Fundus image processing method, device and electronic equipment

Abstract

The present invention provides a fundus image processing method, device and electronic device, the method comprising: obtaining a fundus OCT image with the center of the OCT scan aligned with the corneal vertex of the eye to be tested; extracting the layer line corresponding to each layer of the fundus from the fundus OCT image, and performing curvature correction on each layer line to obtain each corrected layer line; for each corrected layer line, calculating the target topography corresponding to the corrected layer line; wherein the target topography includes at least one of the following: an axial curvature topography map, a tangential curvature topography map, a height map and a pupil center distance map. This method can extract layer lines from the fundus OCT image, and after performing curvature correction on each extracted layer line, obtain at least one of the corresponding axial curvature topography map, tangential curvature topography map, height map and pupil center distance map, thereby enriching the information of the fundus and effectively meeting the current needs of myopia prevention, control and correction.

Description

Technical Field

[0001] The present invention relates to the field of image processing technology, and in particular to a fundus image processing method, device and electronic equipment. Background Art

[0002] Myopia is caused by the excessive length of the eyeball, which causes light to focus in front of the retina instead of on the retina, resulting in blurred retinal imaging. Early ophthalmic biometry equipment used ultrasound technology. In recent years, OCT (Optical Coherence Tomography) technology has gradually become the mainstream technology for ophthalmic biometry equipment due to its high resolution, fast imaging speed, no radiation damage, compact structure, and easy operation. The current ophthalmic biometry based on a swept source uses a telecentric or near-telecentric optical lens, with the scanning line parallel to the optical axis and the focus located in the anterior segment of the eye. This arrangement is conducive to traditional axial length measurement and anterior segment imaging, but the information on the fundus is very limited and cannot meet the current needs of myopia prevention, control, and correction. Summary of the invention

[0003] The purpose of the present invention is to provide a fundus image processing method, device and electronic equipment to enrich the fundus information and meet the current needs of myopia prevention, control and correction.

[0004] The present invention provides a fundus image processing method, which comprises: obtaining a fundus OCT image with an OCT scanning center aligned with the corneal vertex of an eye to be tested; aligning the OCT optical focus with the retina of the eye to be tested; including the retinal fovea of ​​the eye to be tested in the fundus OCT image; extracting a layer line corresponding to each layer of the fundus from the fundus OCT image, and performing curvature correction on each layer line to obtain each corrected layer line; for each corrected layer line, calculating a target topography corresponding to the corrected layer line; wherein the target topography comprises at least one of the following: an axial curvature topography map, a tangential curvature topography map, a height map, and a pupil center distance map.

[0005] Furthermore, if the target topographic map includes an axial curvature topographic map, the axial curvature topographic map is determined in the following manner: for each corrected layering line, each pixel point in the corrected layering line is obtained; for each pixel point, the meridian plane where the pixel point and the pre-acquired eye axis are located is determined; on the meridian plane, the intersection point of the normal line of the pixel point and the eye axis is determined; the first distance between the pixel point and the intersection point is calculated; and according to the first distance corresponding to each pixel point, the axial curvature topographic map corresponding to the corrected layering line is determined.

[0006] Furthermore, if the target topographic map includes a tangential curvature topographic map, the tangential curvature topographic map is determined in the following manner: for each corrected layer line, each pixel point in the corrected layer line is obtained; for each pixel point, the meridian plane where the pixel point and the pre-acquired eye axis are located is determined; on the meridian plane, the radius of curvature corresponding to the pixel point is calculated; based on the radius of curvature corresponding to each pixel point, the tangential curvature topographic map corresponding to the corrected layer line is determined.

[0007] Furthermore, if the target topographic map includes a height map, the height map is determined in the following manner: for each corrected layer line, each pixel point in the corrected layer line is obtained; spherical fitting is performed based on each pixel point to obtain a fitted sphere; the second distance between each pixel point and the center of the fitted sphere is calculated respectively; the second distance corresponding to each pixel point is calculated, and the difference between the radius of the fitting sphere corresponding to the fitting sphere is calculated to determine the height map corresponding to the corrected layer line.

[0008] Furthermore, if the target topographic map includes a pupil center distance map, the pupil center distance map is determined in the following manner: for each corrected stratification line, each pixel point in the corrected stratification line is obtained; the third distance between each pixel point and a preset polar coordinate origin is calculated; wherein the polar coordinate origin is located on the anterior surface of the cornea, the posterior surface of the cornea, the anterior surface of the lens or the posterior surface of the lens; and according to the third distance corresponding to each pixel point, the pupil center distance map corresponding to the corrected stratification line is determined.

[0009] Furthermore, the stratification lines corresponding to each layer of the fundus include: the stratification line corresponding to the internal limiting membrane layer, the stratification line between the nerve fiber layer and the ganglion cell layer, the stratification line between the inner plexiform layer and the inner nuclear layer, the stratification line between the inner nuclear layer and the outer plexiform layer, the stratification line corresponding to the pigment epithelium layer, the stratification line corresponding to Bruch's membrane, and the stratification line corresponding to the choroid layer.

[0010] Furthermore, the step of obtaining a fundus OCT image with the OCT scanning center aligned with the corneal vertex of the eye to be tested includes: scanning the whole eye according to a preset scanning method to obtain a whole-eye OCT image with the OCT scanning center aligned with the corneal vertex of the eye to be tested; wherein the preset scanning methods include: a star scanning method under a posterior segment scanning mode; extracting a fundus OCT image from the whole-eye OCT image.

[0011] Furthermore, the step of scanning the whole eye according to a preset scanning method and obtaining a whole-eye OCT image with the OCT scanning center aligned with the corneal vertex of the eye to be tested includes: scanning the whole eye according to a preset scanning method; during the scanning process, detecting the inclination of the lens; if the inclination meets a preset inclination angle threshold, obtaining a whole-eye OCT image with the OCT scanning center aligned with the corneal vertex of the eye to be tested.

[0012] The present invention provides a fundus image processing device, which includes: a first acquisition module, used to acquire a fundus OCT image with an OCT scanning center aligned with the corneal vertex of an eye to be tested; the OCT optical focus is aligned with the retina of the eye to be tested; the fundus OCT image includes the retinal fovea of ​​the eye to be tested; a second acquisition module, used to extract a layer line corresponding to each layer of the fundus from the fundus OCT image, and perform curvature correction on each layer line to obtain each corrected layer line; a calculation module, used to calculate a target topography corresponding to each corrected layer line; wherein the target topography includes at least one of the following: an axial curvature topography map, a tangential curvature topography map, a height map, and a pupil center distance map.

[0013] An electronic device provided by the present invention includes a processor and a memory, wherein the memory stores machine executable instructions that can be executed by the processor, and the processor executes the machine executable instructions to implement any of the above fundus image processing methods.

[0014] The fundus image processing method, device and electronic device provided by the present invention obtain a fundus OCT image with the OCT scanning center aligned with the corneal vertex of the eye to be tested; the OCT optical focus is aligned with the retina of the eye to be tested; the fundus OCT image includes the retinal fovea of ​​the eye to be tested; the layered lines corresponding to each layer of the fundus are extracted from the fundus OCT image, and each layered line is subjected to curvature correction to obtain each corrected layered line; for each corrected layered line, the target topography corresponding to the corrected layered line is calculated; wherein the target topography includes at least one of the following: axial curvature topography, tangential curvature topography, height map and pupil center distance map. This method can extract layered lines from the fundus OCT image, and after curvature correction for each extracted layered line, obtain at least one of the corresponding axial curvature topography, tangential curvature topography, height map and pupil center distance map, enriching the information of the fundus and effectively meeting the current needs of myopia prevention, control and correction. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0016] Figure 1 A flowchart of a fundus image processing method provided by an embodiment of the present invention;

[0017] FIG2 (a) is a schematic diagram of a Bscan for calculating an axial curvature topography before correction provided by an embodiment of the present invention;

[0018] FIG2( b ) is a schematic diagram of a corrected Bscan for calculating an axial curvature topography provided by an embodiment of the present invention;

[0019] FIG2 (c) is a schematic diagram of an axial curvature topography provided by an embodiment of the present invention;

[0020] FIG3 (a) is a schematic diagram of a Bscan for calculating a tangential curvature topographic map before correction provided by an embodiment of the present invention;

[0021] FIG3( b ) is a schematic diagram of a corrected Bscan for calculating a tangential curvature topographic map provided by an embodiment of the present invention;

[0022] FIG3 (c) is a schematic diagram of a tangential curvature topographic map provided by an embodiment of the present invention;

[0023] FIG4 (a) is a schematic diagram of a Bscan for calculating a height map before correction provided by an embodiment of the present invention;

[0024] FIG4( b ) is a schematic diagram of a corrected Bscan for calculating a height map provided by an embodiment of the present invention;

[0025] FIG4( c ) is a schematic diagram of a height map provided by an embodiment of the present invention;

[0026] FIG5( a ) is a schematic diagram of a Bscan for calculating a pupil center distance map before correction provided by an embodiment of the present invention;

[0027] FIG5( b ) is a schematic diagram of a corrected Bscan for calculating a pupil center distance map provided by an embodiment of the present invention;

[0028] FIG5( c ) is a schematic diagram of a pupil center distance map provided by an embodiment of the present invention;

[0029] Figure 6 A schematic diagram of an optical path of an OCT provided in an embodiment of the present invention;

[0030] Figure 7 A schematic diagram of the structure of a fundus image processing device provided by an embodiment of the present invention;

[0031] Figure 8 A schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0032] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0033] At present, myopia screening for adolescents is mainly based on traditional vision tests, including subjective eye chart examinations and objective tests with automatic ophthalmometers. The biggest problem with traditional examination methods is that they are easily affected by the lens accommodation state of the subject, and the examination results are unstable and cannot distinguish between pseudomyopia. If the influence of lens accommodation is to be eliminated, mydriatic optometry must be performed. However, since mydriatic optometry will cause the subject to have blurred vision for several days, and there is a risk of blocking the chamber angle, leading to increased intraocular pressure and then causing glaucoma, mydriatic optometry cannot be used as a routine screening method for adolescent myopia.

[0034] Based on the optical biometer, the distance from the corneal vertex to the fovea of ​​the retina can be measured to obtain the axial length value with micron-level accuracy. It is a non-contact, non-destructive objective inspection method. This method is not affected by the state of lens adjustment and is an ideal method for myopia screening. In recent years, biometry has been increasingly used in myopia screening for adolescents.

[0035] The physiological mechanism of myopia is not fully understood at present, but a series of studies on the pathogenesis of myopia in recent years have proved that the occurrence and progression of myopia are related to the thickness of the choroid of the fundus. The thinning of the choroid causes a decrease in choroidal hemorrhage, which in turn leads to thinning of the sclera, which is likely to be an important physiological mechanism leading to myopia. The treatment method of irradiating the fundus with red light to increase the thickness of the choroid has also been gradually promoted. If the choroidal thickness can be obtained at the same time as the biological measurement, it will play an important guiding role in the prediction and treatment of the development of myopia in the subject.

[0036] Traditionally, the treatment for myopia is mainly to wear frame glasses, but teenagers are often prone to worsening myopia after wearing myopia frame glasses. Studies have found that this phenomenon is mainly because after wearing myopia frame glasses, the image at the central vision is projected on the retina, but its periphery is projected behind the retina. This phenomenon is called peripheral hyperopic defocus of the retina. This defocus state causes the retina to stretch backwards for self-adjustment, resulting in further growth of the axial length, which in turn causes myopia to deepen. Studies have shown that by pulling the focus of the retina's periphery back to the front of the retina, forming peripheral myopic defocus of the retina, the growth of the axial length can be controlled and the deepening of myopia can be delayed. The main methods include orthokeratology lenses, specially designed peripheral defocus soft lenses and frame glasses. However, since the curvature of each person's fundus is not the same, the same treatment plan will produce different peripheral defocus amounts in different people, and the amount of defocus will directly affect the effect of myopia control. The commonly used ophthalmic B-ultrasound is greatly affected by the operator's technique and cannot accurately measure the fundus curvature, and contact with the eyeball is required during the examination. Although magnetic resonance imaging (MRI) can accurately measure the fundus curvature, it is extremely expensive and cannot be promoted.

[0037] In recent years, OCT technology has gradually become the mainstream technology of ophthalmic biometric equipment, but there is still a problem that the information of the fundus is very limited, which cannot meet the current needs of myopia prevention and correction. In addition, since the fundus is far away from the focus of the detection light, in the application of traditional cataract preoperative measurement, there is still a certain measurement failure rate for eyes with severe cataracts. Based on this, the embodiments of the present invention provide a fundus image processing method, device and electronic device, which can be applied to applications that need to determine the fundus topography.

[0038] To facilitate understanding of this embodiment, a fundus image processing method disclosed in an embodiment of the present invention is first introduced. Figure 1 As shown, the method comprises the following steps:

[0039] Step S102, acquiring a fundus OCT image with the OCT scanning center aligned with the corneal vertex of the eye to be tested; the OCT optical focus is aligned with the retina of the eye to be tested; the fundus OCT image includes the retinal fovea of ​​the eye to be tested;

[0040] The above-mentioned corneal vertex is generally considered to be the point of maximum curvature or highest point on the anterior surface of the cornea; the above-mentioned fundus OCT image is an image acquired when the fundus is examined using OCT technology; the above-mentioned fovea is the area with the sharpest vision and highest resolution in the retina, located in the center of the macular area, and is the main area for humans to observe the details and shapes of objects; in actual implementation, when it is necessary to obtain relevant topographic maps, it is necessary to first obtain the fundus OCT image acquired when the OCT scanning center is aligned with the corneal vertex of the eye to be tested. When acquiring the fundus OCT image, the OCT optical focus is aligned with the retina of the eye to be tested, and the acquired fundus OCT image includes the fovea of ​​the eye to be tested.

[0041] Step S104, extracting the layer line corresponding to each layer of the fundus from the fundus OCT image, and performing curvature correction on each layer line to obtain each corrected layer line;

[0042] Curvature describes the degree of bending of a curve or surface at a certain point. In actual implementation, the above-mentioned fundus OCT image usually includes multiple layers, and the layer line corresponding to each layer can be extracted from the fundus OCT image. Each layer line can be geometrically corrected to correct the curvature of each layer line to obtain each corrected layer line. The curvature of each layer line after curvature correction is more consistent with the physical structure of the actual eye. The method of curvature correction can refer to the relevant technology, which will not be repeated here.

[0043] Step S106, for each corrected stratification line, calculate and obtain a target topographic map corresponding to the corrected stratification line; wherein the target topographic map includes at least one of the following: an axial curvature topographic map, a tangential curvature topographic map, a height map, and a pupil center distance map.

[0044] The above-mentioned axial curvature topography map can represent the distance between each pixel point on the layering line and the intersection point, and the intersection point refers to the intersection point of each pixel point with the eye axis along the normal direction; the above-mentioned tangential curvature topography map can represent the curvature radius of each pixel point on the layering line; the above-mentioned height map can represent the distance between each pixel point on the layering line and the fitting sphere, and the fitting sphere is obtained based on the fitting of each pixel point; the above-mentioned pupil center distance map can be understood as the distance between each pixel point on the layering line and the preset polar coordinate origin; in actual implementation, after obtaining each corrected layering line, the above-mentioned axial curvature topography map, tangential curvature topography map, height map and pupil center distance map can be calculated for each layering line.

[0045] The above-mentioned fundus image processing method obtains a fundus OCT image with the OCT scanning center aligned with the corneal vertex of the eye to be tested; the OCT optical focus is aligned with the retina of the eye to be tested; the fundus OCT image includes the retinal fovea of ​​the eye to be tested; the layered lines corresponding to each layer of the fundus are extracted from the fundus OCT image, and each layered line is subjected to curvature correction to obtain each corrected layered line; for each corrected layered line, the target topography corresponding to the corrected layered line is calculated; wherein the target topography includes at least one of the following: axial curvature topography, tangential curvature topography, height map, and pupil center distance map. This method can extract layered lines from the fundus OCT image, and after performing curvature correction on each extracted layered line, obtain at least one of the corresponding axial curvature topography, tangential curvature topography, height map, and pupil center distance map, enriching the information of the fundus and effectively meeting the current needs of myopia prevention, control, and correction.

[0046] The embodiment of the present invention further provides another fundus image processing method, which is implemented on the basis of the method in the above embodiment, and comprises the following steps:

[0047] Step 1, scanning the whole eye according to a preset scanning mode, obtaining a whole eye OCT image with the OCT scanning center aligned with the corneal vertex of the eye to be tested; wherein the preset scanning mode includes: a star scanning mode in a posterior segment scanning mode;

[0048] The posterior segment of the eye includes structures such as the vitreous body, retina, and choroid. These structures are located at the back of the eyeball and are responsible for the photosensitivity of the eye. The bottom of the posterior segment of the eye is called the fundus. The above-mentioned star scanning method is a process of collecting data in a star-shaped or radial pattern. In this embodiment, in order to obtain richer fundus information, the posterior segment scanning mode can be used to scan the eye to be tested. In order to obtain a high-resolution image, a star scanning method can be used to perform a full-eye scan of the eye to be tested to obtain a full-eye OCT image from the cornea to the fovea of ​​the retina. When using the star scanning method, the appropriate scanning length range, scanning repetition number and number of lines can be selected according to actual needs. For example, the scanning length range can be 3mm~20mm, the scanning repetition number can be 1 time~100 times, the number of lines can be 6 lines~100 lines, etc.; of course, other suitable scanning methods can also be selected according to actual needs, such as three-dimensional scanning, etc.

[0049] The step 1 can be implemented by following steps 10 to 12:

[0050] Step 10, scanning the entire eye according to a preset scanning method;

[0051] Step 11, during the scanning process, detecting the tilt of the lens;

[0052] Step 12: If the inclination satisfies the preset inclination angle threshold, a full-eye OCT image is acquired with the OCT scanning center aligned with the corneal vertex of the eye to be tested.

[0053] The above-mentioned tilt angle threshold can be set according to actual needs. For example, the preset tilt angle threshold is -1°~+1°. In actual implementation, in the process of acquiring the whole-eye OCT image, the tilt of the lens is usually detected. Specifically, a picture containing the lens can be obtained by scanning, and the front and back surfaces of the lens can be identified through deep learning. Based on the identified front and back surfaces, three-dimensional reconstruction is performed to obtain the three-dimensional state of the lens. The tilt of the lens can be analyzed and evaluated based on the three-dimensional state. If the lens is tilted, the signals of its reflected light at different depths will be deformed. In order to ensure an accurate target topographic map, it is usually required that the tilt of the lens should not exceed + / -1°. When the detected tilt of the lens meets the tilt angle threshold, the above-mentioned whole-eye OCT image can be acquired.

[0054] Step 2: extracting a fundus OCT image from the whole-eye OCT image; aligning the OCT optical focus with the retina of the eye to be tested; and the fundus OCT image includes the fovea of ​​the retina of the eye to be tested;

[0055] In actual implementation, the radius range or line length of the fundus OCT image is usually not less than 3 mm, and the fundus OCT image can be extracted from the whole-eye OCT image obtained above. The whole-eye OCT image usually contains the cornea, lens and retina. The extracted fundus OCT image may not include the cornea or lens. The fundus OCT image usually needs to include the fovea of ​​the retina of the eye to be tested.

[0056] Step 3, extracting the layer line corresponding to each layer of the fundus from the fundus OCT image, and performing curvature correction on each layer line to obtain each corrected layer line;

[0057] The stratification lines corresponding to each layer of the fundus include: the stratification line corresponding to the internal limiting membrane layer, the stratification line between the nerve fiber layer and the ganglion cell layer, the stratification line between the inner plexiform layer and the inner nuclear layer, the stratification line between the inner nuclear layer and the outer plexiform layer, the stratification line corresponding to the pigment epithelium layer, the stratification line corresponding to Bruch's membrane, and the stratification line corresponding to the choroid layer.

[0058] The above-mentioned internal limiting membrane is a thin film located between the inner surface of the retina and the surface of the vitreous body, which can separate the retina from the gel-like vitreous humor that fills the inside of the eyeball; the above-mentioned nerve fiber layer is mainly composed of the axons of ganglion cells, which are used to transmit commands from the brain; the above-mentioned ganglion cell layer is composed of the cell bodies of ganglion cells, which are used to transmit information and form visual nerves on the retina; the above-mentioned inner plexiform layer is mainly composed of the axons of bipolar cells and the dendrites of ganglion cells; the above-mentioned inner nuclear layer is composed of the cell bodies of bipolar cells, horizontal cells, amacrine cells and Müller cells; the above-mentioned outer plexiform layer is formed by the axons of photoreceptor rods and cones and the dendrites of bipolar cells, which is thickest in the macula and gradually thins in the periphery; the above-mentioned pigment epithelium is composed of a single layer of pigment epithelial cells, which are used to maintain the photoreceptor microenvironment; the above-mentioned Bruch's membrane refers to a thin membrane-like structure located between the choroidal capillary layer and the retinal visual pigment epithelium; the above-mentioned choroid layer is located between the retina and the sclera, and is a soft, smooth, elastic and vascular brown film. In actual implementation, the stratification lines corresponding to each stratification of the fundus can be extracted from the above-mentioned fundus OCT image. It can be understood that the stratification lines include but are not limited to the stratification lines disclosed above. The stratification can be performed using a stratification method based on a traditional algorithm or a stratification method based on deep learning. Each extracted stratification line is curvature corrected to form a fan-shaped image from the front surface of the lens to the fundus, and each corrected stratification line can be obtained.

[0059] Step 4: For each corrected stratification line, calculate a target topographic map corresponding to the corrected stratification line; wherein the target topographic map includes at least one of the following: an axial curvature topographic map, a tangential curvature topographic map, a height map, and a pupil center distance map.

[0060] The radius range of the target topography is usually related to the OCT device, for example, the radius range may be 3 mm to 18 mm, etc. If the target topography includes an axial curvature topography, the axial curvature topography is determined by the following steps 40 to 44:

[0061] Step 40, for each corrected layered line, obtaining each pixel point in the corrected layered line;

[0062] Step 41, for each pixel point, determining the meridian plane where the pixel point and the pre-acquired eye axis are located;

[0063] Step 42, determining the intersection point of the normal line of the pixel point and the eye axis on the meridian plane;

[0064] Step 43, calculating a first distance between the pixel point and the intersection point;

[0065] Step 44, determining the axial curvature topography corresponding to the corrected layering line according to the first distance corresponding to each pixel point.

[0066] The meridian plane in optics can be understood as the plane formed by the main light of the off-axis object point and the main axis of the optical system, which is called the meridian plane of the optical system imaging; in actual implementation, for each corrected layered line, at the three-dimensional level, the normal of each pixel point of the BScan layered line does not necessarily have an intersection with the eye axis. In this embodiment, all quantities are restricted to the meridian plane, and the meridian plane where each pixel point and the eye axis are located in the corrected layered line can be determined, and the intersection of the normal of each pixel point and the eye axis is calculated on the meridian plane, and then the first distance between each pixel point and the intersection is calculated respectively, and the axial curvature topography corresponding to the corrected layered line can be obtained according to the first distance.

[0067] As shown in FIG2 (a), a schematic diagram of a Bscan for calculating an axial curvature topography before correction is shown; as shown in FIG2 (b), a schematic diagram of a Bscan for calculating an axial curvature topography after correction is shown; and as shown in FIG2 (c), an axial curvature topography is shown. The Bscan diagram in FIG2 (a) is a layered line before correction. With reference to the correction method in the related art, the Bscan diagram in FIG2 (b) can be obtained. The Bscan diagram in FIG2 (b) is a layered line after correction. In this embodiment, the axial curvature topography in FIG2 (c) can be calculated based on the Bscan diagram in FIG2 (b) and the calculation method in the above embodiment. The numbers in the axial curvature topography are the first distances corresponding to each pixel point on the corresponding layered line. The corresponding axial curvature topography can be calculated for each layered line.

[0068] If the target topographic map includes a tangential curvature topographic map, the tangential curvature topographic map is determined by the following steps 45 to 48:

[0069] Step 45, for each corrected layer line, obtaining each pixel point in the corrected layer line;

[0070] Step 46, for each pixel point, determining the meridian plane where the pixel point and the pre-acquired eye axis are located;

[0071] Step 47, calculating the radius of curvature corresponding to the pixel point on the meridian plane;

[0072] Step 48, determining the tangential curvature topography corresponding to the corrected layering line according to the curvature radius corresponding to each pixel point.

[0073] The above-mentioned radius of curvature can be used to describe the rotation rate of the tangent direction angle of the pixel point to the arc length; in actual implementation, for each corrected stratification line, the curvature radius corresponding to each pixel point on the corrected stratification line can be calculated on the meridian plane, and according to each curvature radius, the tangential curvature topographic map corresponding to the corrected stratification line can be obtained.

[0074] As shown in FIG3 (a), a schematic diagram of a Bscan for calculating a tangential curvature topography before correction is shown; FIG3 (b) is a schematic diagram of a Bscan for calculating a tangential curvature topography after correction and FIG3 (c) is a tangential curvature topography. The Bscan in FIG3 (a) is a layered line before correction. Referring to the correction method in the related art, the Bscan in FIG3 (b) can be obtained. The Bscan in FIG3 (b) is a layered line after correction. This embodiment can calculate the tangential curvature topography in FIG3 (c) based on the Bscan in FIG3 (b) and the calculation method in the above embodiment. The numbers in the tangential curvature topography are the curvature radius corresponding to each pixel point on the corresponding layered line. The corresponding tangential curvature topography can be calculated for each layered line.

[0075] If the target terrain map includes a height map, the height map is determined by the following steps 49 to 52:

[0076] Step 49, for each corrected layer line, obtaining each pixel point in the corrected layer line;

[0077] Step 50, performing spherical fitting based on each pixel point to obtain a fitting spherical surface;

[0078] Step 51, respectively calculating the second distance between each pixel point and the center of the fitted sphere;

[0079] Step 52, calculating the difference between the second distance corresponding to each pixel point and the radius of the fitting sphere corresponding to the fitting spherical surface, and determining the height map corresponding to the corrected layering line.

[0080] In actual implementation, for each corrected layering line, a spherical fitting can be performed based on the corrected layering line. The method of spherical fitting can refer to relevant technologies and will not be repeated here. The fitted sphere can be understood as an optimal sphere that approximates each pixel point. The distance between each pixel point on the corrected layering line and the center of the fitting sphere is calculated. This distance is defined as the second distance. The difference between the second distance corresponding to each pixel point and the radius of the fitting sphere is calculated. Thus, the height map corresponding to the corrected layering line can be obtained.

[0081] As shown in FIG4(a), there is a schematic diagram of a Bscan for calculating a height map before correction; FIG4(b), there is a schematic diagram of a Bscan for calculating a height map after correction, and FIG4(c), there is a height map. The Bscan in FIG4(a) is a layered line before correction. With reference to the correction method in the related art, the Bscan in FIG4(b) can be obtained. The Bscan in FIG4(b) is a layered line after correction. In this embodiment, the height map in FIG4(c) can be calculated based on the Bscan in FIG4(b) and the calculation method in the above embodiment. The numbers in the height map are the difference between the second distance between each pixel point on the corresponding layered line and the center of the fitting sphere minus the radius of the fitting sphere. With the fitting sphere as a reference, the position of each pixel point may be higher or lower than the fitting sphere. The pixel points sampled during fitting are related to the number of lines of the star scan. For example, 18 lines means 18 points are sampled, and the point with the smallest error can be selected for fitting (for example, the average value, variance, etc. can be selected). The corresponding height map can be calculated for each layer line.

[0082] If the target topographic map includes a pupil center distance map, the pupil center distance map is determined by the following steps 54 to 56:

[0083] Step 54, for each corrected layer line, obtaining each pixel point in the corrected layer line;

[0084] Step 55, calculating a third distance between each pixel point and a preset polar coordinate origin; wherein the polar coordinate origin is located at the front surface of the cornea, the rear surface of the cornea, the front surface of the lens, or the rear surface of the lens;

[0085] Step 56, determining the pupil center distance map corresponding to the corrected stratification line according to the third distance corresponding to each pixel point.

[0086] The origin of the polar coordinate system is the polar coordinate origin, wherein the polar coordinate system refers to a coordinate system composed of a pole, a polar axis, and a polar diameter in a plane; in actual implementation, for each corrected stratification line, the third distance between each pixel point and the preset polar coordinate origin on the corrected stratification line can be calculated, and according to each third distance, a pupil center distance map corresponding to the corrected stratification line can be generated.

[0087] A schematic diagram of a Bscan for calculating a pupil center distance map before correction as shown in FIG5 (a); a schematic diagram of a Bscan for calculating a pupil center distance map after correction as shown in FIG5 (b) and a pupil center distance map as shown in FIG5 (c), the Bscan map in FIG5 (a) is a layered line before correction, and the Bscan map in FIG5 (b) can be obtained by referring to the correction method in the related art, and the Bscan map in FIG5 (b) is a layered line after correction. This embodiment can calculate the pupil center distance map of FIG5 (c) according to the Bscan map in FIG5 (b) and the calculation method in the above embodiment, and the numbers in the pupil center distance map are the third distances between each pixel point on the corresponding layered line and the preset polar coordinate origin. The corresponding pupil center distance map can be calculated for each layered line.

[0088] In the above Figures 2 (c), 3 (c), 4 (c), and 5 (c), the black area in each topographic map is the location of the optic disc, which needs to be removed and has no stratification significance.

[0089] For easier understanding, see Figure 6 The optical path diagram of an OCT is shown, which includes: a model eye, an eyepiece, an intermediate mirror position (a position definition), a dichroic mirror, a lens, and a galvanometer position. In the posterior segment scanning mode, by aligning the eye to be tested with the center of the OCT optical path, adjusting the working distance and the reference arm, a clear fundus OCT image can be obtained, and the human eye and the OCT scanning center are further fine-tuned to align until the fundus OCT image including the retinal fovea of ​​the eye to be tested is obtained, and the acquisition is completed; after stratification and curvature correction, the axial curvature topography, tangential curvature topography, height map, and pupil center distance map corresponding to each stratification line are calculated respectively.

[0090] Compared with B-ultrasound technology, the above fundus image processing method has the advantages of non-contact, high resolution, fast imaging speed, no radiation damage, compact structure, and easy operation. Compared with MRI technology, this method can be realized through hardware and software upgrades based on the existing OCT platform. It is easy to operate, low cost, high resolution, and easy to promote. It is helpful for the fitting of OK lenses and scleral lenses.

[0091] The embodiment of the present invention provides a fundus image processing device, such as Figure 7As shown, the device includes: a first acquisition module 70, which is used to acquire a fundus OCT image with the OCT scanning center aligned with the corneal vertex of the eye to be tested; the OCT optical focus is aligned with the retina of the eye to be tested; the fundus OCT image includes the retinal fovea of ​​the eye to be tested; a second acquisition module 71, which is used to extract the layer line corresponding to each layer of the fundus from the fundus OCT image, and perform curvature correction on each layer line to obtain each corrected layer line; a calculation module 72, which is used to calculate the target topography corresponding to each corrected layer line for each corrected layer line; wherein the target topography includes at least one of the following: an axial curvature topography map, a tangential curvature topography map, a height map, and a pupil center distance map.

[0092] The above-mentioned fundus image processing device can extract layered lines from the fundus OCT image, and after performing curvature correction on each extracted layered line, obtain at least one of the corresponding axial curvature topography map, tangential curvature topography map, height map and pupil center distance map, thereby enriching the fundus information and effectively meeting the current needs of myopia prevention, control and correction.

[0093] Furthermore, if the target topographic map includes an axial curvature topographic map, the device also includes: an axial curvature topographic map determination module; the axial curvature topographic map determination module is used to: for each corrected layer line, obtain each pixel point in the corrected layer line; for each pixel point, determine the meridian plane where the pixel point and the pre-acquired eye axis are located; on the meridian plane, determine the intersection of the normal of the pixel point and the eye axis; calculate the first distance between the pixel point and the intersection; and determine the axial curvature topographic map corresponding to the corrected layer line based on the first distance corresponding to each pixel point.

[0094] Furthermore, if the target topographic map includes a tangential curvature topographic map, the device also includes: a tangential curvature topographic map determination module; the tangential curvature topographic map determination module is used to: for each corrected layer line, obtain each pixel point in the corrected layer line; for each pixel point, determine the meridian plane where the pixel point and the pre-acquired eye axis are located; on the meridian plane, calculate the curvature radius corresponding to the pixel point; based on the curvature radius corresponding to each pixel point, determine the tangential curvature topographic map corresponding to the corrected layer line.

[0095] Furthermore, if the target topographic map includes a height map, the device also includes: a height map determination module; the height map determination module is used to: for each corrected layer line, obtain each pixel point in the corrected layer line; perform spherical fitting based on each pixel point to obtain a fitted sphere; respectively calculate the second distance between each pixel point and the center of the fitted sphere; calculate the difference between the second distance corresponding to each pixel point and the radius of the fitting sphere corresponding to the fitting sphere, and determine the height map corresponding to the corrected layer line.

[0096] Furthermore, if the target topographic map includes a pupil center distance map, the device also includes: a pupil center distance map determination module; the pupil center distance map determination module is used to: for each corrected stratification line, obtain each pixel point in the corrected stratification line; calculate the third distance between each pixel point and a preset polar coordinate origin; wherein the polar coordinate origin is located on the anterior surface of the cornea, the posterior surface of the cornea, the anterior surface of the lens or the posterior surface of the lens; and determine the pupil center distance map corresponding to the corrected stratification line according to the third distance corresponding to each pixel point.

[0097] Furthermore, the stratification lines corresponding to each layer of the fundus include: the stratification line corresponding to the internal limiting membrane layer, the stratification line between the nerve fiber layer and the ganglion cell layer, the stratification line between the inner plexiform layer and the inner nuclear layer, the stratification line between the inner nuclear layer and the outer plexiform layer, the stratification line corresponding to the pigment epithelium layer, the stratification line corresponding to Bruch's membrane, and the stratification line corresponding to the choroid layer.

[0098] Furthermore, the first acquisition module 70 is also used to: scan the whole eye according to a preset scanning method to obtain a whole-eye OCT image with the OCT scanning center aligned with the corneal vertex of the eye to be tested; wherein the preset scanning methods include: a star scanning method in a posterior segment scanning mode; extracting a fundus OCT image from the whole-eye OCT image.

[0099] Furthermore, the first acquisition module 70 is further used to: scan the entire eye according to a preset scanning method;

[0100] During the scanning process, the tilt of the lens is detected; if the tilt meets the preset tilt angle threshold, a full-eye OCT image is acquired with the OCT scanning center aligned with the corneal vertex of the eye to be tested.

[0101] The fundus image processing device provided in the embodiment of the present invention has the same implementation principle and technical effects as those in the aforementioned fundus image processing method embodiment. For the sake of brief description, for matters not mentioned in the embodiment of the fundus image processing device, reference may be made to the corresponding contents in the aforementioned fundus image processing method embodiment.

[0102] The embodiment of the present invention further provides an electronic device, see Figure 8 As shown, the electronic device includes a processor 130 and a memory 131 , wherein the memory 131 stores machine executable instructions that can be executed by the processor 130 , and the processor 130 executes the machine executable instructions to implement the above fundus image processing method.

[0103] Further, Figure 8 The electronic device shown further includes a bus 132 and a communication interface 133 , and the processor 130 , the communication interface 133 and the memory 131 are connected via the bus 132 .

[0104] The memory 131 may include a high-speed random access memory (RAM), and may also include a non-volatile memory, such as at least one disk storage. The communication connection between the system network element and at least one other network element is realized through at least one communication interface 133 (which may be wired or wireless), and the Internet, wide area network, local area network, metropolitan area network, etc. may be used. The bus 132 may be an ISA bus, a PCI bus, or an EISA bus, etc. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 8 Only one bidirectional arrow is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0105] The processor 130 may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method can be completed by the hardware integrated logic circuit or software instructions in the processor 130. The above processor 130 can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components. The methods, steps and logic block diagrams disclosed in the embodiments of the present invention can be implemented or executed. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor, etc. The steps of the method disclosed in conjunction with the embodiments of the present invention can be directly embodied as a hardware decoding processor for execution, or a combination of hardware and software modules in the decoding processor for execution. The software module may be located in a storage medium mature in the art, such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory, or an electrically erasable programmable memory, a register, etc. The storage medium is located in the memory 131, and the processor 130 reads the information in the memory 131 and completes the steps of the method of the above embodiment in combination with its hardware.

[0106] An embodiment of the present invention also provides a machine-readable storage medium, which stores machine-executable instructions. When the machine-executable instructions are called and executed by a processor, the machine-executable instructions prompt the processor to implement the above-mentioned fundus image processing method. The specific implementation can be found in the method embodiment, which will not be repeated here.

[0107] The computer program products of the fundus image processing method, device and electronic device provided in the embodiments of the present invention include a computer-readable storage medium storing program code. The instructions included in the program code can be used to execute the methods described in the previous method embodiments. The specific implementation can be found in the method embodiments and will not be repeated here.

[0108] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc., which can store program codes.

[0109] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A fundus image processing method, characterized in that: The method comprises: Acquire a fundus OCT image with the OCT scanning center aligned with the corneal vertex of the eye to be tested; the OCT optical focus is aligned with the retina of the eye to be tested; the fundus OCT image includes the fovea of ​​the retina of the eye to be tested; Extracting a layer line corresponding to each layer of the fundus from the fundus OCT image, and performing curvature correction on each layer line to obtain each corrected layer line; For each corrected stratification line, a target topographic map corresponding to the corrected stratification line is calculated; wherein the target topographic map includes at least one of the following: an axial curvature topographic map, a tangential curvature topographic map, a height map, and a pupil center distance map.

2. The method according to claim 1, characterized in that If the target topography includes an axial curvature topography, the axial curvature topography is determined in the following manner: For each corrected layer line, obtain each pixel point in the corrected layer line; For each pixel point, determining the meridian plane where the pixel point and the pre-acquired eye axis are located; On the meridian plane, determining the intersection point of the normal line of the pixel point and the eye axis; Calculating a first distance between the pixel point and the intersection point; According to the first distance corresponding to each pixel point, the axial curvature topographic map corresponding to the corrected layering line is determined.

3. The method according to claim 1, characterized in that If the target topographic map includes a tangential curvature topographic map, the tangential curvature topographic map is determined in the following manner: For each corrected layer line, obtain each pixel point in the corrected layer line; For each pixel point, determining the meridian plane where the pixel point and the pre-acquired eye axis are located; On the meridian plane, calculating the radius of curvature corresponding to the pixel point; According to the curvature radius corresponding to each pixel point, the tangential curvature topographic map corresponding to the corrected layering line is determined.

4. The method according to claim 1, characterized in that: If the target terrain map includes a height map, the height map is determined in the following manner: For each corrected layer line, obtain each pixel point in the corrected layer line; Perform spherical fitting based on each pixel point to obtain a fitting spherical surface; Calculating the second distance between each pixel point and the center of the fitting sphere respectively; The difference between the second distance corresponding to each pixel point and the radius of the fitting sphere corresponding to the fitting spherical surface is calculated to determine the height map corresponding to the corrected layering line.

5. The method according to claim 1, characterized in that If the target topographic map includes a pupil center distance map, the pupil center distance map is determined in the following manner: For each corrected layer line, obtain each pixel point in the corrected layer line; Calculating a third distance between each pixel point and a preset polar coordinate origin; wherein the polar coordinate origin is located on the front surface of the cornea, the rear surface of the cornea, the front surface of the lens, or the rear surface of the lens; According to the third distance corresponding to each pixel point, a pupil center distance map corresponding to the corrected stratification line is determined.

6. The method according to claim 1, characterized in that The stratification lines corresponding to each stratum of the fundus include: the stratification line corresponding to the inner limiting membrane layer, the stratification line between the nerve fiber layer and the ganglion cell layer, the stratification line between the inner plexiform layer and the inner nuclear layer, the stratification line between the inner nuclear layer and the outer plexiform layer, the stratification line corresponding to the pigment epithelium layer, the stratification line corresponding to Bruch's membrane, and the stratification line corresponding to the choroid layer.

7. The method according to claim 1, characterized in that The steps of obtaining a fundus OCT image with the OCT scanning center aligned with the corneal vertex of the eye to be tested include: Scan the whole eye according to a preset scanning mode to obtain a whole-eye OCT image with the OCT scanning center aligned with the corneal vertex of the eye to be tested; wherein the preset scanning mode includes: a star scanning mode in a posterior segment scanning mode; A fundus OCT image is extracted from the whole-eye OCT image.

8. The method according to claim 7, characterized in that The steps of scanning the whole eye in a preset scanning mode and obtaining a whole eye OCT image with the OCT scanning center aligned with the corneal vertex of the eye to be tested include: Scan the entire eye according to a preset scanning method; During the scan, the tilt of the lens is detected; If the inclination satisfies a preset inclination angle threshold, a full-eye OCT image is acquired with the OCT scanning center aligned with the corneal vertex of the eye to be tested.

9. A fundus image processing device, characterized in that: The device comprises: The first acquisition module is used to acquire a fundus OCT image with the OCT scanning center aligned with the corneal vertex of the eye to be tested; the OCT optical focus is aligned with the retina of the eye to be tested; the fundus OCT image includes the retinal fovea of ​​the eye to be tested; A second acquisition module is used to extract the layer line corresponding to each layer of the fundus from the fundus OCT image, and perform curvature correction on each layer line to obtain each corrected layer line; A calculation module is used to calculate, for each corrected stratification line, a target topographic map corresponding to the corrected stratification line; wherein the target topographic map includes at least one of the following: an axial curvature topographic map, a tangential curvature topographic map, a height map, and a pupil center distance map.

10. An electronic device, characterized in that: The invention comprises a processor and a memory, wherein the memory stores machine executable instructions that can be executed by the processor, and the processor executes the machine executable instructions to implement the fundus image processing method according to any one of claims 1 to 8.

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