For bone segmentation, the classical geodesic active contour model is usually limited by its indiscriminate feature extraction, and then struggles to handle the phenomena of edge obstruction, edge leakage and bone fracture. Thus, we propose a fracture interactive geodesic active contour algorithm tailored for bone segmentation, which can better capture bone features and perform robustly to the presence of bone fractures and soft tissues. Inspired by orthopedic knowledge, we construct a novel edge-detector function that combines both the intensity and gradient norm of the image, which guides the contour towards bone edges without being obstructed by other soft tissues and therefore reduces mis-segmentation. Furthermore, distance information, where fracture prompts can be embedded, is introduced into the contour evolution as an adaptive step size to stabilize the evolution and help the contour stop at bone edges and fractures. This embedding provides a way to interact with bone fractures and improves the accuracy in the fracture regions. Experiments in pelvic and ankle segmentation demonstrate the effectiveness on addressing the aforementioned problems and show an accurate, stable and consistent performance, indicating a broader application in other bone anatomies. Our algorithm also provides insights into combining the domain knowledge and deep neural networks.
Publication:
PATTERN RECOGNITION
http://dx.doi.org/10.1016/j.patcog.2026.113049
Author:
Liheng Wang
SKLMS, ICMSEC, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, 100190, China
University of Chinese Academy of Sciences, Beijing, 100190, China
Licheng Zhang
Department of Orthopedics, The Fourth Medical Center of Chinese PLA General Hospital, Beijing, 100048, China
National Clinical Research Center for Orthopedics, Sports Medicine and Rehabilitation, Beijing, 100048, China
Hailin Xu
Department of Trauma and Orthopedics, People’s Hospital Peking University, Beijing, 100044, China
Jingxin Zhao
Department of Orthopedics, The Fourth Medical Center of Chinese PLA General Hospital, Beijing, 100048, China
National Clinical Research Center for Orthopedics, Sports Medicine and Rehabilitation, Beijing, 100048, China
Xiuyun Su
Department of Orthopedics, The Fourth Medical Center of Chinese PLA General Hospital, Beijing, 100048, China
National Clinical Research Center for Orthopedics, Sports Medicine and Rehabilitation, Beijing, 100048, China
Jiantao Li
Department of Orthopedics, The Fourth Medical Center of Chinese PLA General Hospital, Beijing, 100048, China
National Clinical Research Center for Orthopedics, Sports Medicine and Rehabilitation, Beijing, 100048, China
Miutian Tang
Department of Trauma and Orthopedics, People’s Hospital Peking University, Beijing, 100044, China
Weilu Gao
Department of Orthopedics, The Fourth Medical Center of Chinese PLA General Hospital, Beijing, 100048, China
National Clinical Research Center for Orthopedics, Sports Medicine and Rehabilitation, Beijing, 100048, China
Chong Chen
SKLMS, ICMSEC, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, 100190, China
Corresponding author.
Email address: chench@lsec.cc.ac.cn
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