This record has been edited as far as possible, missing data will be added when the version of record is issued.
Fast and robust femur segmentation from computed tomography images for patient-specific hip fracture risk screening
- Journal Article
Osteoporosis is a common bone disease that increases the risk of bone fracture. Hip-fracture risk screening methods based on finite element analysis depend on segmented computed tomography (CT) images; however, current femur segmentation methods require manual delineations of large data sets. Here we propose a deep neural network for fully automated, accurate, and fast segmentation of the proximal femur from CT. Evaluation on a set of 1147 proximal femurs with ground truth segmentations demonstrates that our method is apt for hip-fracture risk screening, bringing us one step closer to a clinically viable option for screening at-risk patients for hip-fracture susceptibility. Show more
Journal / seriesComputer Methods in Biomechanics and Biomedical Engineering
PublisherTaylor & Francis
SubjectComputed tomography; femur; segmentation; convolutional neural networks; osteoporosis
MoreShow all metadata