My Master Thesis concerns methods for the segmentation of retina fundus images based on innovative techniques from deep learning. Systematic diseases such as diabetic retinopathy, glaucoma and aged-related macular degeneration, are known to cause quantifiable changes in the morphology of the retinal microvasculature. This microvasculature is the only part of the human circulation that can be visualized non-invasively in vivo so that it can be readily photographed and processed with the tools of digital image analysis. As the treatment of serious pathologies such as diabetic retinopathy can be significantly improved with early detection, retinal image analysis has been the subject of extensive studies.