{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/retinal-vessel-segmentation-based-on-fully","title":"Retinal vessel segmentation based on Fully Convolutional Neural Networks","arxiv_id":"1812.07110","date":"2018-12-18","proceeding":null,"authors":["Américo Oliveira","Sérgio Pereira","Carlos A. Silva"],"abstract":"The retinal vascular condition is a reliable biomarker of several\nophthalmologic and cardiovascular diseases, so automatic vessel segmentation\nmay be crucial to diagnose and monitor them. In this paper, we propose a novel\nmethod that combines the multiscale analysis provided by the Stationary Wavelet\nTransform with a multiscale Fully Convolutional Neural Network to cope with the\nvarying width and direction of the vessel structure in the retina. Our proposal\nuses rotation operations as the basis of a joint strategy for both data\naugmentation and prediction, which allows us to explore the information learned\nduring training to refine the segmentation. The method was evaluated on three\npublicly available databases, achieving an average accuracy of 0.9576, 0.9694,\nand 0.9653, and average area under the ROC curve of 0.9821, 0.9905, and 0.9855\non the DRIVE, STARE, and CHASE_DB1 databases, respectively. It also appears to\nbe robust to the training set and to the inter-rater variability, which shows\nits potential for real-world applications.","url_abs":"http://arxiv.org/abs/1812.07110v2","url_pdf":"http://arxiv.org/pdf/1812.07110v2.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"retinal-vessel-segmentation-based-on-fully","repo_url":"https://github.com/americofmoliveira/VesselSegmentation_ESWA","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"data-augmentation","task_name":"Data Augmentation"},{"task_slug":"retinal-vessel-segmentation","task_name":"Retinal Vessel Segmentation"},{"task_slug":"segmentation","task_name":"Segmentation"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}