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Towards a novel minimally invasive three dimensional ultrasound imaging based computer assisted orthopaedic surgery system for bone fracture reduction

University of British Columbia

Current practice in orthopaedic surgery relies on intra-operative two dimensional (2D) fluoroscopy as the main imaging modality for localization and visualization of bone tissue, fractures, implants, and surgical tool positions. However, with such projection imaging, surgeons typically face considerable difficulties in accurately localizing bone fragments in three dimensional (3D) space and assessing the adequacy and accuracy of reduced fractures. Furthermore, fluoroscopy involves significant radiation exposure. Ultrasound (US) has recently emerged as a potential non-ionizing imaging alternative that promises safer operation while remaining relatively cheap and widely available. US image data, however, is typically characterized by high levels of speckle noise, reverberation, anisotropy and signal dropout which introduce significant difficulties in interpretation of captured data, automatic detection and segmentation of image features and accurate localization of imaged bone surfaces. In this thesis we propose a novel technique for automatic bone surface and surgical tool localization in US that employs local phase image information to derive symmetry-based features corresponding to tissue/bone or tissue/surgical tool interfaces through the use of 2D Log-Gabor filters. We extend the proposed method to 3D in order to take advantage of correlations between adjacent images. We validate the performance of the proposed approach quantitatively using realistic phantom and in-vitro experiments as well as qualitatively on in-vivo and ex-vivo data. Furthermore, we evaluate the ability of the proposed method in detecting gaps between fractured bone fragments. The current study is therefore the first to show that bone surfaces, surgical tools and fractures can be accurately localized using local phase features computed directly from 3D ultrasound image volumes. Log-Gabor filters have a strong dependence on the chosen filter parameters, the values of which significantly affect the outcome of the features being extracted. We present a novel method for contextual parameter selection that is autonomously adaptive to image content. Finally, we investigate the hypothesis that 3D US can be used to detect fractures reliably in the emergency room with three clinical studies. We believe that the results presented in this work will be invaluable for all future imaging studies with US in orthopaedics.

Text

2010-05-06

Attribution-NonCommercial-NoDerivatives 4.0 International

http://hdl.handle.net/2429/24463

Electrical and Computer Engineering

University of British Columbia

UBCV

http://creativecommons.org/licenses/by-nc-nd/4.0/