Application of artificial intelligence in ophthalmology for solving the problem of semantic segmentation of fundus images
The paper presents main aspects of the application of artificial intelligence in ophthalmology for the diagnosis and treatment of eye diseases, considering the problem of semantic segmentation of fundus images as an example. The classic approach to semantic segmentation on the basis of textural feat...
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| Format: | Article |
| Language: | English |
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Samara National Research University
2023-10-01
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| Series: | Компьютерная оптика |
| Subjects: | |
| Online Access: | https://www.computeroptics.ru/eng/KO/Annot/KO47-5/470517e.html |
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| author | N.S. Demin N.Y. Ilyasova R.A. Paringer D.V. Kirsh |
| author_facet | N.S. Demin N.Y. Ilyasova R.A. Paringer D.V. Kirsh |
| author_sort | N.S. Demin |
| collection | DOAJ |
| description | The paper presents main aspects of the application of artificial intelligence in ophthalmology for the diagnosis and treatment of eye diseases, considering the problem of semantic segmentation of fundus images as an example. The classic approach to semantic segmentation on the basis of textural features is compared to the proposed approach based on neural networks. Basic problems of using the neural network approach in biomedicine are formulated. We propose a new method for selecting an optimal zone of laser exposure for laser coagulation based on two neural networks. The first network is used for detecting anatomical objects in the fundus and the second one is used for selecting the area of macular edema. The region of interest is formed from the edema area while taking into account the location of anatomical objects in it. A comparative analysis of sev-eral architectures of neural networks for solving the problem of selecting the edema area is carried out. The best results in the selection of the edema area are shown by the neural network architecture of Unet++. |
| format | Article |
| id | doaj-art-f094f8f03b2143a794ff9933026cde35 |
| institution | Kabale University |
| issn | 0134-2452 2412-6179 |
| language | English |
| publishDate | 2023-10-01 |
| publisher | Samara National Research University |
| record_format | Article |
| series | Компьютерная оптика |
| spelling | doaj-art-f094f8f03b2143a794ff9933026cde352025-01-23T06:06:30ZengSamara National Research UniversityКомпьютерная оптика0134-24522412-61792023-10-0147582483110.18287/2412-6179-CO-1283Application of artificial intelligence in ophthalmology for solving the problem of semantic segmentation of fundus imagesN.S. Demin0N.Y. Ilyasova1R.A. Paringer2D.V. Kirsh3IPSI RAS – Branch of the FSRC "Crystallography and Photonics" RAS; Samara National Research UniversityIPSI RAS – Branch of the FSRC "Crystallography and Photonics" RAS; Samara National Research UniversityIPSI RAS – Branch of the FSRC "Crystallography and Photonics" RAS; Samara National Research UniversitySamara National Research University; IPSI RAS – Branch of the FSRC "Crystallography and Photonics" RASThe paper presents main aspects of the application of artificial intelligence in ophthalmology for the diagnosis and treatment of eye diseases, considering the problem of semantic segmentation of fundus images as an example. The classic approach to semantic segmentation on the basis of textural features is compared to the proposed approach based on neural networks. Basic problems of using the neural network approach in biomedicine are formulated. We propose a new method for selecting an optimal zone of laser exposure for laser coagulation based on two neural networks. The first network is used for detecting anatomical objects in the fundus and the second one is used for selecting the area of macular edema. The region of interest is formed from the edema area while taking into account the location of anatomical objects in it. A comparative analysis of sev-eral architectures of neural networks for solving the problem of selecting the edema area is carried out. The best results in the selection of the edema area are shown by the neural network architecture of Unet++.https://www.computeroptics.ru/eng/KO/Annot/KO47-5/470517e.htmlfundus imagelaser coagulationdiabetic retinopathyimage processingsegmentationneural networkartificial intelligence |
| spellingShingle | N.S. Demin N.Y. Ilyasova R.A. Paringer D.V. Kirsh Application of artificial intelligence in ophthalmology for solving the problem of semantic segmentation of fundus images Компьютерная оптика fundus image laser coagulation diabetic retinopathy image processing segmentation neural network artificial intelligence |
| title | Application of artificial intelligence in ophthalmology for solving the problem of semantic segmentation of fundus images |
| title_full | Application of artificial intelligence in ophthalmology for solving the problem of semantic segmentation of fundus images |
| title_fullStr | Application of artificial intelligence in ophthalmology for solving the problem of semantic segmentation of fundus images |
| title_full_unstemmed | Application of artificial intelligence in ophthalmology for solving the problem of semantic segmentation of fundus images |
| title_short | Application of artificial intelligence in ophthalmology for solving the problem of semantic segmentation of fundus images |
| title_sort | application of artificial intelligence in ophthalmology for solving the problem of semantic segmentation of fundus images |
| topic | fundus image laser coagulation diabetic retinopathy image processing segmentation neural network artificial intelligence |
| url | https://www.computeroptics.ru/eng/KO/Annot/KO47-5/470517e.html |
| work_keys_str_mv | AT nsdemin applicationofartificialintelligenceinophthalmologyforsolvingtheproblemofsemanticsegmentationoffundusimages AT nyilyasova applicationofartificialintelligenceinophthalmologyforsolvingtheproblemofsemanticsegmentationoffundusimages AT raparinger applicationofartificialintelligenceinophthalmologyforsolvingtheproblemofsemanticsegmentationoffundusimages AT dvkirsh applicationofartificialintelligenceinophthalmologyforsolvingtheproblemofsemanticsegmentationoffundusimages |