<p> In volumetric image analysis and visualization, challenges have be induced by the increasing size of volume over recent years. Rendering and interacting with a volume with reduced size is preferable and highly needed. The primary concern in producing such downsized volumetric images is to preserve the important structures and those of the user's interest, such as boundaries between materials. Typical volume reduction approaches usually perform uniform subsampling without the awareness of user-specified parameters such as the opacity and color transfer functions. However, it is also handy for the algorithm to have "global'' encoding and control over the entire volume, meanwhile revealing some features of the data while it is being downsized. This thesis aims at providing a means of such type, extended from the famous seam carving operator that has been used widely in the task of image and video retargeting. </p><p> Our work applies and extends the seam carving algorithm for videos proposed by Rubinstein et al. to downsize three-dimensional volumetric images. This extended technique computes and removes from the volume two-dimensional seams, or what we name and define as sheets, to reduce the size of the volume with minimum loss of important details measured by gradient. We aim at learning through experimentation the visual quality of seam carved volumetric images, making improvements based on feedback and potentially paving ways towards applications. With the great flexibility of the graph cut formulation, we implement in our algorithm the existing backward and forward energy optimization, and add extensions including isosurface protection and the encoding of the opacity transfer function. </p><p> At the visual level, experimental results tell us when applied alone with fixed parameters, volumetric seam carving outperforms trivial approaches in preserving important structures only for part of the datasets, on which discussions are included at the best knowledge of the author.</p><p>

A pose estimation method is proposed for measuring the position and orientation of a biopsy needle. The technique is to be used as a touchless needle guide system for guidance of percutaneous procedures with 4D ultrasound. A pair of uncalibrated, light-weight USB cameras are used as inputs. A database is prepared offline, using both the needle line estimated from camera-captured images and the true needle line recorded from an independent tracking device. A nonparametric learning algorithm determines the best fit model from the database. This model can then be used in real-time to estimate the true position of the needle with inputs from only the camera images. Simulation results confirm the feasibility of the method and show how a small, accurately made database can provide satisfactory results. In a series of tests with cameras, we achieved an average error of 2.4mm in position and 2.61° in orientation. The system is also extended to real ultrasound imaging, as the two miniature cameras capture images of the needle in air and the ultrasound system captures a volume as the needle moves through the workspace. A new database is created with the estimated 3D position of the needle from the ultrasound volume and the 2D position and orientation of the needle calculated from the camera images. This study achieved an average error of 0.94 mm in position and 3.93° in orientation. / Applied Science, Faculty of / Electrical and Computer Engineering, Department of / Graduate

Inflammation is important in both the pathogenesis and outcome of atherosclerosis. Plaques containing numerous inflammatory cells, particularly macrophages, have a high risk of rupture, whereas those with fewer inflammatory cells are at lower risk. The current ‘gold standard’ technique for imaging atherosclerosis is x-ray contrast angiography, which provides high-resolution definition of the site and severity of luminal stenoses, but no information about plaque inflammation. Quantification of plaque inflammation is desirable both to predict risk of plaque rupture and to monitor the effects of atheroma-modifying therapies. This is important since recent studies strongly suggest that HMG Co-A reductase inhibitors promote plaque stability by decreasing plaque macrophage content and activity without substantially reducing plaque size and therefore angiographic appearance. FDG is a glucose analogue that is taken up by cells in proportion to their metabolic activity. In this work, the central hypothesis was that plaque inflammation could be visualised and quantified non-invasively using FDG-PET. Initially, THP-1 monocytes and buffy-coat macrophages were stimulated with cellular activators, and the effect on deoxyglucose uptake was observed. It was demonstrated that both types of cell accumulated deoxyglucose in proportion to their metabolic activity. Next, FDG uptake was assessed in endarterectomy specimens from patients with symptomatic carotid disease. Autoradiography of excised plaques confirmed accumulation of deoxyglucose in macrophage-rich areas. Subsequently, co-registered FDG-PET imaging was performed in patients with transient ischaemic attack. FDG accumulated within carotid plaques, with significantly more FDG being taken up into symptomatic plaques than contralateral asymptomatic lesions. Finally, a rabbit model of atherosclerosis was established to investigate two related questions: firstly, whether an animal PET scanner (MicroPet) might detect atheroma, and secondly whether FDG-PET could image and perhaps quantify both atheroma progression and regression. Aortic atheroma was identified by FDG-PET, but full quantification was not possible, because the microPet system is currently unable to perform studies with attenuation correction. In summary, it has been shown, both in vitro and in vivo, that inflammation within atherosclerotic plaques can be successfully imaged by FDG-PET. In addition, pilot data from an experimental study of atherosclerosis in rabbits suggested that serial imaging with this technique might be useful for monitoring the effects of anti-atheroma drugs.

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We demonstrate hyperspectral imaging using two time-delayed, coherent extreme ultraviolet (XUV) sources. The approach combines broadband XUV high-harmonic generation, holographic imaging, and Fourier transform spectroscopy. The two harmonics sources are spatially separated at generation,and overlap in the far field resulting in a double slit diffraction pattern. We record the two-dimensional intensity modulation as a function of relative time delay; the Fourier transform determines the spatially dependent spectrum. To reduce the delay jitter and improve the spectral resolution, we demonstrate a novel experimental setup that records the relative delay of the two pulses through optical interference. Moreover, we have demonstrated that this broadband approach can be extended to Fourier transform holographic imaging, which avoids extensive phase retrieval computations. Applications include imaging of biological materials near the carbon K-edge.

The restoration of images degraded by a stochastic, time varying point spread func-tion(PSF) is addressed. The object to be restored is assumed to remain fixed during the observation time. A sequence of observations of the unknown object is assumed available. The true value of the random PSF is not known. However, for each observation a "noisy" measurement of the random PSF at the time of observation is assumed available. Practical applications in which the PSF is time varying include situations in which the images are obtained through a nonhomogeneous medium such as water or the earth's atmosphere. Under such conditions, it is not possible to determine the PSF in advance, so attempts must be made to extract it from the degraded images themselves. A measurement of the PSF may be obtained by either isolating a naturally occurring point object in the scene, such as a reference star in optical astronomy, or by artificially installing an impulse light source in the scene. The noise in the measurements of point spread functions obtained in such a manner are particularly troublesome in cases when the light signals emitted by the point object are not very strong. In this thesis, we formulate a model for this restoration problem with PSF measurement error. A maximum likelihood filter and a Wiener filter are then developed for this model. Restorations are performed on simulated degraded images. Comparisons are made with standard filters of the classical restoration model(ignoring the PSF error), and also with results based on the averaged degraded image and averaged PSF's. Experimental results confirm that the filters we developed perform better than those based on averaging and than those ignoring the PSF measurement error. / Applied Science, Faculty of / Electrical and Computer Engineering, Department of / Graduate

Imaging systems play an important role in many diverse applications. Requirements for these applications, however, can lead to complex or sub-optimal designs. Traditionally, imaging systems are designed to yield a visually pleasing representation, or "pretty picture", of the scene or object. Often this is because a human operator is viewing the acquired image to perform a specific task. With digital computers increasingly being used for automation, a large number of algorithms have been designed to accept as input a pretty picture. This isomorphic representation however is neither necessary nor optimal for tasks such as data compression, transmission, pattern recognition or classification. This disconnect between optical measurement and post processing for the final system outcome has motivated an interest in computational imaging (CI). In a CI system the optical sub-system and post-processing sub-system is jointly designed to optimize system performance for a specific task. In these hybrid imagers, the measured image may no longer be a pretty picture but rather an intermediate non-traditional measurement. In this work, applications of non-traditional measurements are considered for computational imaging. Two systems for an image reconstruction task are studied and one system for a detection task is investigated. First, a CI system to extend the field of view is analyzed and an experimental prototype demonstrated. This prototype validates the simulation study and is designed to yield a 3x field of view improvement relative to a conventional imager. Second, a CI system to acquire time-varying natural scenes, i.e. video, is developed. A candidate system using 8x8x16 spatiotemporal blocks yields about 292x compression compared to a conventional imager. Candidate electro-optical architectures, including charge-domain processing, to implement this approach are also discussed. Lastly, a CI system with x-ray pencil beam illumination is investigated for a detection task where system performance is quantified using an information-theoretic metric.