Pelvic bone tumor segmentation fusion algorithm based on fully convolutional neural network and conditional random field

Pelvic bone tumor segmentation fusion algorithm based on fully convolutional neural network and conditional random field

Background and objective: Pelvic bone tumors represent a harmful orthopedic condition, encompassing both benign and malignant forms. Addressing the issue of limited accuracy in current machine learning algorithms for bone tumor image segmentation, we have developed an enhanced bone tumor image segme...

Full description

Bibliographic Details
Main Authors: Shiqiang Wu, Zhanlong Ke, Liquan Cai, Liangming Wang, XiaoLu Zhang, Qingfeng Ke, Yuguang Ye
Format: Article
Language:English
Published: Elsevier 2024-04-01
Series:Journal of Bone Oncology
Subjects:
Pelvis bone tumor
Image segmentation
Fully convolutional neural network
Conditional random fields
Computed tomography
Online Access:http://www.sciencedirect.com/science/article/pii/S2212137424000733

Internet

http://www.sciencedirect.com/science/article/pii/S2212137424000733

Similar Items