Volume rendering of abdominal aortic aneurysms

One well known application area of volume rendering 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. 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. 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.

[1]  R H Hruban,et al.  Three-dimensional reconstruction of the human body. , 1988, AJR. American journal of roentgenology.

[2]  Marc Levoy,et al.  Volume Rendering For Display Of Multiple Organs, Treatment Objects, And Image Intensities , 1989, Other Conferences.

[3]  J. Wolfe,et al.  The role of categorization in visual search for orientation. , 1992, Journal of experimental psychology. Human perception and performance.

[4]  J. Wolfe,et al.  Limitations on the Parallel Guidance of Visual Search : Color x Color and Orientation x Orientation Conjuctions , 2004 .

[5]  Elliot K. Fishman,et al.  Surgical Planning for Liver Resection , 1996, Computer.

[6]  Pat Hanrahan,et al.  Volume Rendering , 2020, Definitions.

[7]  Colin Ware,et al.  Color sequences for univariate maps: theory, experiments and principles , 1988, IEEE Computer Graphics and Applications.

[8]  Elliot K. Fishman,et al.  Volumetric rendering of computed tomography data: principles and techniques , 1990, IEEE Computer Graphics and Applications.

[9]  Eric A. Hoffman,et al.  Volumetric analysis of abdominal aortic aneurysm , 1996, Medical Imaging.

[10]  Christopher G. Healey,et al.  Choosing effective colours for data visualization , 1996, Proceedings of Seventh Annual IEEE Visualization '96.

[11]  Brian Cabral,et al.  Accelerated volume rendering and tomographic reconstruction using texture mapping hardware , 1994, VVS '94.

[12]  Bernice E. Rogowitz,et al.  An architecture for rule-based visualization , 1993, Proceedings Visualization '93.

[13]  T. Callaghan Dimensional interaction of hue and brightness in preattentive field segregation , 1984, Perception & psychophysics.