal thickness, anterior chamber depth, lens thickness, vitreous cavity length, and choroid thickness; Moreover, the manner in which the analysis module analyzes the first type of human eye parameters of the human eye according to all the human eye-related position information specifically includes: Based on all the sub-position information included in all the human eye-related position information, determine, from all the sub-position information, the characteristic position information required for measuring human eye-related parameters and the parameter types that can be measured by the characteristic position information; Group all the characteristic position information according to the parameter types corresponding to all the characteristic position information, to obtain a plurality of groups of characteristic position information. Each group of characteristic position information corresponds to a parameter type, and each group of characteristic position information includes at least one piece of characteristic position information; Process all the characteristic position information within each group of characteristic position information to obtain the human eye parameters of the parameter type corresponding to this group of characteristic position information; Determine the human eye parameters of the parameter types corresponding to all the groups of characteristic position information as the first type of human eye parameters; Among them, each group of characteristic position information specifically includes: The highest point position on the corneal surface included in the corneal position information and the retinal surface position included in the retinal position information; or, The position information of the upper corneal surface included in the corneal position information and the position information of the lower corneal surface included in the corneal position information; or, The position information of the retinal nerve fiber layer included in the retinal position information and the position information of the outer plexiform layer included in the retinal position information; or, The position information of the corneal apex included in the corneal position information and the position information of the anterior lens surface included in the iris and lens position information; or, The apex position information of the anterior lens surface included in the iris and lens position information and the apex position information of the posterior lens surface included in the iris and lens position information; or, The position information of the posterior lens capsule included in the iris and lens position information and the position information of the retinal neuroepithelial layer included in the retinal position information; or, The position information of the retinal pigment epithelium layer included in the retinal position information and the position information of the choroid / sclera junction included in the choroid position information; Moreover, the manner in which the analysis module processes all the characteristic position information within each group of characteristic position information to obtain the human eye parameters of the parameter type corresponding to this group of characteristic position information specifically includes: For each piece of characteristic position information, when this group of characteristic position information includes the highest point position on the corneal surface included in the corneal position information and the retinal surface position included in the retinal position information, draw a vertical line perpendicular to the corneal surface at the highest point position, extend the vertical line to the retinal surface position, and calculate the length of the vertical line as the axial length of the human eye; When this group of characteristic position information includes the position information of the upper corneal surface and the position information of the lower corneal surface included in the corneal position information, calculate the position difference between the upper corneal surface and the lower corneal surface according to the position information of the upper corneal surface and the position information of the lower corneal surface as the central corneal thickness of the human eye; When the characteristic position information group includes the position information of the retinal nerve fiber layer and the position information of the outer plexiform layer included in the retinal position information, calculate the position difference between the retinal nerve fiber layer and the outer plexiform layer according to the position information of the retinal nerve fiber layer and the position information of the outer plexiform layer, and use it as the retinal thickness of the human eye; When the characteristic position information group includes the position information of the corneal apex included in the corneal position information and the position information of the anterior surface of the lens included in the iris and lens position information, calculate the position difference between the corneal apex and the anterior surface of the lens according to the position information of the corneal apex and the position information of the anterior surface of the lens, and use it as the anterior chamber depth of the human eye; When the characteristic position information group includes the vertex position information of the anterior surface of the lens and the vertex position information of the posterior surface of the lens, calculate the position difference between the anterior surface of the lens and the posterior surface of the lens according to the vertex position information of the anterior surface of the lens and the vertex position information of the posterior surface of the lens, and use it as the lens thickness of the human eye; When the characteristic position information group includes the position information of the posterior capsule of the lens and the position information of the retinal neuroepithelial layer, use the retinal neuroepithelial layer as the inner limiting membrane of the retina, and calculate the distance between the posterior capsule of the lens and the inner limiting membrane of the retina according to the position information of the posterior capsule of the lens and the position information of the retinal neuroepithelial layer to obtain the vitreous cavity length of the human eye; When the characteristic position information group includes the position information of the retinal pigment epithelium and the position information of the choroid / sclera junction, calculate the position difference between the retinal pigment epithelium and the choroid / sclera junction according to the position information of the retinal pigment epithelium and the position information of the choroid / sclera junction, and use it as the choroid thickness of the human eye.

7. An apparatus for measuring human eye parameters of corneal tomographic images based on OCT, characterized in that, The device includes: A memory storing executable program code; A processor coupled to the memory; The processor calls the executable program code stored in the memory and executes the method for measuring human eye parameters based on OCT corneal tomographic images according to any one of claims 1-5.

8. A computer storage medium, characterized in that, The computer storage medium stores computer instructions which, when called, are used to execute the method for measuring human eye parameters based on OCT corneal tomographic images according to any one of claims 1-5.

Images