Robust Bone Detection in Ultrasound Using Combined Strain Imaging and Envelope Signal Power Detection

Abstract

Abstract. Bone localization in ultrasound (US) remains challenging despite encouraging advances. Current methods, e.g. local image phasebased 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.

Delineating Bone Surfaces in B-Mode Images Constrained by Physics of Ultrasound Propagation

“…Although there are US radiofrequncy (RF) raw data based bone localization techniques, e.g. [11], [12], RF data access is not commonly available in commercial US systems, let alone its realtime streaming. Therefore, most techniques in the literature utilize commonly available beamformed, demodulated, and dynamic-range adjusted brightness (B)-mode images.…”

Spine surface detection from local phase‐symmetry enhanced ridges in ultrasound images

“…Hacihaliloglu et al and Hacihaliloglu et al used a Log‐Gabor filter based phase‐symmetry measure to produce a strong response on the bone surface. The automated parameter estimation technique for Log‐Gabor filters attempts to suppress nonbone responses elsewhere in the B‐mode image but is prone to false‐positive bone responses at soft‐tissue interfaces that have similar intensity profiles as the bone surface …”

“…The automated parameter estimation technique for Log-Gabor filters attempts to suppress nonbone responses elsewhere in the B-mode image but is prone to false-positive bone responses at soft-tissue interfaces that have similar intensity profiles as the bone surface. [22][23][24] Little attention has been paid to spine surface segmentation in US images especially those obtained in the transverse plane. Khallaghi et al, 25 Behnami et al, 26 Rasoulian et al, 27 and Nagpal et al 28 have incorporated statistical shape, pose, and scale priors obtained from segmented vertebral CT slices co-registered with spinal US images.…”

“…Elastography has been suggested as a potential aid to ultrasonography for bone surface localization due to the high mechanical contrast between bones and surrounding soft tissue, but it has not been investigated for spinal applications yet. Strain patterns in proximity of spines may be affected by the complexity of the spine geometry as well as adjoining soft tissues, erector spinae muscles and ligaments conjoined with the laminae, and transverse and articular processes that lie deeper down the skin surface.…”