Open AccessA Lumen Segmentation Method in Ureteroscopy Images based on a Deep Residual U-Net architecture
Author(s) -
Jorge F. Lazo,
Aldo Marzullo,
Sara Moccia,
Michele Catellani,
Benoit Rosa,
Francesco Calimeri,
Michel de Mathelin,
Elena De Momi
Publication year - 2021
Publication title -
hal (le centre pour la communication scientifique directe)
Language(s) - English
Resource type - Conference proceedings
Subject(s) - residual , computer science , ureteroscopy , segmentation , artificial intelligence , image segmentation , lumen (anatomy) , architecture , computer vision , medicine , algorithm , surgery , geography , archaeology , ureter