Tracking of an object in six degrees-of-freedom (DOF) produces a position and orientation estimate of the object as it moves in 3D space. This thesis investigates the design and implementation of a prototype optical 6 DOF tracking system. Although optical scanners potentially have issues regarding occlusion they have advantages over electromagnetic scanners in that they can be used without distortion near ferromagnetic materials and can have large working volumes. This thesis focuses on the design of a small camera module named the ‘Black Spot’ that forms part of the overall tracking system. This module is capable of tracking the locations of up to 27 LED markers at 60 frames/s as the module moves in space. These markers provide fixed reference points that are utilised by the tracking system. A number of these modules will, in future revisions of the system, be clustered closely together forming a tracking hub. In this research this hub has been partially implemented in software on a PC. This software implements a ‘pose estimation’ algorithm that iteratively refines the location and position of the camera modules. Results from testing three Black Spot modules indicates that the locations of the LED markers can be determined very precisely using a centroid calculation. Standard deviations of better than 0.01 pixels have been recorded using these modules. The pose estimation algorithm has been tested revealing the need for a better minimisation algorithm. It is recommended that a bundle adjustment algorithm is used in the future to refine the world model used by the hub. The calibration of the system is a task for future research.

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The thesis looks at various aspects of the modulation transfer function (MTF) and Wiener spectrum (WS) measurements for screen-film systems aiming at robust and simple methods for their routine measurement in a hospital setting. To measure the MTF of the film-screen systems, the square wave response function method was used. To normalise the MTF at a lower spatial frequency, a lead step and an object were incorporated into the measurement. Work on fitting the MTF data was carried out by considering two MTF models. To check if the current MTF calculation makes a low estimate, calculation using more terms in the Coltmann equation was performed. The value of the edge spread function method to measure the MTF was examined. The MTF of the microdensitometer was measured, and the correction factor for the screen-film. MTF based on this was calculated. MTF measurements of several screen-film combinations in use at the Aberdeen Royal Infirmary were made. The method used for the measurement of the WS of the screen-film was the fast Fourier transform digital method. A proper normalisation was chosen and implemented in the calculation. Low pass filtering, low frequency filtering, and windowing of the density fluctuation data were examined using sinusoidal and real noise data. The square shape of the scanning aperture of the microdensitomer was taken into account in the determination of WS. Slit length was synthesised and incorporated into the WS calculation. WS measurements of several screen-film combinations were made. A short receiver operating characteristic (ROC) study of two screen-film systems, recently introduced into Aberdeen Royal Infirmary, was undertaken to study the relationship between the physical measures of image quality that had been developed and the subjective measure based on the area under the ROC curve.

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This research focuses on providing a fast and space efficient compression method to answer information queries on spectroscopic data. Our primary hypothesis was whether a conversion from decimal data to character/integer space could be done in a manner that enables use of succinct structures and provides good compression. This compression algorithm is motivated to handle queries on spectroscopic data that approaches limits of main computer memory. The primary hypothesis is supported in that the new compression method can save 79.20% - 94.07% computer space on the average. The average of maximum error rates is also acceptable, being 0.05% - 1.36% depending on the subject that the data was collected from. Additionally, the data’s compression rate and entropy are negatively correlated; while compression rate and maximum error were positively correlated when the max error rates were performed on a natural logarithm transformation. The effects of different types of data sources on compression rate have been studied as well. Fungus datasets achieved highest compression rates, while mouse brain datasets obtained the lowest compression rates among four types of data sources. Finally, the effect of the studied compression algorithm and method on integrating spectral bands has been investigated in this study. The spectral integration for determining lipid, CH2 and dense core plaque obtained good image quality and the errors can be considered inconsequential except the case of determining creatine deposits. Despite the fact that creatine deposits are still recognizable in the reconstructed image, the image quality was reduced.

The subject of digital image analysis deals with extracting relevant information from image data, stored in digital form in a computer. A fundamental problem in image analysis is image segmentation, i.e., the identification and separation of relevant objects and structures in an image. Accurate segmentation of objects of interest is often required before further processing and analysis can be performed. Despite years of active research, fully automatic segmentation of arbitrary images remains an unsolved problem. Interactive, or semi-automatic, segmentation methods use human expert knowledge as additional input, thereby making the segmentation problem more tractable. The goal of interactive segmentation methods is to minimize the required user interaction time, while maintaining tight user control to guarantee the correctness of the results. Methods for interactive segmentation typically operate under one of two paradigms for user guidance: (1) Specification of pieces of the boundary of the desired object(s). (2) Specification of correct segmentation labels for a small subset of the image elements. These types of user input are referred to as boundary constraints and regional constraints, respectively. This thesis concerns the development of methods for interactive segmentation, using a graph-theoretic approach. We view an image as an edge weighted graph, whose vertex set is the set of image elements, and whose edges are given by an adjacency relation among the image elements. Due to its discrete nature and mathematical simplicity, this graph based image representation lends itself well to the development of efficient, and provably correct, methods. The contributions in this thesis may be summarized as follows: Existing graph-based methods for interactive segmentation are modified to improve their performance on images with noisy or missing data, while maintaining a low computational cost. Fuzzy techniques are utilized to obtain segmentations from which feature measurements can be made with increased precision. A new paradigm for user guidance, that unifies and generalizes regional and boundary constraints, is proposed. The practical utility of the proposed methods is illustrated with examples from the medical field.