Enhancement of bone shadow region using local phase-based ultrasound transmission maps

Ultrasound is increasingly being employed in different orthopedic procedures as an imaging modality for real-time guidance. Nevertheless, low signal-to-noise-ratio and different imaging artifacts continue to hamper the success of ultrasound-based procedures. Bone shadow region is an important feature indicating the presence of bone/tissue interface in the acquired ultrasound data. Enhancement and automatic detection of this region could improve the sensitivity of ultrasound for imaging bone and result in improved guidance for various orthopedic procedures.

In this work, a method is introduced for the enhancement of bone shadow regions from B-mode ultrasound data. The method is based on the combination of three different image phase features: local phase tensor, local weighted mean phase angle, and local phase energy. The combined local phase image features are used as an input to an [Formula: see text] norm-based contextual regularization method which emphasizes uncertainty in the shadow regions. The enhanced bone shadow images are automatically segmented and compared against expert segmentation.

Qualitative and quantitative validation was performed on 100 in vivo US scans obtained from five subjects by scanning femur and vertebrae bones. Validation against expert segmentation achieved a mean dice similarity coefficient of 0.88.

The encouraging results obtained in this initial study suggest that the proposed method is promising enough for further evaluation. The calculated bone shadow maps could be incorporated into different ultrasound bone segmentation and registration approaches as an additional feature.