Algorithms for Assessment and Segmentation of Fundus Image Quality in Eye Diseases

Mirzayev, N., Shamsiyeva, X.G.

Рақамли технологияларнинг назарий ва амалий масалалари · 2024-yil

Annotatsiya

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.

Maqola ma’lumotlari
MualliflarMirzayev, N., Shamsiyeva, X.G.
JurnalРақамли технологияларнинг назарий ва амалий масалалари
Nashr sanasi2024-12-30
Jild7
Son4
Betlar73-79
TilRus
DOI10.62132/ijdt.v7i4.222

Kalit so‘zlar

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

Ilmiy soha

Рақамли технологияларнинг назарий ва амалий масалалари jurnalidan boshqa maqolalar

Рақамли технологияларнинг назарий ва амалий масалалари — barcha maqolalar