Visualization and Graphical Processing of Volume Data

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The extraction and visualization of information from volume data constitute important research avenues in computer graphics and imaging. The rapid development of GPUs with increasing computational power has made it possible to generate intuitive, three-dimensional representations of data sets, which can be tweaked and manipulated interactively. This thesis presents various techniques developed within the field of volume graphics. These have wide applicability in the generation of meaningful images from mainly CT and MRI data sets. The work addresses multiple aspects of volume visualization and rendering, such as the representation, classification and in-depth graphical analysis of the information contained within volume data. Initially, we present generic information on the nature of volume data, the mathematical and physical models behind volume rendering, as well as the rendering algorithms used within our prototyping framework for the rendering of images. Subsequently, we address the problem of volume classification, where we explore the use of various types of transfer functions. These operate on voxel properties such as the gradient, curvature or visibility, allowing for the isolation of increasingly complex and problematic features. We provide alternative, more computationally-efficient ways of approximating some of these properties and show how they can be used for classification purposes. We also provide an effective way of specifying multidimensional transfer functions from 1D components, thus increasing the flexibility and expanding the potential of the classification process.Another part of the thesis deals with cardiac MRI data. Specifically, we develop a tool for the visual inspection of parameters which influence the status and functionality of the left ventricle. The considered parameters are the thickness and thickening of the myocardial wall, the moment of maximum thickness and the average speed of the wall during a cardiac cycle. Starting from segmentation contours which outline the epicardium and endocardium, we construct surfaces and use these to visualize the distribution of parameter values using color coding. The technique allows for information from multiple slices, over multiple phases and stress levels to be represented on a single 3D geometry, therefore facilitating the analysis of multidimensional data sets comprising a large number of slices. The values of the cardiac parameters are depicted in an intuitive manner, making them easily accessible to both medical staff and patients with no medical training. In the last part of the thesis we develop a method for the analysis of parameters involved in the volume rendering pipeline. The technique involves sampling the parameters across their domains, rendering images for each sample, and computing the differences among these images. The resulting values characterize the behavior and stability of the parameters across their domains. These values are further used to augment various user interfaces, such as sliders or transfer function specification widgets. The newly-modified interfaces use color coding, graphs, arrows and other info-vis techniques to show the potential changes induced by the parameters in images resulting from volume rendering, thus allowing users to make better-informed decisions when adjusting parameter values.