Robust bone detection in ultrasound using combined strain imaging and envelope signal power detection.

Bone localization in ultrasound (US) remains challenging despite encouraging advances. Current methods, e.g. local image phase-based feature analysis, showed promising results but remain reliant on delicate parameter selection processes and prone to errors at confounding soft tissue interfaces of similar appearance to bone interfaces. We propose a different approach combining US strain imaging and envelope power detection at each radio-frequency (RF) sample. After initial estimation of strain and envelope power maps, we modify their dynamic ranges into a modified strain map (MSM) and a modified envelope map (MEM) that we subsequently fuse into a single combined map that we show corresponds robustly to actual bone boundaries. Our quantitative results demonstrate a marked reduction in false positive responses at soft tissue interfaces and an increase in bone delineation accuracy. Comparisons to the state-of-the-art on a finite-element-modelling (FEM) phantom and fiducial-based experimental phantom show an average improvement in mean absolute error (MAE) between actual and estimated bone boundaries of 32% and 14%, respectively. We also demonstrate an average reduction in false bone responses of 87% and 56%, respectively. Finally, we qualitatively validate on clinical in vivo data of the human radius and ulna bones, and demonstrate similar improvements to those observed on phantoms.