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The development of active 'smart materials', which are materials that can change their physical properties when subject to an external stimulus such as a thermal, mechanical or magnetic energy, are expected to significantly enhance technology developments in future years. These new materials can be integrated into existing technologies to increase efficiency, performance, durability and size reduction.

Knee replacement surgery is a common orthopaedic procedure that greatly benefits from a three-dimensional geometric representation of a patient's knee bone obtained from MR or CT data. The use of these image modalities pose the following challenges: (i) high imaging cost; (ii) long wait times; (iii) limited availability and (iv) in the latter, large exposure to ionizing radiation. Traditional approaches based on planar X-ray radiography are significantly less prone to these issues; however, they only provide two-dimensional information. This work presents a proof of concept study for generating patient-specific femoral bone shapes from a statistical shape atlas using anatomical features acquired from calibrated X-ray radiographs. Our hypothesis was: three-dimensional geometry can be reconstructed, within 2 millimeters RMS, by identifying features on two calibrated radiographs. We illustrate the feasibility of our approach with regards to acquiring features and the viability of reconstructing patient-specific bony anatomy. A set of reliable and relevant features is identified for which an acquisition protocol and user-interface was devised to minimize inter-observer variability. Both the data and methods used to construct the atlas are discussed as well generating shapes from features. The reconstructions accuracy was comparable to, albeit lower than, competing approaches that rely on two-dimensional bony contours. / Thesis (Master, Computing) -- Queen's University, 2014-04-29 21:53:10.809

Patients with severe back deformities can greatly benefit from customized medical seating. Customized medical seating is made by taking measurements of each individual patient and making the seat as per these measurements. The current measuring systems employed by the industry are limited to use in clinics which are generally located only in major population centres. Patients living in remote areas are severely affected by this as the clinics could be far away and inaccessible for these patients. To provide service of customized medical seating requires a new measurement system which is portable so that the system could be transported to the patients in remote areas. The requirements for a new measurement system are analysed to suite the needs of Equipment Technology Services of the Cerebral Palsy League of Queensland. Design for a new measurement system was conceptualised by reviewing systems and technologies in various scientific disciplines. Design for a new system was finalised by optimizing each individual component. The final approach was validated by measuring difficult models and repeating the process to check for process variances. This system has now been adopted for clinical evaluation by ETS Suggestions have been made for further improvements in this new measurement approach.

Thesis (Ph.D.)--University of Central Florida, 2007. / Adviser: Raj Vaidyanathan. Includes bibliographical references (p. 115-120). Also available in print.

Thesis (M.S.V.)--University of Toledo, 2004. / Typescript. "A thesis [submitted] as partial fulfillment of the requirements of the Master of Science degree in Civil Engineering." Includes bibliographical references (leaves 63-64).

This thesis presents a method of object classification using the idea of deformable shape matching. Three types of visual features, geometric blur, C1 and SIFT, are used to generate feature descriptors. These feature descriptors are then used to find point correspondences between pairs of images. Various morphable models are created by small subsets of these correspondences using thin-plate spline. Given these morphs, a simple algorithm, least median of squares (LMEDS), is used to find the best morph. A scoring metric, using both LMEDS and distance transform, is used to classify test images based on a nearest neighbor algorithm. We perform the experiments on the Caltech 101 dataset [5]. To ease computation, for each test image, a shortlist is created containing 10 of the most likely candidates. We were unable to duplicate the performance of [1] in the shortlist stage because we did not use hand-segmentation to extract objects for our training images. However, our gain from the shortlist to correspondence stage is comparable to theirs. In our experiments, we improved from 21% to 28% (gain of 33%), while [1] improved from 41% to 48% (gain of 17%). We find that using a non-shape based approach, C2 [14], the overall classification rate of 33.61% is higher than all of the shaped based methods tested in our experiments.

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In the last twenty years Reversible Shape-Memory (RSM) alloys have become the source of considerable technological interest as a result of their ability to generate spontaneous and reversible changes of shape on thermal cycling. This has led to the development of a range of reversible shape-memory devices for thermostatic sensing applications. In these devices the alloy is subjected to several thousand shape-memory cycles and the stability of the reversible shape-memory is therefore an important alloy property. Data on the effect of shape-memory cycling on the long-term stability of the reversible shape-memory, however, is extremely limited. The present work, conducted to fill this gap, has shown that there is an inherent instability in the reversible shape-memory, with changes in the operating temperatures and cumulative reductions in the maximum shape-strain output of actuators on long-term thermal cycling under conditions simulating real devices. Extensive investigation has shown that these instabilities result from a number of sources, ageing of the shape-memory martensites and most importantly from morphological disruptions in the "trained" martensites caused by two-stage stress-induced transformation and due to the build-up of transformation-induced dislocation debris. This shape-strain degradation has also been successfully modelled by means of a simple two-stage stress-induced martensitic transformation model.

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