Focal Spot, Spring 1987

https://digitalcommons.wustl.edu/focal_spot_archives/1045/thumbnail.jp

An Overview of Rendering from Volume Data --- including Surface and Volume Rendering

Volume rendering is a title often ambiguously used in science. One meaning often quoted is: `to render any three volume dimensional data set'; however, within this categorisation `surface rendering'' is contained. Surface rendering is a technique for visualising a geometric representation of a surface from a three dimensional volume data set. A more correct definition of Volume Rendering would only incorporate the direct visualisation of volumes, without the use of intermediate surface geometry representations. Hence we state: `Volume Rendering is the Direct Visualisation of any three dimensional Volume data set; without the use of an intermediate geometric representation for isosurfaces'; `Surface Rendering is the Visualisation of a surface, from a geometric approximation of an isosurface, within a Volume data set'; where an isosurface is a surface formed from a cross connection of data points, within a volume, of equal value or density. This paper is an overview of both Surface Rendering and Volume Rendering techniques. Surface Rendering mainly consists of contouring lines over data points and triangulations between contours. Volume rendering methods consist of ray casting techniques that allow the ray to be cast from the viewing plane into the object and the transparency, opacity and colour calculated for each cell; the rays are often cast until an opaque object is `hit' or the ray exits the volume

Efficiently computing and registering digitally reconstructed radiographs

Generation of digitally reconstructed radiographs (DRRs) is computationally expensive and has been cited as the rate-limiting step in the execution time of intensity-based two-dimensional/three-dimensional registration algorithms. This paper considers the problem of generating DRRs by conventional ray tracing. Experiments confirm that good quality reconstructions can be obtained using this approach in a few seconds. We evaluate the approach for automatic patient setup prior to radiotherapy treatment by performing intensity based 2D-3D registration using normalized cross correlation. Preliminary results using a pelvic CT data set show the method is accurate to about ±2 pixels (i.e. ±0.3 mm)

Computed tomography-osteoabsorptiometry for assessing the density distribution of subchondral bone as a measure of long-term mechanical adaptation in individual joints

To estimate subchondral mineralisation patterns which represent the long-term loading history of individual joints, a method has been developed employing computed tomography (CT) which permits repeated examination of living joints. The method was tested on 5 knee, 3 sacroiliac, 3 ankle and 5 shoulder joints and then investigated with X-ray densitometry. A CT absorptiometric presentation and maps of the area distribution of the subchondral bone density areas were derived using an image analyser. Comparison of the results from both X-ray densitometry and CT-absorptiometry revealed almost identical pictures of distribution of the subchondral bone density. The method may be used to examine subchondral mineralisation as a measure of the mechanical adaptability of joints in the living subject