Volume Rendering

Volume Rendering:

This program will produce different volume renderings of the Infant datasets.
Volume rendering techniques have been developed to overcome problems of the accurate representation of surfaces in the isosurface techniques. Volume rendering does not use intermediate geometrical representations, in contrast to surface rendering techniques. It offers the possibility for displaying weak or fuzzy surfaces.

The term volume rendering is used to describe techniques which allow the visualization of three-dimensional data. Volume rendering is a technique for visualizing sampled functions of three spatial dimensions by computing 2-D projections of a colored semitransparent volume.
The Obvious Advantages of Volume rendering over isosurfacing.

Volume Rendering displays a dataset which convey depth information much more clearly than isosurfacing; this is not surprising since with isosurfacing we are limited to particular surface (isovalue) while with Volume Rendering we see a set of nested surfaces. But isosurfacing is much faster than volume rendering and if quick iterative results with acceptable visualization quality applied as three views (axial, frontal and sagital) on one slice, is achieving what we want then isosurfacing is good.

The major application area of volume rendering is medical imaging, where volume data is available from X-ray Computer Tomagraphy (CT) scanners. The image has given in this assignment is taken by a CT scanner. CT produce three-dimensional stacks of parallel plane images, each of which consists of an array of X-ray absorption coefficients.
The assignment dataset X-ray CT images will have a resolution of 512 * 512 * 123 bits and there will be up to 50 slides in a stack. The slides are 1-5 mm thick, and are spaced 1-5 mm apart.

Volume rendering involves the following steps: the forming of an RGBA volume from the data, reconstruction of a continuous function from this discrete data set, and projecting it onto the 2D viewing plane (the output image) from the desired point of view. An RGBA volume is a 3D four-vector data set, where the first three components are the familiar R, G, and B color components and the last component, A, represents opacity. An opacity value of 0 means totally transparent and a value of 1 means totally opaque. Behind the RGBA volume an opaque background is placed. The mapping of the data to opacity values acts as a classification of the data one is interested in. Isosurfaces can be shown by mapping the corresponding data values to almost opaque values and the rest to transparent values.

The appearance of surfaces can be improved by using shading techniques to form the RGB mapping. However, opacity can be used to see the interior of the data volume too. These interiors appear as clouds with varying density and color. A big advantage of volume rendering is that this interior information is not thrown away, so that it enables one to look at the 3D data set as a whole. Disadvantages are the difficult interpretation of the cloudy interiors and the long time, compared to surface rendering, needed to perform volume rendering.