Method for determining structural progression of eye disease and device thereof

1 . A device for determining structural progression of an eye disease, the device comprising:

a processor; and

a memory electrically connected to the processor,

wherein, when the processor is executed, the memory stores instructions for:

obtaining a first-n th ocular image, which is an n th first ocular image for a user (where n is a natural number),

obtaining a second-n th ocular image, which is an n th second ocular image for the user,

combining the first-n th ocular image and the second-n th ocular image according to a preset method to generate an n th combined image, and

generating an n th eye disease image for the user by using the n th combined image and a preset prone area image,

wherein the first-n th ocular image is an ocular image of the user's optic disc,

wherein the second-n th ocular image is an ocular image of the user's macula, and

wherein the preset prone area image includes a first area corresponding to the optic disc, a second area where optic nerve damage is observed in the optic disc, and a third area where the optic nerve damage is observed in the macular area.

2 . The device of claim 1 , wherein the memory stores instructions for generating a first-n th comparison image by using an optic nerve thickness of the first-n th ocular image and a pre-stored first-(n−1) th ocular image, generating a second-n th comparison image by using an optic nerve thickness of the second-n th ocular image and a pre-stored second-(n−1) th ocular image, and generating the n th combined image by combining the first-n th comparison image and the second-n th comparison image according to a preset method.

3 . The device of claim 2 , wherein the memory stores instructions for generating the n th combined image by matching a blood vessel portion of the first-n th comparison image and a blood vessel portion of the second-n th comparison image.

4 . The device of claim 1 , wherein the memory stores instructions for generating an n th eye disease progression image for the user using pre-stored first to n−1 combined images and the n th combined image, and generating the n th eye disease image by combining the n th eye disease progression image and the prone area image.

5 . The device of claim 4 , wherein the memory stores instructions for, when an eye disease progression image of another person corresponding to the n th eye disease progression image is searched, analyzing the degree of eye disease progression of the user using the eye disease progression image of another person.

6 . The device of claim 5 , wherein the memory stores instructions for searching for the eye disease progression image of another person considering a generation period and an optic nerve change position corresponding to the n th eye disease image,

wherein the generation period corresponds to a generation period of a first eye disease image to the n th eye disease image,

wherein the optic nerve change position corresponds to an optic nerve change position of each of a first combined image to the n th combined image,

wherein the first eye disease image is a first image of eye disease of the user, and

wherein the first combined image is a first combined image of the user.

7 . A method of determining structural progression of an eye disease performed in a device for determining structural progression of an eye disease, the method comprising:

obtaining a first-n th ocular image, which is an n th first ocular image for a user (where n is a natural number);

obtaining a second-n th ocular image, which is an n th second ocular image for the user;

generating an n th combined image by combining the first-n th ocular image and the second-n th ocular image according to a preset method; and

generating an n th eye disease image for the user by using the n th combined image and a preset prone area images,

wherein the first-n th ocular image is an ocular image of the user's optic disc,

wherein the second-n th ocular image is an ocular image of the user's macula, and

wherein the preset prone area image includes a first area corresponding to the optic disc, a second area where optic nerve damage is observed in the optic disc, and a third area where the optic nerve damage is observed in the macular area.

8 . The method of claim 7 , wherein the generating of the n th combined image comprises:

generating a first-n th comparison image by using an optic nerve thickness of the first-n th ocular image and a pre-stored first-(n−1) th ocular image;

generating a second-n th comparison image by using an optic nerve thickness of the second-n th ocular image and a pre-stored second-(n−1) th ocular image; and

generating the n th combined image by combining the first-n th comparison image and the second-n th comparison image according to a preset method.

9 . The method of claim 8 , wherein the generating of the n th combined image comprise generating the n th combined image by matching a blood vessel portion of the first-n th comparison image and a blood vessel portion of the second-n th comparison image.

10 . The method of claim 7 , wherein the generating of the n th eye disease image comprises:

generating an n th eye disease progression image for the user using pre-stored first to n−1 combined images and the n th combined image; and

generating the n th eye disease image by combining the n th eye disease progression image and the prone area image.

11 . The method of claim 10 , further comprising, in a case that an eye disease progression image of another person corresponding to the n th eye disease progression image is searched, analyzing the degree of eye disease progression of the user using the eye disease progression image of another person.

12 . The method of claim 11 , wherein the analyzing of the degree of eye disease progression of the user comprises:

searching for the eye disease progression image of another person considering a generation period and an optic nerve change position corresponding to the n th eye disease progression image,

wherein the generation period corresponds to a generation period of a first eye disease progression image to the n th eye disease progression image,

wherein the optic nerve change position corresponds to an optic nerve change position of each of a first combined image to the n th combined image,

wherein the first eye disease progression image is a first eye disease progression image of the user, and

wherein the first combined image is a first combined image of the user.