During this reporting period, the development of a tool usable to connect flood vessels in fundus images gave a contribution to the retinal community. This work, which was published at IEEE EMBC 2015, presented a tool that used implicit neural cost functions to join retinal vessels. Results obtained showed that the quality of the segmentation affected the outcome of connectivity algorithms and by enhancing the segmentation the connectivity was improved. Research focused also on arteries and veins recognition in fundus image. This is a topic of high interest in order to insight the study of diseases. An algorithm able to classify arteries and veins after segmenting vessels is currently being implemented and tested.
Collaboration was carried out with ESR 3.3 Giovanni Ometto. In this work, a fast method for the definition of clinically relevant retinal areas in use for screening programmes for diabetic retinopaghy was produced.