Title |
Investigation of eye fundus blood vessel segmentation using autoencoders / |
Translation of Title |
Autoenkoderių taikymas akies dugno kraujagyslėms atpažinti. |
Authors |
Shirvinskii, Aleksandr |
Full Text |
|
Pages |
47 |
Keywords [eng] |
Eye Fundus Blood Vessels, Segmentation, Autoencoders, Unet |
Abstract [eng] |
Progress of compact high definition digital retinal cameras allowed us to reveal structural and functional information about the human retina in a harmless and non-invasive way. Eye diseases cause noticeable pathological changes, so segmentation of vessels in fundus images is of great importance. In this research work I developed a new retinal vessel segmentation method that achieves state-of-the-art performance in several metrics and with threshold optimization the model showed comparable results to well researched methods on cross datasets experiments on the segmentation task. |
Dissertation Institution |
Vilniaus universitetas. |
Type |
Master thesis |
Language |
English |
Publication date |
2022 |