Volume rendering is a valuable and important technique for scientific visualization. One well known application area is the reconstruction and visualization of output from medical scanners like computed tomography (CT). 2D greyscale slices produced by these scanners can be reconstructed and displayed onscreen as a 3D model.Volume visualization of medical images must address two important issues. First, it is difficult to segment medical scans into individual materials based only on intensity values. This can result in volumes that contain large amounts of unimportant or unnecessary material. Second, although greyscale images are the normal method for displaying medical volumes, these types of images are not necessarily appropriate for highlighting regions of interest within the volume. Studies of the human visual system have shown that individual intensity values are difficult to detect in a greyscale image. In these situations colour is a more effective visual feature, since the lowlevel visual system can rapidly and accurately detect the presence or absence of a particular target colour in a multi-coloured image.We addressed both problems during the visualization of CT scans of abdominal aortic aneurysms. We have developed a classification method that empirically segments regions of interest in each of the 2D slices. We use a perceptual colour selection technique to identify each region of interest in both the 2D slices and the 3D reconstructed volumes. The result is a colourized volume that the radiologists are using to rapidly and accurately identify the locations and spatial interactions of different materials from their scans. Our technique is being used in an experimental post-operative environment to help to evaluate the results of surgery designed to prevent the rupture of the aneurysm. In the future, we hope to use the technique during the planning of placement of support grafts prior to the actual operation.
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