This research paper proposes that integrated approaches to image processing, the use of machine learning algorithms in segmentation, the U-Net method will help to achieve high accuracy in diagnosing various retinal diseases, and an analysis of modern methods is presented for processing and segmentation of fundus images. In this direction, an analysis of scientific and research works carried out using fundus images was carried out. Upon receipt of the results, it was verified that the U-Net method gives effective results in processing and segmentation of fundus images in the DIARETDB1 database.
| Mualliflar | Mirzayev, N., Shamsiyeva, X.G. |
|---|---|
| Jurnal | Рақамли технологияларнинг назарий ва амалий масалалари |
| Nashr sanasi | 2024-12-30 |
| Jild | 7 |
| Son | 4 |
| Betlar | 73-79 |
| Til | Rus |
| DOI | 10.62132/ijdt.v7i4.222 |
DOI: 10.62132/ijdt.v7i4.222 · Maqolaning asl sahifasi
Fundus kamera, ko‘z kasalliklari, to‘r parda, diabetik retinopatiya, raqamli tasvir, tasvir sifatini baholash, U-Net, segmentlash, Fundus camera, eye diseases, retina, diabetic retinopathy, digital imaging, image quality assessment, U-Net, segmentation
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