Coronary arteries are the blood vessels supplying oxygen-rich blood to the heart muscles. Coronary artery calcium (CAC), which is the total amount of calcium deposited in these arteries, indicates the presence or the future risk of coronary artery diseases. Quantification of CAC is done by using computed tomography (CT) scan which uses attenuation of x-ray by different tissues in the body to generate three-dimensional images. Calcium can be easily spotted in the CT images because of its higher opacity to x-ray compared to that of the surrounding tissue. However, the arteries cannot be identified easily in the CT images. Therefore, a second scan is done after injecting a patient with an x-ray opaque dye known as contrast material which makes different chambers of the heart and the coronary arteries visible in the CT scan. This procedure is known as computed tomography angiography (CTA) and is performed to assess the morphology of the arteries in order to rule out any blockage in the arteries. The CT scan done without the use of contrast material (non-contrast-enhanced CT) can be eliminated if the calcium can be quantified accurately from the CTA images. However, identification of calcium in CTA images is difficult because of the proximity of the calcium and the contrast material and their overlapping intensity range. In this dissertation first we compare the calcium quantification by using a state-of-the-art non-contrast-enhanced CT scan method to conventional methods suggesting optimal quantification parameters. Then we develop methods to accurately quantify calcium from the CTA images. The methods include novel algorithms for extracting centerline of an artery, calculating the threshold of calcium adaptively based on the intensity of contrast along the artery, calculating the amount of calcium in mixed intensity range, and segmenting the artery and the outer wall. The accuracy of the calcium quantification from CTA by using our methods is higher than the non-contrast-enhanced CT thus potentially eliminating the need of the non-contrast-enhanced CT scan. The implications are that the total time required for the CT scan procedure, and the patient's exposure to x-ray radiation are reduced.

Recent advances in retinal imaging have made it possible to take measurements of retinal oxygen saturation noninvasively in humans. This allows studying the supply of oxygen in healthy and diseased retinae, thereby advancing our understanding of both the normal functioning of the retina and of retinal pathologies. However, retinal oximetry is still a research tool only and requires further improvement before being used in a clinical setting. Here, a single-wavelength flickering light was used to increase retinal blood flow in healthy subjects. This increase is revealed by both vasodilation and an increase in retinal oxygen saturation. A flickering light stimulus provides the means to assess the sensitivity of any retinal oximetry system, as such systems should be able to pick up this increase in retinal blood flow. In addition, the flickering light allows for com- parison to be made within rather than between subjects and can be used to examine the activation of the eye. This reduces the influence of potential confounding factors between subjects including differences in fundus pigmentation and illumination. The most commonly used method to measure retinal oxygenation is the optical density ra- tio (ODR) approach. The standard approach is to compute the average ODR for each vessel segment by combining the hundreds of individual ODR readings and then to use the mean of these segment averages as a measure of oxygen saturation. Alternatively, it has been suggested that the peak location of Gaussian functions fitted to histograms of individual ODR readings can be used as an measure of retinal oxygenation. In response to a 10Hz flickering light, the venular diameter increased by 3.44% (SEM: ±0.53%) (n=16, p<0.05) and the arteriolar diameter by 1.87% (±0.72 %) (p<0.05). The optical density ratio, measured with the Gaussian fit, decreased in the venules from 0.713 (±0.015) to 0.694 (±0.015) (p<0.05). No changes in arteriolar optical density ratios were measured. The post-flicker measurement was computed as the average of up to four post-flicker datasets obtained at 10s, 20s, 30s and 40s after onset of flickering. These results suggest that the flickering light increased retinal blood flow. The mean absolute percentage error was lower in venules for the Gaussian fit method than for the gold standard method for datasets taken at 30s and 40s after onset of flickering. Thus, the Gaussian fit method was more robust. All measurements were taken with a custom-made retinal oximeter. The pixel intensity of the blood vessel and the intensity on either side of the vessel had to be extracted to compute the individual optical density ratios. This required the automatic extraction of the retinal vasculature. Two such algorithms were developed and applied to two databases of retinal fundus images: the DRIVE and the novel DR HAGIS database. One algorithm was purely based on the pixel intensities, while the other made use of oriented Gabor filters. These two algorithms segmented the images to a similar accuracy (DRIVE: 94.56% and 94.54%, DR HAGIS: 95.83% and 95.71% for the intensity and Gabor filter based algorithm, respectively) and performed as well as a human expert (DRIVE: 94.73%). These algorithms were of sufficient quality to extract individual segments for the oximetry study and to align fundus images.