Рақамли технологияларнинг назарий ва амалий масалалари 7-tom 4-san (2024) · 73-79-betler
Algorithms for Assessment and Segmentation of Fundus Image Quality in Eye Diseases
Mirzayev, N., Shamsiyeva, X.G.
Annotaciya
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.
Fundus kamerako‘z kasalliklarito‘r pardadiabetik retinopatiyaraqamli tasvirtasvir sifatini baholashU-NetsegmentlashFundus cameraeye diseases
Metadata derekkózi: jurnal OAI-PMH arxivi · Sindex tolıq mátindi saqlamaydı, derekkózge silteme beredi.