Quantitative evaluation method, apparatus, and storage medium for conjunctival congestion

Abstract

The present invention discloses a method, an apparatus, and a storage medium for quantitatively evaluating conjunctival congestion. The method for quantitatively evaluating conjunctival congestion includes step S1 of acquiring a video of the movement of the eye from the inner side to the outer side or from the outer side to the inner side, step S2 of performing eye image segmentation on the video to obtain an eye conjunctival image and extracting the red channel value and the blue channel value of each pixel from the eye conjunctival image, and step S3 of determining the percentage of conjunctival congestion based on the proportional value between the red channel value and the blue channel value of each pixel. By the method for quantitatively evaluating conjunctival congestion, an accurate value of conjunctival congestion can be obtained.

Description

Technical Field

[0001] The present invention relates to the technical field of eye detection, and particularly to a method, apparatus, and storage medium for quantitatively evaluating conjunctival hyperemia.

Background Art

[0002] The degree of conjunctival hyperemia is one of the important reference indicators when a doctor evaluates a patient's eye inflammation. Clinically, the doctor needs to judge whether the degree of conjunctival hyperemia is mild, moderate, or severe within 1 m from the patient by artificial experience. Due to the subjective consciousness of different doctors, there is no unified standard for the judgment of mild, moderate, and severe degrees, which is likely to cause misdiagnosis and missed diagnosis.

[0003] There is a problem that the accuracy in manual measurement is affected by human factors. In the prior art, technical means related to image recognition depending on shape have been proposed. As described in Chinese Patent CN111212594A (Application No.: CN201880066273.2, Publication Date: May 29, 2020), an image including an eye photographed by a camera is acquired, one or more blood vessels in the image are identified, and the degree of conjunctival hyperemia is determined based on the size of the one or more identified blood vessels. Further, in the prior art, a method for examining the degree of conjunctival hyperemia by using the ratio of the red pixel value of the eye part is disclosed. In this method, specifically, a high-resolution eye image is acquired, the eye image is converted from RGB to gray, a Gaussian filter is used to find a region where the difference in gradients in the horizontal and vertical directions is large, and a filter heat map is used to divide the hyperemic part and the non-hyperemic part by using a threshold value.

[0004] However, eye congestion is often conjunctival congestion, and the congestion in this area is often diffuse. Therefore, when using a discrimination method that depends on shape in the prior art, the following drawbacks exist. 1. It is easily affected by the lightness and darkness of the blood vessel color, and the red pixel value cannot be accurately extracted, resulting in inaccurate discrimination. 2. Due to the characteristics of the human eye structure, there are shadows at the intersection of the eyelid and the eyeball, which affects the accuracy. 3. The same light beam irradiates the eyeball, and since the eyeball is spherical, a situation where the light becomes uneven occurs.

Summary of the Invention

Problems to be Solved by the Invention

[0005] In order to solve the problem that the accuracy in measuring the degree of conjunctival congestion in the prior art is not high, the present invention provides a quantitative evaluation method for conjunctival congestion.

Means for Solving the Problems

[0006] To achieve the above object, the present invention uses the following technical means.

[0007] In one aspect, the quantitative evaluation method for conjunctival congestion according to the present invention includes: Step S1 of acquiring a video of the movement of the eyeball from the inside to the outside or from the outside to the inside; Step S2 of performing eye image segmentation on the video to obtain an eye conjunctival image, and extracting the red channel value and blue channel value of each pixel from the eye conjunctival image; Step S3 of determining the percentage of conjunctival congestion based on the proportional value between the red channel value and the blue channel value of each pixel.

[0008] Furthermore, in step S2, the second eye position images when the eyeball moves to the inner and outer limit positions are respectively acquired, and the eye conjunctival image is obtained by combining the second eye position image when the eyeball moves to the inner limit position and the second eye position image when the eyeball moves to the outer limit position.

[0009] Furthermore, in step S3, it is determined that a pixel point where the proportional value between the red channel value and the blue channel value exceeds the threshold is a congested area, and the percentage of conjunctival congestion is the percentage of the area of the pixel points in the congested area occupying the conjunctival area of the ocular conjunctival image.

[0010] Furthermore, the threshold value is a preset fixed value or a manually set value.

[0011] In one aspect, the apparatus for quantitatively evaluating conjunctival congestion according to the present application includes a video acquisition module that acquires a video of the movement of the eyeball from the inside to the outside or from the outside to the inside in response to a video acquisition command; a feature extraction module that performs ocular image segmentation on the video to obtain an ocular conjunctival image, and extracts the red channel value and blue channel value of each pixel from the ocular conjunctival image; and a calculation module that calculates the proportional value between the red channel value and the blue channel value of each pixel to determine the percentage of conjunctival congestion.

[0012] Furthermore, the feature extraction module further includes an image extraction module that extracts a second eye position image in which the eyeball moves to the limit positions inside and outside from the video.

[0013] In one aspect, at least one program code that is loaded and executed by a processor to implement the method for quantitatively evaluating conjunctival congestion in the foregoing first aspect is stored in the computer-readable storage medium according to the present invention.

Advantages of the Invention

[0014] Compared with the prior art, the present invention has at least the following beneficial effects.

[0015] In the present invention, after synthesizing the ocular conjunctiva image with the second eye position image in which the eyeball moves to the inner and outer limit positions, the red channel value and the blue channel value are extracted from each pixel of the image. Since the light reflected in the congested area is mainly red light and the sclera itself has a high reflectivity for both red and blue, at the location where there is a congested area, the red channel value is significantly higher than the blue channel value, and at the location where there is no congested area, the red channel value and the blue channel value are equivalent. The congestion point can be accurately determined by the proportional value between the red channel value and the blue channel value of each pixel, and the percentage of conjunctival congestion can be determined.

Brief Description of the Drawings

[0016]

Figure 1

Figure 2

Figure 3

Figure 4

Modes for Carrying Out the Invention

[0017] Hereinafter, with reference to the drawings and examples, specific embodiments of the present invention will be described in more detail. The following examples are for explaining the present invention and do not limit the scope of the present invention.

[0018] As shown in FIGS. 1 to 3, the method for quantitatively evaluating conjunctival congestion includes the following steps S1 to S3.

[0019] In step S1, a video of the movement of the eyeball from the inner side to the outer side or from the outer side to the inner side is acquired. Specifically, in step S1, the user's eyes and head are fixed by an eye evaluation or measurement device, and a video of the user's eyeballs moving horizontally from the inside to the outside or from the outside to the inside is captured by a camera provided in front of the user's eyes, and the movement of the user's eyeballs may be instructed using an indicator lamp.

[0020] Videos of the necessary eye movements may be obtained by other eye devices or video collection devices.

[0021] In step S2, eye image segmentation is performed on the video to obtain an eye conjunctiva image, and the red channel value and blue channel value of each pixel are extracted from the eye conjunctiva image. Specifically, in step S2, an eye conjunctiva image with the eyeballs removed can be obtained by performing eye image segmentation on the video. Specifically, second eye position images in which the eyeballs move from the inside to the outside and from the outside to the inside to their limit positions are respectively extracted from the video, and the second eye position image in which the extracted eyeballs move to the inner limit position and the second eye position image in which the eyeballs move to the outer limit position are combined to obtain an eye conjunctiva image, thereby obtaining an eye conjunctiva image unaffected by the eyeball image, and the red channel value and blue channel value of each pixel point are extracted from the eye conjunctiva image.

[0022] Note that the eye position refers to the position of the eyeballs in an ophthalmic examination and is divided into the first eye position, the second eye position, and the third eye position. The first eye position refers to the eye position when both eyes are looking straight at an infinitely distant point on the horizontal plane. The second eye position refers to the eye position when the eyeballs rotate upward, downward, inward, and outward. The third eye position refers to the eye position when the eyeballs rotate diagonally upward, downward, inward, and outward, that is, when they rotate upward, downward, temporally upward, and temporally downward. Accordingly, the first, second, and third eye position images respectively refer to the images captured when the eyeballs are in each eye position.

[0023] In step S3, the percentage of conjunctival congestion is determined based on the proportional value of the red channel value and the blue channel value of each pixel.

[0024] In the step S3, it is determined that the pixel points where the proportional value between the red channel value and the blue channel value exceeds the threshold value are the congested parts, and the percentage of conjunctival congestion is the percentage that the area of the pixel points in the congested part occupies the conjunctival area of the ocular conjunctival image. Since the light reflected in the congested area is mainly red light and the sclera itself has a high reflectivity for both red and blue, at the location with a congested part, the red channel value is significantly higher than the blue channel value, and at the location without a congested part, the red channel value and the blue channel value are equal. Therefore, the percentage of conjunctival congestion is determined by the proportional value between the red channel value and the blue channel value of each pixel. Specifically, the threshold value is a preset fixed value or a manually set value. For example, the threshold value 3 may be input in advance in a computer, and it is determined that the pixel points where the proportional value between the red channel value and the blue channel value exceeds 3 are the congested parts. When the RGB value of a certain pixel point is RGB(250, 245, 240), the red channel value and the blue channel value are equal and the ratio of the two is close to 1, then this pixel point is not a congested part but the white color of the sclera itself. When the RGB value of a certain pixel point is RGB(250, 20, 15), if the proportional value between the red channel value and the blue channel value exceeds the threshold value 3, it is determined that this pixel point is a congested part. In addition to inputting the threshold value in advance, the threshold value may also be a value manually set by a technician such as a doctor or an operator based on experience.

[0025] Figure 3 shows more specifically the step diagram of the quantitative evaluation method for conjunctival congestion. First, the user controls the left and right movements of the eyeball in front of the camera and records it in a video. Next, ocular image segmentation is performed. When performing ocular image segmentation, the second eye position images when the eyeball moves to the inner and outer limit positions are respectively obtained. The second eye position image when the eyeball moves to the inner limit position and the second eye position image when the eyeball moves to the outer limit position are combined to obtain an ocular conjunctival image. The red channel value and the blue channel value of each pixel point in the ocular conjunctival image are extracted. Further, the ratio of the red and blue channel pixel values of each pixel point is obtained, and based on a preset threshold value or a manually set threshold value, it is determined whether each pixel point is a congested part, thereby obtaining the percentage of the congested part.

[0026] Figure 4 is a schematic configuration diagram of a conjunctival congestion quantitative evaluation apparatus 40 according to an embodiment of the present invention. As shown in Figure 4, the apparatus includes a video acquisition module 401, a feature extraction module 402, and a calculation module 403.

[0027] The video acquisition module 401 acquires a video of the movement of the eyeball from the inside to the outside or from the outside to the inside in response to a video acquisition command. In a possible embodiment, when receiving an acquisition command, the video acquisition module controls a camera or other imaging device to start up, and controls an audio device or an illumination device to guide the user's eye movement, so as to acquire a video of the required eye movement.

[0028] The feature extraction module 402 performs eye image segmentation on the video to obtain an eye conjunctiva image, and extracts the red channel value and blue channel value of each pixel from the eye conjunctiva image.

[0029] The calculation module 403 calculates the proportional value of the red channel value and the blue channel value of each pixel to determine the percentage of conjunctival congestion.

[0030] Furthermore, the feature extraction module further includes an image extraction module that extracts a second eye position image in which the eyeball moves to the limit positions inside and outside from the video.

[0031] In an exemplary embodiment, there is further provided a computer-readable storage medium including a memory in which at least one program code loaded and executed by a processor to implement the conjunctival congestion quantitative evaluation method in the above embodiment is stored. For example, the computer-readable storage medium may be a read-only memory (ROM), a random access memory (RAM), a compact disc read-only memory (CDROM), a magnetic tape, a floppy disk, and an optical data storage device, etc.

[0032] A person skilled in the art would understand that the implementation of all or part of the steps in the above embodiments may be completed by hardware, may also be completed by hardware related to at least one program code, the program may be stored in a computer-readable storage medium, and the above-mentioned storage medium may be a read-only memory, a magnetic disk, an optical disk, or the like.

[0033] The above are only preferred embodiments of the present invention, and do not limit the present invention. All modifications, equivalent substitutions, improvements, etc. made within the concept and principles of the present invention should all be included within the protection scope of the present invention.

Claims

1. Step S1 of obtaining a video of the movement of the eyeball from the inside to the outside or from the outside to the inside; Step S2 of performing eye image segmentation on the video to obtain an eye conjunctiva image, and extracting the red channel value and blue channel value of each pixel from the eye conjunctiva image; Step S3 of determining the percentage of conjunctival congestion based on the proportional value between the red channel value and the blue channel value of each pixel, A quantitative evaluation method for conjunctival congestion, characterized by the above.

2. In step S2, a second eye position image in which the eyeball moves to the inner and outer limit positions is respectively obtained, and the second eye position image in which the eyeball moves to the inner limit position and the second eye position image in which the eyeball moves to the outer limit position are combined to obtain the eye conjunctiva image, The quantitative evaluation method for conjunctival congestion according to claim 1, characterized by the above.

3. In step S3, it is determined that the pixel points where the proportional value between the red channel value and the blue channel value exceeds the threshold are the congested parts, and the percentage of conjunctival congestion is the percentage of the area of the pixel points in the congested part occupying the conjunctiva area of the eye conjunctiva image, The quantitative evaluation method for conjunctival congestion according to claim 1, characterized by the above.

4. The threshold is a preset fixed value or a manually set value, The quantitative evaluation method for conjunctival congestion according to claim 3, characterized by the above.

5. A video acquisition module that acquires a video of the movement of the eyeball from the inside to the outside or from the outside to the inside in response to a video acquisition command; A feature extraction module that performs eye image segmentation on the video to obtain an eye conjunctiva image, and extracts the red channel value and blue channel value of each pixel from the eye conjunctiva image; A calculation module that calculates the proportional value between the red channel value and the blue channel value of each pixel and determines the percentage of conjunctival congestion, A quantitative evaluation device for conjunctival congestion, characterized by the above.

6. The feature extraction module, extracts a second eye position image in which the eyeball moves to the inner and outer limit positions from the video, and includes an image processing sub-module that combines the second eye position image in which the eyeball moves to the inner limit position and the second eye position image in which the eyeball moves to the outer limit position to obtain the eye conjunctiva image, The quantitative evaluation device for conjunctival congestion according to claim 5, characterized by the above.

7. At least one program code that is loaded by a processor and executes the method for quantitatively evaluating conjunctival congestion according to any one of claims 1 to 4 is stored, A computer-readable storage medium, characterized in that.

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