Thesis Details
Generation of Synthetic Retinal Images with High Resolution
Special equipment, a fundus camera, is needed to capture the retina, which is the most important part of the human eye. Therefore, the main objective of this work is to design and implement a system that would be able to generate retinal images. The proposed solution uses an image-to-image translation, where the system is provided with a black and white image at the input containing only bloodstream, on the basis of which a color image of the entire retina is generated. The system consists of two neural networks: a generator, which generates retinal images, and a discriminator, which classifies these images as real or synthetic. Training of this system was performed on 141 images from publicly available databases. A new database was created with more than 2,800 images of healthy retinas in a resolution of 1024x1024. This database could be used as a learning tool for ophthalmologists or for the development of various applications working with retinas.
human eye, eye retina, synthetic retinal images, image processing, image generation, machine learning, neural networks, GAN, high resolution, Python, TensorFlow
Burget Radek, doc. Ing., Ph.D. (DIFS FIT BUT), člen
Grégr Matěj, Ing., Ph.D. (DIFS FIT BUT), člen
Holík Lukáš, doc. Mgr., Ph.D. (DITS FIT BUT), člen
Kořenek Jan, doc. Ing., Ph.D. (DCSY FIT BUT), člen
Rychlý Marek, RNDr., Ph.D. (DIFS FIT BUT), člen
@mastersthesis{FITMT21968,
author = "Tom\'{a}\v{s} Aubrecht",
type = "Master's thesis",
title = "Generation of Synthetic Retinal Images with High Resolution",
school = "Brno University of Technology, Faculty of Information Technology",
year = 2020,
location = "Brno, CZ",
language = "english",
url = "https://www.fit.vut.cz/study/thesis/21968/"
}