Unifying the seeds auto-generation (SAGE) with knee cartilage segmentation framework: data from the osteoarthritis initiative

Hong-Seng Gan, Khairil Amir Sayuti, Muhammad Hanif Ramlee, Yeng-Seng Lee, Wan Mahani Hafizah Wan Mahmud, Ahmad Helmy Abdul Karim

Abstract: Manual segmentation is sensitive to operator bias, while semiautomatic random walks segmentation offers an intuitive approach to understand the user knowledge at the expense of large amount of user input. In this paper, we propose a novel random walks seed auto-generation (SAGE) hybrid model that is robust to interobserver error and intensive user intervention.