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.

Introduction

Bony deformities in the hip that cause femoroacetabular impingement (FAI) can be resected in order to delay the onset of osteoarthritis and improve hip range of motion. However, achieving accurate osteoplasty arthroscopically is challenging because the narrow hip joint capsule limits field of view. Recently, image-based navigation using a preoperative plan has been shown to improve the accuracy of femoral bone surfaces following arthroscopic osteoplasty for FAI. The current standard for intraoperative monitoring, 3D x-ray fluoroscopy, is accurate at the initial registration step to within 0.8±0.5mm but involves radiation. Intraoperative 3D ultrasound (US) is a promising radiation-free alternative for providing real-time visual feedback during FAI osteoplasty. The objective was to determine if intraoperative 3D US of the femoral head/neck region can be registered to a CT-based preoperative plan with comparable accuracy to fluoroscopic navigation in order to visualise progress during arthroscopic FAI osteoplasty.

Due to its ease of use, portability, low cost, real-time response and absence of ionising radiation, ultrasound (US) imaging could potentially be an important tool for non-invasive diagnostic imaging in orthopaedics. Unfortunately, nonlinear characteristics of ultrasound, low signal-to-noise ratio and speckle make it difficult to accurately and reliably determine the location and shape of the bone surface. Recently, local phase-based image processing methods, named phase symmetry (PS), have been shown to perform very well at locating bone surfaces in ultrasound images, with reported accuracies of better than 0.4mm. The local phase features are extracted by filtering the B-mode US image in the frequency domain with a Log-Gabor filter. Although successful results were achieved, accurate localization is highly affected by the choice of filter parameters. Recently, our group proposed a method of automatically selecting the scale, bandwidth and orientation parameters of Log-Gabor filters. Previously, we showed our first clinical results using local phase information to identify distal radius fractures from B-mode US images using automatically selected filter parameters.

The objective of the current study was to determine if the proposed automatic parameter selection method could produce accurate pelvic bone surface shapes in a live clinical setting.

CT scans were obtained as part of normal clinical care from ten patients admitted to Vancouver General Hospital for pelvic fractures. A ‘gold standard’ bone surface was computed from the CT scan. After obtaining informed consent, we performed an additional US scan using a commercially-available real-time scanner (Voluson 730, GE Healthcare, Waukesha, WI) with a 3D US transducer. The PS bone surfaces were extracted from the US scans using the empirical Log-Gabor filter parameters and optimised Log-Gabor filter parameters. The bone surfaces on CT were extracted using a standard thresholding approach that minimises the intra-class variance. The US images were then registered to the CT images using a feature-based rigid registration algorithm with manual landmarking. The quality of the resulting surface matching was evaluated by computing the root mean square distance between the two surface representations.

The average fiducial registration error was 0.31mm (SD 0.25mm). The average surface fitting error (SFE) was 0.72mm (SD 1.24 mm) for PS surfaces extracted using empirical filter parameters and 0.41mm (SD 0.44 mm) using the optimized filter parameters.

In this study, we have demonstrated that our automatic filter parameter selection process can be applied successfully to a bone surface extraction task on 3D US images acquired under clinically realistic conditions. The accuracy of the resulting bone surface is excellent, with an average discrepancy relative to a CT standard of well under a millimeter. This level of accuracy is likely to be sufficiently good for a number of important surgical tasks, including CT to US registration.

Purpose

Radiographs are the most common imaging modality used to guide orthopaedic interventions. Ultrasound (US) imaging offers potential advantages for intraoperative imaging by its portability and ability to produce real-time 2D or 3D images without radiation to either the patient or surgical team. Our objective in this study was to determine in a live emergency room setting, if a newly-developed image processing method for 3D US would allow us to accurately extract (reproduce) the surfaces of fractured bones.