Application US20200187775

EYE DISEASE DIAGNOSIS METHOD AND SYSTEM USING ARTIFICIAL INTELLIGENCE
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US20200187775

1. An eye disease diagnosis method using artificial intelligence, the eye disease diagnosis method comprising: (4) (4)

collecting, from a database, a first eyeground image of a myopic patient who is not diagnosed with an eye disease and a second eyeground image of a myopic patient who has been diagnosed with the eye disease;

learning eyeball change information by degree of myopia based on the first eyeground image, using deep learning;

comparing and analyzing the first eyeground image and the second eyeground image based on the eyeball change information by the degree of myopia, and learning eyeball change information by the eye disease using deep learning; and

estimating determination criteria of an eyeground image for diagnosis of the eye disease, based on a difference between the eyeball change information by the degree of myopia and the eyeball change information by the eye disease.

2. The eye disease diagnosis method of claim 1, wherein the eyeball change information by the degree of myopia comprises one or more of twisted optic nerve, myopic maculopathy and peripapillary atrophy. (0)

3. The eye disease diagnosis method of claim 1, wherein the eyeball change information by the eye disease comprises one or more of the border thickness and shape of an optic nerve disc, the color of optic nerves, the shape of macula and peripapillary atrophy. (0)

4. The eye disease diagnosis method of claim 1, further comprising analyzing an eyeground image of a test subject based on the determination criteria and diagnosing an eye disease of the test subject, when the eyeground image of the test subject is inputted. (0)

9. A computer-readable recording medium which stores a program for implementing the method of claim 1. (0)

5. An eye disease diagnosis system using artificial intelligence, the eye disease diagnosis system comprising: (3) (4)

a data collection unit configured to collect, from a database, a first eyeground image of a myopic patient who is not diagnosed with an eye disease and a second eyeground image of a myopic patient who has been diagnosed with the eye disease;

a first deep learning unit configured to learn eyeball change information by degree of myopia based on the first eyeground image, using deep learning;

a second deep learning unit configured to compare and analyze the first eyeground image and the second eyeground image based on the eyeball change information by the degree of myopia, and learn eyeball change information by the eye disease using deep learning; and

a determination criteria estimation unit configured to estimate determination criteria of an eyeground image for diagnosis of the eye disease, based on a difference between the eyeball change information by the degree of myopia and the eyeball change information by the eye disease.

6. The eye disease diagnosis system of claim 5, wherein the eyeball change information by the degree of myopia comprises one or more of twisted optic nerve, myopic maculopathy and peripapillary atrophy. (0)

7. The eye disease diagnosis system of claim 5, wherein the eyeball change information by the eye disease comprises one or more of the border thickness and shape of an optic nerve disc, the color of optic nerves, the shape of macula and peripapillary atrophy. (0)

8. The eye disease diagnosis system of claim 5, further comprising an eye disease diagnosis unit configured to analyze an eyeground image of a test subject based on the determination criteria and diagnose an eye disease of the test subject, when the eyeground image of the test subject is inputted through the data collection unit. (0)

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Application US20200187775

EYE DISEASE DIAGNOSIS METHOD AND SYSTEM USING ARTIFICIAL INTELLIGENCE

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