A multi-stage semi-supervised learning approach to spine image segmentation

• Main Author: Pan, Ruixiang
• Other Authors: Lin Zhiping
• Format: Thesis-Master by Coursework
• Language: English
• Published: Nanyang Technological University 2024
• Subjects: Engineering; Spine segmentation; Unet; Semi-supervised learning; Fracture; 2.5D; Multi-stage
• Online Access: https://hdl.handle.net/10356/174682
• Institution: Nanyang Technological University

Spine segmentation in computed tomography (CT) images is critical for automatic analysis, especially when focusing on varied spinal regions. Despite having comprehensive annotations for normal vertebrae, the current dataset does not encompass fracture data, posing challenges for predictive modeli...