Quantitative and qualitative assessment of the regenerative potential of osteoblasts versus bone marrow derived mesenchymal stem cells in the reconstruction of critical sized segmental tibial bone defects in a large animal model

This thesis is about the use of different cells for bone tissue engineering. The cells were used in combination with a novel biomaterial in a large tibial bone defects in a sheep model. Furthermore this study developed a novel cell delivery procedure for bone tissue engineering. This novel procedure of cell delivery could overcome the current problems of cell-based tissue engineering and serve as a baseline for the translation of novel concepts into clinical application.

An integrated approach for precise road reconstruction from aerial imagery and LiDAR data

Accurate and detailed road models play an important role in a number of geospatial applications, such as infrastructure planning, traffic monitoring, and driver assistance systems. In this thesis, an integrated approach for the automatic extraction of precise road features from high resolution aerial images and LiDAR point clouds is presented. A framework of road information modeling has been proposed, for rural and urban scenarios respectively, and an integrated system has been developed to deal with road feature extraction using image and LiDAR analysis. For road extraction in rural regions, a hierarchical image analysis is first performed to maximize the exploitation of road characteristics in different resolutions. The rough locations and directions of roads are provided by the road centerlines detected in low resolution images, both of which can be further employed to facilitate the road information generation in high resolution images. The histogram thresholding method is then chosen to classify road details in high resolution images, where color space transformation is used for data preparation. After the road surface detection, anisotropic Gaussian and Gabor filters are employed to enhance road pavement markings while constraining other ground objects, such as vegetation and houses. Afterwards, pavement markings are obtained from the filtered image using the Otsu's clustering method. The final road model is generated by superimposing the lane markings on the road surfaces, where the digital terrain model (DTM) produced by LiDAR data can also be combined to obtain the 3D road model. As the extraction of roads in urban areas is greatly affected by buildings, shadows, vehicles, and parking lots, we combine high resolution aerial images and dense LiDAR data to fully exploit the precise spectral and horizontal spatial resolution of aerial images and the accurate vertical information provided by airborne LiDAR. Objectoriented image analysis methods are employed to process the feature classiffcation and road detection in aerial images. In this process, we first utilize an adaptive mean shift (MS) segmentation algorithm to segment the original images into meaningful object-oriented clusters. Then the support vector machine (SVM) algorithm is further applied on the MS segmented image to extract road objects. Road surface detected in LiDAR intensity images is taken as a mask to remove the effects of shadows and trees. In addition, normalized DSM (nDSM) obtained from LiDAR is employed to filter out other above-ground objects, such as buildings and vehicles. The proposed road extraction approaches are tested using rural and urban datasets respectively. The rural road extraction method is performed using pan-sharpened aerial images of the Bruce Highway, Gympie, Queensland. The road extraction algorithm for urban regions is tested using the datasets of Bundaberg, which combine aerial imagery and LiDAR data. Quantitative evaluation of the extracted road information for both datasets has been carried out. The experiments and the evaluation results using Gympie datasets show that more than 96% of the road surfaces and over 90% of the lane markings are accurately reconstructed, and the false alarm rates for road surfaces and lane markings are below 3% and 2% respectively. For the urban test sites of Bundaberg, more than 93% of the road surface is correctly reconstructed, and the mis-detection rate is below 10%.

Bone tissue engineering : reconstruction of critical sized segmental bone defects in the ovine tibia

Well-established therapies for bone defects are restricted to bone grafts which face significant disadvantages (limited availability, donor site morbidity, insufficient integration). Therefore, the objective was to develop an alternative approach investigating the regenerative potential of medical grade polycaprolactone-tricalcium phosphate (mPCL-TCP) and silk-hydroxyapatite (silk-HA) scaffolds. Critical sized ovine tibial defects were created and stabilized. Defects were left untreated, reconstructed with autologous bone grafts (ABG) and mPCL-TCP or silk-HA scaffolds. Animals were observed for 12 weeks. X-ray analysis, torsion testing and quantitative computed tomography (CT) analyses were performed. Radiological analysis confirmed the critical nature of the defects. Full defect bridging occurred in the autograft and partial bridging in the mPCL-TCP group. Only little bone formation was observed with silk-HA scaffolds. Biomechanical testing revealed a higher torsional moment/stiffness (p < 0.05) and CT analysis a significantly higher amount of bone formation for the ABG group when compared to the silk-HA group. No significant difference was determined between the ABG and mPCL-TCP groups. The results of this study suggest that mPCL-TCP scaffolds combined can serve as an alternative to autologous bone grafting in long bone defect regeneration. The combination of mPCL-TCP with osteogenic cells or growth factors represents an attractive means to further enhance bone formation.

Modeling kinect sensor noise for improved 3D reconstruction and tracking

We contribute an empirically derived noise model for the Kinect sensor. We systematically measure both lateral and axial noise distributions, as a function of both distance and angle of the Kinect to an observed surface. The derived noise model can be used to filter Kinect depth maps for a variety of applications. Our second contribution applies our derived noise model to the KinectFusion system to extend filtering, volumetric fusion, and pose estimation within the pipeline. Qualitative results show our method allows reconstruction of finer details and the ability to reconstruct smaller objects and thinner surfaces. Quantitative results also show our method improves pose estimation accuracy. © 2012 IEEE.

Quantitative electroencephalographic comodulation : an investigation of patterns in chronic fatigue syndrome

Introduction. This is a pilot study of quantitative electro-encephalographic (QEEG) comodulation analysis, which is used to assist in identifying regional brain differences in those people suffering from chronic fatigue syndrome (CFS) compared to a normative database. The QEEG comodulation analysis examines spatial-temporal cross-correlation of spectral estimates in the resting dominant frequency band. A pattern shown by Sterman and Kaiser (2001) and referred to as the anterior posterior dissociation (APD) discloses a significant reduction in shared functional modulation between frontal and centro-parietal areas of the cortex. This research attempts to examine whether this pattern is evident in CFS. Method. Eleven adult participants, diagnosed by a physician as having CFS, were involved in QEEG data collection. Nineteen-channel cap recordings were made in five conditions: eyes-closed baseline, eyes-open, reading task one, math computations task two, and a second eyes-closed baseline. Results. Four of the 11 participants showed an anterior posterior dissociation pattern for the eyes-closed resting dominant frequency. However, seven of the 11 participants did not show this pattern. Examination of the mean 8-12 Hz amplitudes across three cortical regions (frontal, central and parietal) indicated a trend of higher overall alpha levels in the parietal region in CFS patients who showed the APD pattern compared to those who did not have this pattern. All patients showing the pattern were free of medication, while 71% of those absent of the pattern were using antidepressant medications. Conclusions. Although the sample is small, it is suggested that this method of evaluating the disorder holds promise. The fact that this pattern was not consistently represented in the CFS sample could be explained by the possibility of subtypes of CFS, or perhaps co-morbid conditions. Further, the use of antidepressant medications may mask the pattern by altering the temporal characteristics of the EEG. The results of this pilot study indicate that further research is warranted to verify that the pattern holds across the wider population of CFS sufferers.

Towards automatic tree crown detection and delineation in spectral feature space using PCNN and morphological reconstruction

The application of object-based approaches to the problem of extracting vegetation information from images requires accurate delineation of individual tree crowns. This paper presents an automated method for individual tree crown detection and delineation by applying a simplified PCNN model in spectral feature space followed by post-processing using morphological reconstruction. The algorithm was tested on high resolution multi-spectral aerial images and the results are compared with two existing image segmentation algorithms. The results demonstrate that our algorithm outperforms the other two solutions with the average accuracy of 81.8%.

Prevalence and occurrence of zoonotic bacterial pathogens in surface waters determined by quantitative PCR

The prevalence and concentrations of Campylobacter jejuni, Salmonella spp. and enterohaemorrhagic E. coli (EHEC) were investigated in surface waters in Brisbane, Australia using quantitative PCR (qPCR) based methodologies. Water samples were collected from Brisbane City Botanic Gardens (CBG) Pond, and two urban tidal creeks (i.e., Oxley Creek and Blunder Creek). Of the 32 water samples collected, 8 (25%), 1 (3%), 9 (28%), 14 (44%), and 15 (47%) were positive for C. jejuni mapA, Salmonella invA, EHEC O157 LPS, EHEC VT1, and EHEC VT2 genes, respectively. The presence/absence of the potential pathogens did not correlate with either E. coli or enterococci concentrations as determined by binary logistic regression. In conclusion, the high prevalence, and concentrations of potential zoonotic pathogens along with the concentrations of one or more fecal indicators in surface water samples indicate a poor level of microbial quality of surface water, and could represent a significant health risk to users. The results from the current study would provide valuable information to the water quality managers in terms of minimizing the risk from pathogens in surface waters.

Fast reconstruction of aerodynamic shapes using evolutionary algorithms and virtual Nash strategies in a CFD design environment

This paper compares the performances of two different optimisation techniques for solving inverse problems; the first one deals with the Hierarchical Asynchronous Parallel Evolutionary Algorithms software (HAPEA) and the second is implemented with a game strategy named Nash-EA. The HAPEA software is based on a hierarchical topology and asynchronous parallel computation. The Nash-EA methodology is introduced as a distributed virtual game and consists of splitting the wing design variables - aerofoil sections - supervised by players optimising their own strategy. The HAPEA and Nash-EA software methodologies are applied to a single objective aerodynamic ONERA M6 wing reconstruction. Numerical results from the two approaches are compared in terms of the quality of model and computational expense and demonstrate the superiority of the distributed Nash-EA methodology in a parallel environment for a similar design quality.