Fast and robust femur segmentation from computed tomography images for patient-specific hip fracture risk screening. Issue 2 (4th March 2023) - Bjornsson, Pall Asgeir; Baker, Alexander; Fleps, Ingmar; Pauchard, Yves; Palsson, Halldor; Ferguson, Stephen J.; Sigurdsson, Sigurdur; Gudnason, Vilmundur; Helgason, Benedikt; Ellingsen, Lotta Maria
ABSTRACT: Osteoporosis is a common bone disease that increases the risk of bone fracture. Hip-fracture risk screening methods based on ﬂnite 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.