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The research in this thesis was undertaken because information on the relationship between scan parameters and image quality for the MARS spectral CT was lacking. However, the MARS spectral CT is expected to extend into clinical use in the future, so it is absolutely crucial that we know how the quality of the images that it produces is effected by different can parameters. This will allow us to make further improvements to the machine, and ultimately help clinicians to visualise important information in patients which are not revealed by other imaging modalities. This thesis provides information on how the image quality is affected by different scan parameters on the MARS spectral CT using a Medipix3 silicon quad detector. In particular, it explores how different numbers of projections, exposure time products (mAs), and peak tube voltages (kVp) with different threshold energies (kV) effect the image noise, image resolution and image uniformity, respectively. This provides a set of guidelines for future work using the MARS scanner to obtain images of optimal quality. This thesis also determines that the new image reconstruction software mART developed by Niels de Ruiter, is a suitable replacement for the reconstruction software OctopusCT that is currently being used by the MARS team. Using mART reduces the scan times and dose delivered by the MARS spectral CT.

Thesis (Ph.D)--Biomedical Engineering, Georgia Institute of Technology, 2009. / Committee Chair: Hu, Xiaoping; Committee Member: Keilholz, Shella; Committee Member: Mao, Hui; Committee Member: Martin, Diego; Committee Member: Oshinski, John. Part of the SMARTech Electronic Thesis and Dissertation Collection.

Medical imaging plays an essential role in current clinical research and practice. Among the wealth of available imaging modalities, Positron Tomography Emission (PET) reveals functional processes in vivo by providing information on the interaction between a biological target and its tracer at the molecular level. A time series of PET images obtained from a dynamic scan depicts the spatio-temporal distribution of the PET tracer. Analysing the dynamic PET data then enables the quantification of the functional processes of interest for disease understanding and drug development. Given the time duration of a dynamic PET scan, which is usually 1-2 hours, any subject motion inevitably corrupts the tissue-tovoxel mapping during PET imaging, resulting in an unreliable analysis of the data for clinical decision making. Image registration has been applied to perform motion correction on misaligned dynamic PET frames, however, the current methods are solely based on spatial similarity. By ignoring the temporal changes due to PET tracer kinetics they can lead to inaccurate registration. In this thesis, a spatio-temporal registration framework of dynamic PET data is developed to overcome such limits. There are three scientific contributions made in this thesis. Firstly, the likelihood of dynamic PET data is formulated based on the generative model with both tracer kinetics and subject motion, providing a novel objective function. Secondly, the solution to the optimisation based on the generic plasma-input model is given, leading to the availability of a variety of biological targets. Thirdly, reference-input models are also incorporated to avoid blood sampling and thus extend the coverage of PET studies of the proposed framework. In the simulation-based validation, the proposed method achieves sub-voxel accuracy and its impact on clinical studies is evaluated on dopamine receptor data from an occupancy study, as well as breast cancer data from a reproducibility study. By successfully eliminating the motion artifacts as shown by visual inspection, the proposed method reduces the variability in clinical PET data and improves the confidence of deriving outcome measures on a study level. The motion correction algorithms developed in this thesis do not require any additional computational resources for a PET research centre, and they facilitate cost reduction by eliminating the need of acquiring extra PET scans in cases of motion corruption.

The aim of this thesis is to link perceived image quality to physical display parameters. This is done in the context of automotive displays. Specialities of automotive display applications like high ambient lighting conditions and the necessity to access information quickly are explained. A summary of readability models relevant to automotive applications is given and the difference between readability and perceived image quality is explained. The methodology chosen to investigate perceived image quality is the Image-Quality-Circle framework by Engeldrum (2000). Engeldrum states that observers form their image quality rating by weighting the visual attributes they perceive. Visual algorithms, which can be investigated via psychometric scaling, link visual attributes to the underlying physical image parameters which are typically measure by physical instruments. The visual attributes investigated in this thesis are perceived contrast, brightness, blackness and colourfulness. Perceived contrast, brightness and blackness are derived from display luminance via the DICOM just noticeable difference (JND) scale. Colourfulness is scaled based colour gamut in the CIE1931 chromaticity diagram. It was shown that image quality rating rises with growing perceived contrast; the limiting factors are glare and perceived blackness. In colourfulness scaling a linear relationship between colour gamut and colourfulness rating was demonstrated. Higher colourfulness can compensate lower brightness in perceived image quality.

Image quality has been found to be positively correlated with diagnosis accuracy. Radiologist aim for the highest quality image possible to determine the location of the suspected pathology. However, the most effective way of producing high quality images is to increase the radiation dosage to the patient. To avoid the many risks that come with radiation, patients want to keep dosage as low as possible. Diagnosing instruments are constantly being re-engineered and optimized to keep image quality high and radiation dosage low. If patients wish to avoid nuclear radiation exposure, alternative non-nuclear and low radiation modalities must be employed. The three most important metrics of image quality are spatial resolution, signal-to-noise (SNR) ratio and contrast-to-noise (CNR) ratio [1]. Radiologists and imaging technicians can do very little to improve the spatial resolution; and to improve the CNR a higher dosage is necessary to increase the value of every pixel. To increase radiation-SNR efficiency, the dosage can be reduced by 50% while only dropping the SNR by about 30% [2]. To simulate lower dosage, data is randomly taken out while the image is reconstructed until the acceptable SNR value is achieved. The broad applications can include reducing the signal-to-dosage ratio for any modality involving ionizing radiation and image reconstruction, reducing the risk for every imaged patient.

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Yes / Introduction: Within medical imaging variations in patient size can generate challenges, especially when selecting appropriate acquisition parameters. This experiment sought to evaluate the impact of increasing body part thickness on image quality (IQ) and effective dose (E) and identify optimum exposure parameters. Methods: An anthropomorphic pelvis phantom was imaged with additional layers (1e15 cm) of animal fat as a proxy for increasing body thickness. Acquisitions used the automatic exposure control (AEC), 100 cm source to image distance (SID) and a range of tube potentials (70e110 kVp). IQ was evaluated physically and perceptually. E was estimated using PCXMC software. Results: For all tube potentials, signal to noise ratio (SNR) and contrast to noise ratio (CNR) deceased as body part thickness increased. 70 kVp produced the highest SNR (46.6e22.6); CNR (42.8e17.6). Visual grading showed that the highest IQ scores were achieved using 70 and 75 kVp. As thickness increases, E increased exponentially (r ¼ 0.96; p < 0.001). Correlations were found between visual and physical IQ (SNR r ¼ 0.97, p < 0.001; CNR r ¼ 0.98, p < 0.001). Conclusion: To achieve an optimal IQ across the range of thicknesses, lower kVp settings were most effective. This is at variance with professional practice as there is a tendency for radiographers to increase kVp as thickness increases. Dose reductions were experienced at higher kVp settings and are a valid method for optimisation when imaging larger patients. / Hashemite University in Jordan, College of Radiographers Industry Partnership (CoRIPS)

Yes / An automated closed-loop dose control system balances the radiation dose delivered to patients and the quality of images produced in cardiac x-ray imaging systems. Using computer simulations, this study compared two designs of automatic x-ray dose control in terms of the radiation dose and quality of images produced. The first design, commonly in x-ray systems today, maintained a constant dose rate at the image receptor. The second design maintained a constant image quality in the output images. A computer model represented patients as a polymethylmetacrylate phantom (which has similar x-ray attenuation to soft tissue), containing a detail representative of an artery filled with contrast medium. The model predicted the entrance surface dose to the phantom and contrast to noise ratio of the detail as an index of image quality. Results showed that for the constant dose control system, phantom dose increased substantially with phantom size (x5 increase between 20 cm and 30 cm thick phantom), yet the image quality decreased by 43% for the same thicknesses. For the constant quality control, phantom dose increased at a greater rate with phantom thickness (>x10 increase between 20 cm and 30 cm phantom). Image quality based dose control could tailor the x-ray output to just achieve the quality required, which would reduce dose to patients where the current dose control produces images of too high quality. However, maintaining higher levels of image quality for large patients would result in a significant dose increase over current practice. / This work has been performed in the project PANORAMA, funded by grants from Belgium, Italy, France, the Netherlands, and the United Kingdom, and the ENIAC Joint Undertaking.

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