A challenging problem in ultrasound based orthopaedic surgery is the identification and interpretation of bone surfaces. Recently we have proposed a new fully automatic ultrasound bone surface enhancement filter in the context of spine interventions. The method is based on the use of a Gradient Energy Tensor filter to construct a new feature enhancement metric, which we call the Local Phase Tensor.

The goal of this study is to provide further improvements to the proposed filtering method by incorporating a-priori knowledge about the physics of ultrasound imaging and salient grouping of enhanced bone features.

Typical ultrasound scan of the spine, there is a large soft tissue interface present close to the transducer surface with high intensity values similar to those of the bone anatomy response. Typical ultrasound image segmentation or enhancement methods will be affected by this thick soft tissue response. In order to weaken this soft tissue interface we calculate a new transmission map where features deeper in the ultrasound image have higher transmission values and shallow features have lower transmission values. The calculation of this new US transmission/attenuation map allows the proposed image enhancement method to mask out erroneous regions, such as the soft tissue interface, and improve the accuracy and robustness of the spine surface enhancement. The masked US images were used as an input to the LPT image enhancement method. In order to provide a more compact spine surface representation and further reduce the typical US imaging artifacts and soft tissue interfaces we calculate saliency Local Phase Tensor features. The saliency images are computed using Difference of Gaussian filters.

Qualitative results, obtained from in vivo clinical scans, show a strong correspondence between enhanced features and the actual bone surfaces present in the ultrasound scans. Future work will include the extension of the proposed method to 3D and validation of the method in the context of intra-operative ultrasound image registration in CAOS applications.

Percutaneous fixation of scaphoid fractures has become popular in recent years, mainly due to its reduced complexity compared to open surgical approaches. Fluoroscopy is currently used as guidance for this percutaneous approach, however, as a projective imaging modality, it provides only a 2D view of the complex 3D anatomy of the wrist during surgery, and exposes both patient and physician to harmful X-ray radiation. To avoid these drawbacks, 3D ultrasound has been suggested to provide imaging for guidance as a widely available, real-time, radiation-free and low-cost modality. However, the blurred, disconnected, weak and noisy bone responses render interpretation of the US data difficult so far. In this work, we present the integration of 3D ultrasound with a statistical wrist model to allow development of an improved ultrasound-based guidance procedure. For enhancement of bone responses in ultrasound, a phase symmetry based approach is used to exploit the symmetry of the ultrasound signal around the expected bone location. We propose an improved estimation of the local phase symmetry by using the local spectrum variation of the ultrasound image. The statistical wrist model is developed through a group-wise registration based framework in order to capture the major modes of shape and pose variations across 30 subjects at different wrist positions. Finally, the statistical wrist model is registered to the enhanced ultrasound bone surfaces using a probabilistic registration approach. Feasibility experiments are performed using two volunteer wrists, and the results are promising and warrant further development and validation to enable ultrasound guided percutaneous scaphoid fracture reduction.