Joint kinematics has been suggested to play an important role in the initiation and progression of a number of musculoskeletal pathologies. Thus, investigation of joint kinematics can help clinicians and researchers to better understand musculoskeletal conditions such as osteoarthritis and trochanteric bursitis. Existing motion capture technologies used in clinical settings suffer from various limitations, including soft tissue artefact. These limitations result in a lengthy examination process, an incomplete movement description, or an inaccurate representation of the real bony landmarks. The recent introduction of a motion analysis with ultrasound (MAUS) system aimed to provide a less constrained approach to detect actual bony structures and describe joint kinematics in three dimensional (3D) space. However, the accuracy of the original MAUS system was highly dependent on the operator's experience. In this doctoral thesis, a computer-aided tracking and motion analysis with ultrasound (CAT & MAUS) system is developed to track underlying bony landmarks and describe hip joint kinematics during gait. The key contribution of this thesis is to combine state-of-the-art computer vision approaches with the original MAUS system to improve the speed, accuracy and repeatability of joint kinematics examination for clinical measurement and diagnosis. Firstly, a comprehensive review of gait analysis and relevant clinical diagnostic modalities is presented. Then, an augmented MAUS system architecture is presented, which is more flexible than the previous MAUS system of the data acquisition. It combines an optoelectronic motion analysis (MA) system with a 2D ultrasound (US) device to build up a 3D representation of the bony structure of interest. A novel calibration box with multiple functions for the augmented MAUS system is designed to spatially and temporally match US images to the motion analysis data. The average Euclidean distance error of the spatial calibration is found to be 0.34 mm and the accuracy of the temporal calibration is found to be within half of the frame acquisition interval. The augmented MAUS system with its more accurate calibration procedures can accurately present the bone of interest in 3D space. Secondly, a computer-aided post-processing pipeline is presented to automatically track the bone of interest in 3D space. A globally optimal registration method is employed to align the 3D surfaces of the target bony structure reconstructed from the manual segmentation in US images at different positions to locate the target bony landmark from one position to another. The globally optimal registration overcomes the issue of getting trapped into local minima for the conventional iterative closest point registration. The accuracy of the globally optimal registration is validated with a proximal femur phantom. The average rotation error is found to be 0.38° and the average translation error is found to be 0.33 mm, both of which are within the clinical tolerance of computer-aided orthopaedics surgery ±3° and ± 1 mm). The 3D globally optimal registration guarantees an accurate track of the same target bony structure at different positions instead of estimating the similar bony structure at each position by eyeball with previous MAUS system. However, in practice, it takes around 20 minutes to manually segment the bone structure for a single surface reconstruction, which is extremely laborious and time consuming. In order to automate the CAT & MAUS system, a novel automatic segmentation of the bone structure in a 2D US image is then developed as a precursor for an accurate globally optimal registration. The automatic bone segmentation introduces the local phase features and acoustic characteristics to enhance the bone probability for detection. The result of the automatic segmentation is validated with a pilot phantom study before applying to the in-vivo experiment and achieves an accuracy of 0.13 mm. After fully developing the CAT & MAUS system, hip joint kinematics of healthy subjects are quantified in six degrees of freedom using the CAT & MAUS system and compared to the results from the optoelectronic motion analysis system. It is shown that CAT & MAUS results describe a greater rotation range than MA results by up to 4.03° in the sagittal plane because the optoelectronic motion analysis system alone suffers from severe soft tissue artefact as the skin markers shift away from the underlying bony structures during movement. The deformation of body segments captured by MA during movements caused by soft tissue artefact is explained using Procrustes analysis to indicate the accuracy and repeatability of the CAT & MAUS system. Finally, possible future directions are proposed based on preliminary investigations using the developed CAT & MAUS system with particular reference to both the technical and clinical perspectives.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:724911 |
| Date | January 2016 |
| Creators | Jia, Rui |
| Contributors | Noble, Julia Alison ; Mellon, Stephen |
| Publisher | University of Oxford |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | https://ora.ox.ac.uk/objects/uuid:7253392b-fed1-497b-91e1-9ae72555b348 |
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