CN113662506A - Corneal surface morphology measuring method, device, medium and electronic equipment - Google Patents
Corneal surface morphology measuring method, device, medium and electronic equipment Download PDFInfo
- Publication number
- CN113662506A CN113662506A CN202111131161.0A CN202111131161A CN113662506A CN 113662506 A CN113662506 A CN 113662506A CN 202111131161 A CN202111131161 A CN 202111131161A CN 113662506 A CN113662506 A CN 113662506A
- Authority
- CN
- China
- Prior art keywords
- image
- cornea
- eye
- preset direction
- curvature
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Images
Classifications
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B3/00—Apparatus for testing the eyes; Instruments for examining the eyes
- A61B3/10—Objective types, i.e. instruments for examining the eyes independent of the patients' perceptions or reactions
- A61B3/107—Objective types, i.e. instruments for examining the eyes independent of the patients' perceptions or reactions for determining the shape or measuring the curvature of the cornea
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B3/00—Apparatus for testing the eyes; Instruments for examining the eyes
- A61B3/0016—Operational features thereof
- A61B3/0033—Operational features thereof characterised by user input arrangements
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/21—Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
- G06F18/214—Generating training patterns; Bootstrap methods, e.g. bagging or boosting
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/30—Computing systems specially adapted for manufacturing
Landscapes
- Life Sciences & Earth Sciences (AREA)
- Engineering & Computer Science (AREA)
- Health & Medical Sciences (AREA)
- Physics & Mathematics (AREA)
- Medical Informatics (AREA)
- Surgery (AREA)
- Veterinary Medicine (AREA)
- Public Health (AREA)
- General Health & Medical Sciences (AREA)
- Animal Behavior & Ethology (AREA)
- Molecular Biology (AREA)
- Data Mining & Analysis (AREA)
- Theoretical Computer Science (AREA)
- Heart & Thoracic Surgery (AREA)
- Biophysics (AREA)
- Ophthalmology & Optometry (AREA)
- Biomedical Technology (AREA)
- Artificial Intelligence (AREA)
- General Physics & Mathematics (AREA)
- General Engineering & Computer Science (AREA)
- Bioinformatics & Computational Biology (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Evolutionary Computation (AREA)
- Evolutionary Biology (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Eye Examination Apparatus (AREA)
Abstract
The application discloses a method and a device for measuring the surface morphology of a cornea, a computer readable storage medium and an electronic device, wherein a first eye image and a second eye image with different shooting angles are respectively obtained and identified; then, obtaining a three-dimensional image of the cornea according to the first cornea image and the second cornea image, and selecting a plurality of image points in the three-dimensional image along a preset direction; finally, calculating the curvature in the preset direction according to the plurality of image points, and fitting to obtain the surface morphology of the cornea according to the plurality of image points and the curvature in the preset direction; the method comprises the steps of constructing two staggered two-dimensional images to obtain a three-dimensional image, selecting a plurality of image points in the three-dimensional image to calculate curvature, and fitting according to the curvature to obtain the cornea form, so that the measurement difficulty is reduced, the image point position coordinates of the cornea image can be accurately obtained by utilizing image recognition, and the cornea form can be accurately fitted.
Description
Technical Field
The application relates to the technical field of image processing, in particular to a method and a device for measuring corneal surface morphology, a computer-readable storage medium and electronic equipment.
Background
The cornea is the most anterior, transparent portion of the eye, covering the iris, pupil and anterior chamber, and providing the eye with 70% of its refractive power, and small changes in the cornea can cause large changes in refractive state, and thus, much effort has been made to study the shape and optical characteristics of the cornea. The accurate measurement of the corneal curvature and the Corneal Central Thickness (CCT) provides important basis for early diagnosis of corneal diseases, preoperative screening and postoperative follow-up of corneal refractive surgery, intraocular lens degree calculation and the like, and has important significance for intraocular pressure correction, glaucoma investigation and the like.
Most of the existing methods for measuring the cornea morphology are calculated based on the refraction or reflection of light, however, the propagation of light is easily interfered by external media, and the final measurement result has large deviation due to small influence. Moreover, the measurement by light propagation requires a patient to be well-matched, and the measurement result has a great influence on patients with poor or even non-matched matching.
Disclosure of Invention
The present application is proposed to solve the above-mentioned technical problems. Embodiments of the present application provide a method and an apparatus for measuring corneal surface topography, a computer-readable storage medium, and an electronic device, which solve the above-mentioned problem of inaccurate corneal topography measurement.
According to one aspect of the present application, there is provided a method for measuring corneal topography, comprising: respectively acquiring a first eye image and a second eye image with different shooting angles; identifying a first eye cornea image and a second eye cornea image of the first eye image and the second eye image, respectively; obtaining a three-dimensional image of the cornea according to the first cornea image and the second cornea image; selecting a plurality of image points in the three-dimensional image along a preset direction; calculating the curvature of the preset direction according to the plurality of image points; and fitting to obtain the surface morphology of the cornea of the eye according to the plurality of image points and the curvature in the preset direction.
In an embodiment, the selecting a plurality of image points in the three-dimensional image along a predetermined direction includes: acquiring a central point of the three-dimensional image; calculating the spacing distance between the boundary point of the three-dimensional image and the central point; selecting a connecting line of the boundary point with the minimum and/or maximum spacing distance and the central point along the curved surface of the cornea as the preset direction; and equally spacing and selecting the plurality of image points in the preset direction.
In an embodiment, said calculating the curvature of the preset direction from the plurality of image points comprises: and calculating the curvature in the preset direction according to the distance of the plurality of image points along the preset direction and the straight-line distance of the plurality of image points.
In an embodiment, the fitting to obtain the corneal surface morphology of the eye according to the plurality of image points and the curvature of the preset direction includes: fitting to obtain a curved surface equation of the preset direction according to the plurality of image points and the curvature of the preset direction; and fitting according to the curved surface equation to obtain the surface morphology of the cornea.
In an embodiment, the respectively acquiring the first eye image and the second eye image with different shooting angles includes: and respectively acquiring the first eye image and the second eye image by using a binocular camera.
In an embodiment, the identifying the first and second corneal images of the first and second eye images, respectively, comprises: and respectively inputting the first eye image and the second eye image into a first neural network model to obtain the first eye cornea image and the second eye cornea image.
In an embodiment, before the obtaining the three-dimensional image of the cornea of the eye according to the first cornea image and the second cornea image, the method for measuring the surface morphology of the cornea further includes: acquiring a first distance and a second distance between two shooting lenses of the binocular camera and eyes of a patient; acquiring a third distance between two shooting lenses of the binocular camera; the obtaining of the three-dimensional image of the cornea of the eye according to the first image of the cornea and the second image of the cornea of the eye comprises: and constructing a three-dimensional image of the cornea of the eye according to the first cornea image, the second cornea image, the first distance, the second distance and the third distance.
According to another aspect of the present application, there is provided a corneal topography measuring device comprising: the acquisition module is used for respectively acquiring a first eye image and a second eye image with different shooting angles; an identification module, configured to identify a first eye cornea image and a second eye cornea image of the first eye image and the second eye image, respectively; the construction module is used for obtaining a three-dimensional image of the cornea according to the first cornea image and the second cornea image; the selecting module is used for selecting a plurality of image points in the three-dimensional image along a preset direction; a curvature calculating module, configured to calculate a curvature of the preset direction according to the plurality of image points; and the fitting module is used for fitting to obtain the surface morphology of the cornea according to the plurality of image points and the curvature of the preset direction.
According to another aspect of the present application, there is provided a computer-readable storage medium storing a computer program for executing the method of measuring corneal surface topography as described in any one of the above.
According to another aspect of the present application, there is provided an electronic apparatus including: a processor; and a memory for storing the processor-executable instructions; the processor is used for executing any one of the methods for measuring the surface morphology of the cornea.
According to the method and the device for measuring the surface morphology of the cornea, the computer-readable storage medium and the electronic equipment, the first eye image and the second eye image with different shooting angles are respectively obtained, and the first eye cornea image and the second eye cornea image in the first eye image and the second eye image are respectively identified; then, obtaining a three-dimensional image of the cornea according to the first cornea image and the second cornea image, and selecting a plurality of image points in the three-dimensional image along a preset direction; finally, calculating the curvature in the preset direction according to the plurality of image points, and fitting to obtain the surface morphology of the cornea according to the plurality of image points and the curvature in the preset direction; the method comprises the steps of constructing two staggered two-dimensional images to obtain a three-dimensional image, selecting a plurality of image points in the three-dimensional image to calculate curvature, and fitting according to the curvature to obtain the cornea form, so that the measurement difficulty is reduced, the image point position coordinates of the cornea image can be accurately obtained by utilizing image recognition, and the cornea form can be accurately fitted.
Drawings
The above and other objects, features and advantages of the present application will become more apparent by describing in more detail embodiments of the present application with reference to the attached drawings. The accompanying drawings are included to provide a further understanding of the embodiments of the application and are incorporated in and constitute a part of this specification, illustrate embodiments of the application and together with the description serve to explain the principles of the application. In the drawings, like reference numbers generally represent like parts or steps.
Fig. 1 is a schematic flow chart of a method for measuring corneal topography according to an exemplary embodiment of the present disclosure.
Fig. 2 is a flowchart illustrating an image point selecting method according to an exemplary embodiment of the present application.
Fig. 3 is a schematic flow chart of a method for measuring corneal topography according to another exemplary embodiment of the present disclosure.
Fig. 4 is a schematic structural diagram of a corneal topography measuring device according to an exemplary embodiment of the present application.
Fig. 5 is a schematic structural diagram of a corneal topography measuring device according to another exemplary embodiment of the present application.
Fig. 6 is a block diagram of an electronic device provided in an exemplary embodiment of the present application.
Detailed Description
Hereinafter, example embodiments according to the present application will be described in detail with reference to the accompanying drawings. It should be understood that the described embodiments are only some embodiments of the present application and not all embodiments of the present application, and that the present application is not limited by the example embodiments described herein.
Fig. 1 is a schematic flow chart of a method for measuring corneal topography according to an exemplary embodiment of the present disclosure. As shown in fig. 1, the method for measuring the morphology of the corneal surface includes:
step 110: a first eye image and a second eye image with different shooting angles are respectively obtained.
The specific implementation of step 110 may be: the method comprises the steps of respectively obtaining a first eye image and a second eye image by using a binocular camera, or obtaining the eye images by using two cameras at different shooting angles to obtain the first eye image and the second eye image, namely obtaining two staggered eye images. Specifically, the acquired first eye image and the second eye image may be one or more frames of images captured from video data. Because the patient may not be matched when the cornea image is collected, especially for children or babies, the method and the device can acquire a section of video data by shooting, and select one or more frames of images as the first eye image and the second eye image. Specifically, the method for selecting the eye image may be manually completed, or may be automatically selected, that is, the video data is converted into multi-frame image data, and then the multi-frame image data is selected, specifically, an image with the maximum opening degree of opening of the eye (that is, an image with the maximum distance between the upper eyelid and the lower eyelid) in the multi-frame image data is selected, so that the screened image can completely display the cornea region image.
Step 120: a first eye cornea image and a second eye cornea image of the first eye image and the second eye image are identified, respectively.
The specific implementation of step 120 may be: and respectively inputting the first eye image and the second eye image into the trained recognition model to obtain a first eye cornea image and a second eye cornea image. And inputting the first eye image and the second eye image into the recognition model respectively by using the trained recognition model (such as a neural network model) to obtain a first eye cornea image and a second eye cornea image. The training process of the recognition model can be training by using a standard eye image and a corresponding cornea image.
Step 130: and obtaining a three-dimensional image of the cornea according to the first cornea image and the second cornea image.
After the first cornea image and the second cornea image which are staggered with each other are obtained, a three-dimensional image containing the cornea can be constructed according to the first cornea image and the second cornea image, and the three-dimensional image of the cornea can be obtained.
Step 140: and selecting a plurality of image points in the three-dimensional image along a preset direction.
After obtaining the three-dimensional image of the cornea of the eye, a plurality of image points in the three-dimensional image are selected, wherein the image points may be points at specific positions, for example, a plurality of image points located on the image of the cornea of the eye along a preset direction.
Step 150: the curvature in the preset direction is calculated according to a plurality of image points.
According to the selected image points, the curvature in the preset direction can be calculated, that is, the curvature in the preset direction (the curvature of the cornea image in the preset direction) is calculated according to the image points in the preset direction. Specifically, the specific implementation manner of step 150 may be: and calculating the curvature in the preset direction according to the distance of the plurality of image points along the preset direction and the straight-line distance of the plurality of image points.
Step 160: and fitting according to the plurality of image points and the curvature in the preset direction to obtain the surface morphology of the cornea of the eye.
And after the curvature in the preset direction is obtained through calculation, fitting according to the plurality of selected image points and the curvature in the preset direction to obtain the surface morphology of the cornea. Specifically, the specific implementation manner of step 160 may be: and fitting according to the plurality of image points and the curvature in the preset direction to obtain a curved surface equation in the preset direction, and fitting according to the curved surface equation to obtain the surface morphology of the cornea. Firstly, a curved surface equation in a preset direction is obtained through fitting according to a plurality of image points and the curvature in the preset direction, wherein the preset direction can be a plurality of directions, and after the curved surface equation in the preset direction is obtained, a spherical surface equation (namely surface morphology) of the whole cornea is obtained through fitting according to the plurality of curved surface equations.
According to the method for measuring the surface morphology of the cornea, a first eye image and a second eye image with different shooting angles are respectively obtained, and the first eye cornea image and the second eye cornea image in the first eye image and the second eye image are respectively identified; then, obtaining a three-dimensional image of the cornea according to the first cornea image and the second cornea image, and selecting a plurality of image points in the three-dimensional image along a preset direction; finally, calculating the curvature in the preset direction according to the plurality of image points, and fitting to obtain the surface morphology of the cornea according to the plurality of image points and the curvature in the preset direction; the method comprises the steps of constructing two staggered two-dimensional images to obtain a three-dimensional image, selecting a plurality of image points in the three-dimensional image to calculate curvature, and fitting according to the curvature to obtain the cornea form, so that the measurement difficulty is reduced, the image point position coordinates of the cornea image can be accurately obtained by utilizing image recognition, and the cornea form can be accurately fitted.
Fig. 2 is a flowchart illustrating an image point selecting method according to an exemplary embodiment of the present application. As shown in fig. 2, the step 140 may include:
step 141: and acquiring a central point of the three-dimensional image.
Step 142: and calculating the spacing distance between the boundary point and the central point of the three-dimensional image.
The form direction of the cornea image is determined by acquiring the central point of the three-dimensional image, namely the central point of the cornea image, and then calculating the interval distance between the boundary point of the three-dimensional image and the central point.
Step 143: and selecting a connecting line of the boundary point and the central point with the minimum and/or maximum spacing distance along the curved surface of the cornea as a preset direction.
The connecting line between the boundary point with the minimum and/or maximum spacing distance (i.e. the boundary point closest and/or farthest to the central point) and the centerline point along the corneal curvature is selected as a predetermined direction, that is, the curve of the boundary point closest or farthest to the central point is selected as a predetermined direction.
Step 144: a plurality of image points are selected at equal intervals in a predetermined direction.
By setting the preset interval, a plurality of image points are selected at equal intervals in the preset direction according to the preset interval, so that a plurality of image points representing the curve of the preset direction are obtained.
Fig. 3 is a schematic flow chart of a method for measuring corneal topography according to another exemplary embodiment of the present disclosure. As shown in fig. 3, before step 130, the method for measuring the surface morphology of the cornea may further include:
step 170: a first distance and a second distance between two photographing lenses of a binocular camera and eyes of a patient are acquired.
Step 180: and acquiring a third distance between the two shooting lenses of the binocular camera.
By acquiring the first distance and the second distance between the two shooting lenses of the binocular camera and the eyes of the patient and the third distance between the two shooting lenses of the binocular camera, the dislocation distance between the first eye image and the second eye image which are obtained by shooting through the two shooting lenses of the binocular camera can be calculated by utilizing the optical principle, so that the three-dimensional image of the cornea can be accurately constructed.
Correspondingly, step 130 is adjusted to: and constructing a three-dimensional image of the cornea according to the first cornea image, the second cornea image, the first distance, the second distance and the third distance.
Fig. 4 is a schematic structural diagram of a corneal topography measuring device according to an exemplary embodiment of the present application. As shown in fig. 4, the corneal topography measuring apparatus 40 includes: an obtaining module 41, configured to obtain a first eye image and a second eye image with different shooting angles, respectively; an identifying module 42, configured to identify a first eye cornea image and a second eye cornea image of the first eye image and the second eye image, respectively; a constructing module 43, configured to obtain a three-dimensional image of a cornea of an eye according to the first cornea image and the second cornea image; a selecting module 44, configured to select a plurality of image points in the three-dimensional image along a preset direction; a curvature calculating module 45, configured to calculate a curvature in a preset direction according to the plurality of image points; and a fitting module 46 for fitting the plurality of image points and the curvature in the preset direction to obtain the surface morphology of the cornea.
According to the corneal surface morphology measuring device provided by the application, the acquisition module 41 is used for respectively acquiring the first eye image and the second eye image with different shooting angles, and the identification module 42 is used for respectively identifying the first eye cornea image and the second eye cornea image in the first eye image and the second eye image; then, the constructing module 43 obtains a three-dimensional image of the cornea of the eye according to the first cornea image and the second cornea image, and the selecting module 44 selects a plurality of image points in the three-dimensional image along a preset direction; finally, the curvature calculation module 45 calculates the curvature in the preset direction according to the plurality of image points, and the fitting module 46 fits the plurality of image points and the curvature in the preset direction to obtain the surface morphology of the cornea; the method comprises the steps of constructing two staggered two-dimensional images to obtain a three-dimensional image, selecting a plurality of image points in the three-dimensional image to calculate curvature, and fitting according to the curvature to obtain the cornea form, so that the measurement difficulty is reduced, the image point position coordinates of the cornea image can be accurately obtained by utilizing image recognition, and the cornea form can be accurately fitted.
In an embodiment, the obtaining module 41 may be further configured to: the method comprises the steps of respectively obtaining a first eye image and a second eye image by using a binocular camera, or obtaining the eye images by using two cameras at different shooting angles to obtain the first eye image and the second eye image, namely obtaining two staggered eye images.
In an embodiment, the identification module 42 may be further configured to: and respectively inputting the first eye image and the second eye image into the trained recognition model to obtain a first eye cornea image and a second eye cornea image.
In an embodiment, the curvature calculation module 45 may be further configured to: and calculating the curvature in the preset direction according to the distance of the plurality of image points along the preset direction and the straight-line distance of the plurality of image points.
In an embodiment, fitting module 46 may be further configured to: and fitting according to the plurality of image points and the curvature in the preset direction to obtain a curved surface equation in the preset direction, and fitting according to the curved surface equation to obtain the surface morphology of the cornea.
Fig. 5 is a schematic structural diagram of a corneal topography measuring device according to another exemplary embodiment of the present application. As shown in fig. 5, the selecting module 44 may include: a center obtaining unit 441 configured to obtain a center point of the three-dimensional image; a distance calculation unit 442 for calculating a separation distance between the boundary point and the center point of the three-dimensional image; the direction determining unit 443 is configured to select a connection line between the boundary point and the central point along the corneal curvature of the eye, where the distance between the boundary point and the central point is the minimum and/or the maximum, as a preset direction; an image point determination unit 444 for selecting a plurality of image points at equal intervals in a predetermined direction.
In one embodiment, as shown in fig. 5, the corneal topography measuring device 40 may further include: a lens interval acquisition module 47, configured to acquire a first distance and a second distance between two photographing lenses of the binocular camera and the eyes of the patient; and a shooting distance acquiring module 48 for acquiring a third distance between the two shooting lenses of the binocular camera. Correspondingly, the building module 43 is configured to: and constructing a three-dimensional image containing the cornea of the eye according to the first cornea image, the second cornea image, the first distance, the second distance and the third distance.
Next, an electronic apparatus according to an embodiment of the present application is described with reference to fig. 6. The electronic device may be either or both of the first device and the second device, or a stand-alone device separate from them, which stand-alone device may communicate with the first device and the second device to receive the acquired input signals therefrom.
FIG. 6 illustrates a block diagram of an electronic device in accordance with an embodiment of the present application.
As shown in fig. 6, the electronic device 10 includes one or more processors 11 and memory 12.
The processor 11 may be a Central Processing Unit (CPU) or other form of processing unit having data processing capabilities and/or instruction execution capabilities, and may control other components in the electronic device 10 to perform desired functions.
Memory 12 may include one or more computer program products that may include various forms of computer-readable storage media, such as volatile memory and/or non-volatile memory. The volatile memory may include, for example, Random Access Memory (RAM), cache memory (cache), and/or the like. The non-volatile memory may include, for example, Read Only Memory (ROM), hard disk, flash memory, etc. One or more computer program instructions may be stored on the computer readable storage medium and executed by the processor 11 to implement the corneal topography measurement methods of the various embodiments of the present application described above and/or other desired functions. Various contents such as an input signal, a signal component, a noise component, etc. may also be stored in the computer-readable storage medium.
In one example, the electronic device 10 may further include: an input device 13 and an output device 14, which are interconnected by a bus system and/or other form of connection mechanism (not shown).
When the electronic device is a stand-alone device, the input means 13 may be a communication network connector for receiving the acquired input signals from the first device and the second device.
The input device 13 may also include, for example, a keyboard, a mouse, and the like.
The output device 14 may output various information including the determined distance information, direction information, and the like to the outside. The output devices 14 may include, for example, a display, speakers, a printer, and a communication network and its connected remote output devices, among others.
Of course, for simplicity, only some of the components of the electronic device 10 relevant to the present application are shown in fig. 6, and components such as buses, input/output interfaces, and the like are omitted. In addition, the electronic device 10 may include any other suitable components depending on the particular application.
In addition to the methods and apparatus described above, embodiments of the present application may also be a computer program product comprising computer program instructions that, when executed by a processor, cause the processor to perform the steps in the methods of measuring corneal surface topography according to the various embodiments of the present application described in the "exemplary methods" section above of this specification.
The computer program product may be written with program code for performing the operations of embodiments of the present application in any combination of one or more programming languages, including an object oriented programming language such as Java, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computing device, partly on the user's device, as a stand-alone software package, partly on the user's computing device and partly on a remote computing device, or entirely on the remote computing device or server.
Furthermore, embodiments of the present application may also be a computer-readable storage medium having stored thereon computer program instructions that, when executed by a processor, cause the processor to perform the steps in the method of measuring corneal surface topography according to various embodiments of the present application described in the "exemplary methods" section above in this specification.
The computer-readable storage medium may take any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may include, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples (a non-exhaustive list) of the readable storage medium include: an electrical connection having one or more wires, a portable disk, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
The foregoing describes the general principles of the present application in conjunction with specific embodiments, however, it is noted that the advantages, effects, etc. mentioned in the present application are merely examples and are not limiting, and they should not be considered essential to the various embodiments of the present application. Furthermore, the foregoing disclosure of specific details is for the purpose of illustration and description and is not intended to be limiting, since the foregoing disclosure is not intended to be exhaustive or to limit the disclosure to the precise details disclosed.
The block diagrams of devices, apparatuses, systems referred to in this application are only given as illustrative examples and are not intended to require or imply that the connections, arrangements, configurations, etc. must be made in the manner shown in the block diagrams. These devices, apparatuses, devices, systems may be connected, arranged, configured in any manner, as will be appreciated by those skilled in the art. Words such as "including," "comprising," "having," and the like are open-ended words that mean "including, but not limited to," and are used interchangeably therewith. The words "or" and "as used herein mean, and are used interchangeably with, the word" and/or, "unless the context clearly dictates otherwise. The word "such as" is used herein to mean, and is used interchangeably with, the phrase "such as but not limited to".
It should also be noted that in the devices, apparatuses, and methods of the present application, the components or steps may be decomposed and/or recombined. These decompositions and/or recombinations are to be considered as equivalents of the present application.
The previous description of the disclosed aspects is provided to enable any person skilled in the art to make or use the present application. Various modifications to these aspects will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other aspects without departing from the scope of the application. Thus, the present application is not intended to be limited to the aspects shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
The foregoing description has been presented for purposes of illustration and description. Furthermore, the description is not intended to limit embodiments of the application to the form disclosed herein. While a number of example aspects and embodiments have been discussed above, those of skill in the art will recognize certain variations, modifications, alterations, additions and sub-combinations thereof.
Claims (10)
1. A method for measuring the topography of a corneal surface, comprising:
respectively acquiring a first eye image and a second eye image with different shooting angles;
identifying a first eye cornea image and a second eye cornea image of the first eye image and the second eye image, respectively;
obtaining a three-dimensional image of the cornea according to the first cornea image and the second cornea image;
selecting a plurality of image points in the three-dimensional image along a preset direction;
calculating the curvature of the preset direction according to the plurality of image points; and
and fitting to obtain the surface morphology of the cornea according to the plurality of image points and the curvature in the preset direction.
2. The method for measuring the topography of a corneal surface of claim 1, wherein said selecting a plurality of image points in said three-dimensional image along a predetermined direction comprises:
acquiring a central point of the three-dimensional image;
calculating the spacing distance between the boundary point of the three-dimensional image and the central point;
selecting a connecting line of the boundary point with the minimum and/or maximum spacing distance and the central point along the curved surface of the cornea as the preset direction; and
and equally spacing and selecting the plurality of image points in the preset direction.
3. The method for measuring corneal topography according to claim 1, wherein said calculating curvature in said predetermined direction from said plurality of image points comprises:
and calculating the curvature in the preset direction according to the distance of the plurality of image points along the preset direction and the straight-line distance of the plurality of image points.
4. The method for measuring the corneal surface morphology according to claim 1, wherein the fitting to obtain the corneal surface morphology according to the plurality of image points and the curvature in the preset direction comprises:
fitting to obtain a curved surface equation of the preset direction according to the plurality of image points and the curvature of the preset direction; and
and fitting according to the curved surface equation to obtain the surface morphology of the cornea.
5. The method for measuring the corneal topography according to claim 1, wherein the acquiring the first eye image and the second eye image having different imaging angles, respectively, comprises:
and respectively acquiring the first eye image and the second eye image by using a binocular camera.
6. The method for measuring corneal topography according to claim 1, wherein said identifying a first eye cornea image and a second eye cornea image of said first eye image and said second eye image, respectively, comprises:
and respectively inputting the first eye image and the second eye image into a first neural network model to obtain the first eye cornea image and the second eye cornea image.
7. The method for measuring the topography of a cornea of claim 1, wherein prior to said obtaining a three-dimensional image of said cornea from said first image of said cornea and said second image of said cornea, further comprising:
acquiring a first distance and a second distance between two shooting lenses of the binocular camera and eyes of a patient; and
acquiring a third distance between two shooting lenses of the binocular camera;
the obtaining of the three-dimensional image of the cornea of the eye according to the first image of the cornea and the second image of the cornea of the eye comprises:
and constructing a three-dimensional image of the cornea of the eye according to the first cornea image, the second cornea image, the first distance, the second distance and the third distance.
8. A corneal topography measurement device, comprising:
the acquisition module is used for respectively acquiring a first eye image and a second eye image with different shooting angles;
an identification module, configured to identify a first eye cornea image and a second eye cornea image of the first eye image and the second eye image, respectively;
the construction module is used for obtaining a three-dimensional image of the cornea according to the first cornea image and the second cornea image;
the selecting module is used for selecting a plurality of image points in the three-dimensional image along a preset direction;
a curvature calculating module, configured to calculate a curvature of the preset direction according to the plurality of image points; and
and the fitting module is used for fitting to obtain the surface morphology of the cornea according to the plurality of image points and the curvature in the preset direction.
9. A computer-readable storage medium storing a computer program for executing the method for measuring the topography of a cornea according to any one of claims 1 to 7.
10. An electronic device, the electronic device comprising:
a processor; and
a memory for storing the processor-executable instructions;
the processor is configured to perform the method of measuring corneal topography of any of claims 1-7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111131161.0A CN113662506B (en) | 2021-09-26 | 2021-09-26 | Cornea surface morphology measurement method and device, medium and electronic equipment |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111131161.0A CN113662506B (en) | 2021-09-26 | 2021-09-26 | Cornea surface morphology measurement method and device, medium and electronic equipment |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN113662506A true CN113662506A (en) | 2021-11-19 |
| CN113662506B CN113662506B (en) | 2023-08-04 |
Family
ID=78550237
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202111131161.0A Active CN113662506B (en) | 2021-09-26 | 2021-09-26 | Cornea surface morphology measurement method and device, medium and electronic equipment |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113662506B (en) |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115120178A (en) * | 2022-07-03 | 2022-09-30 | 灵动翘睫(深圳)科技有限公司 | Method for acquiring curvature of front surface of eyeball |
| CN115953389A (en) * | 2023-02-24 | 2023-04-11 | 广州视景医疗软件有限公司 | Strabismus discrimination method and device based on face key point detection |
| CN116831516A (en) * | 2023-07-20 | 2023-10-03 | 广州视景医疗软件有限公司 | Cornea curvature generating method and device |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2012055333A (en) * | 2010-09-03 | 2012-03-22 | Nidek Co Ltd | Anterior ocular segment measuring instrument |
| CN104837399A (en) * | 2012-08-15 | 2015-08-12 | 光视有限公司 | Corneal stromal mapping |
| CN107361737A (en) * | 2011-03-25 | 2017-11-21 | 雷萨公司 | The system and method that broken measurement inclination of lens is emulsified with laser-ultrasound |
| CN108652583A (en) * | 2018-02-11 | 2018-10-16 | 温州眼视光发展有限公司 | Detect corneal thickness and the device and method of curvature |
| JP2019000135A (en) * | 2017-06-09 | 2019-01-10 | 株式会社豊田中央研究所 | Visual line measurement device |
| CN209122188U (en) * | 2018-04-19 | 2019-07-19 | 长春理工大学 | A kind of device digitizing keratometry |
| CN110974150A (en) * | 2019-12-02 | 2020-04-10 | 四川大学 | Method for measuring human eye cornea topography |
-
2021
- 2021-09-26 CN CN202111131161.0A patent/CN113662506B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2012055333A (en) * | 2010-09-03 | 2012-03-22 | Nidek Co Ltd | Anterior ocular segment measuring instrument |
| CN107361737A (en) * | 2011-03-25 | 2017-11-21 | 雷萨公司 | The system and method that broken measurement inclination of lens is emulsified with laser-ultrasound |
| CN104837399A (en) * | 2012-08-15 | 2015-08-12 | 光视有限公司 | Corneal stromal mapping |
| JP2019000135A (en) * | 2017-06-09 | 2019-01-10 | 株式会社豊田中央研究所 | Visual line measurement device |
| CN108652583A (en) * | 2018-02-11 | 2018-10-16 | 温州眼视光发展有限公司 | Detect corneal thickness and the device and method of curvature |
| CN209122188U (en) * | 2018-04-19 | 2019-07-19 | 长春理工大学 | A kind of device digitizing keratometry |
| CN110974150A (en) * | 2019-12-02 | 2020-04-10 | 四川大学 | Method for measuring human eye cornea topography |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115120178A (en) * | 2022-07-03 | 2022-09-30 | 灵动翘睫(深圳)科技有限公司 | Method for acquiring curvature of front surface of eyeball |
| CN115953389A (en) * | 2023-02-24 | 2023-04-11 | 广州视景医疗软件有限公司 | Strabismus discrimination method and device based on face key point detection |
| CN115953389B (en) * | 2023-02-24 | 2023-11-24 | 广州视景医疗软件有限公司 | Strabismus judging method and device based on face key point detection |
| CN116831516A (en) * | 2023-07-20 | 2023-10-03 | 广州视景医疗软件有限公司 | Cornea curvature generating method and device |
| CN116831516B (en) * | 2023-07-20 | 2024-02-06 | 广州视景医疗软件有限公司 | Cornea curvature generating method and device |
Also Published As
| Publication number | Publication date |
|---|---|
| CN113662506B (en) | 2023-08-04 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN113662506B (en) | Cornea surface morphology measurement method and device, medium and electronic equipment | |
| US9628697B2 (en) | Method and device for measuring an interpupillary distance | |
| JP2019519859A (en) | System and method for performing gaze tracking | |
| US20140152956A1 (en) | System for the measurement of the interpupillary distance using a device equipped with a display and a camera | |
| WO2019010959A1 (en) | Method and device for determining sight line, and computer readable storage medium | |
| US20150029322A1 (en) | Method and computations for calculating an optical axis vector of an imaged eye | |
| US12033316B2 (en) | Systems and methods of measuring the body based on image analysis | |
| CN109285602B (en) | Master module, system and method for self-checking a user's eyes | |
| KR101978548B1 (en) | Server and method for diagnosing dizziness using eye movement measurement, and storage medium storin the same | |
| JP2024529785A (en) | Eye gaze tracking method and device | |
| US20220207919A1 (en) | Methods, devices and systems for determining eye parameters | |
| CN115840502B (en) | Three-dimensional sight tracking method, device, equipment and storage medium | |
| JP2019215688A (en) | Visual line measuring device, visual line measurement method and visual line measurement program for performing automatic calibration | |
| CN112099622B (en) | Sight tracking method and device | |
| AU2019273058B2 (en) | Measuring a posterior corneal surface of an eye | |
| EP4333686A1 (en) | Obtaining high-resolution oculometric parameters | |
| CN113723293A (en) | Sight direction determination method and device, electronic equipment and storage medium | |
| CN113616153A (en) | Method, device, medium and electronic equipment for measuring thickness of cornea | |
| CN115997159B (en) | Method for determining the position of the center of rotation of an eye using a mobile device | |
| JP2015123262A (en) | Sight line measurement method using corneal surface reflection image, and device for the same | |
| CN113643253A (en) | Diameter measuring method, device, medium and equipment based on cornea image | |
| CN116309391B (en) | Image processing method and device, electronic equipment and storage medium | |
| CN112528714A (en) | Single light source-based gaze point estimation method, system, processor and equipment | |
| CN113827179B (en) | Eyelid pressure detection method and device, medium and electronic equipment | |
| US20230036611A1 (en) | Gaze estimation apparatus, gaze estimation method, model generation apparatus, and model generation method |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |