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Proceedings Paper

Advanced techniques in volume visualization and analysis
Author(s): Richard A. Robb; Armando Manduca; Dennis P. Hanson; Ronald A. Karwoski
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Paper Abstract

Human vision provides an extraordinarily powerful and effective means for acquiring information. Much of what we know about ourselves and our environment has been derived from images — images produced by various instruments, ranging form microscopes to telescopes and spanning orders of magnitude in scale — extending the range of human vision into realms beyond that which is naturally accessible. The full scientific, educational, and/or clinical value of these images is profoundly significant, and recent development of advanced methods to fully visualize and quantitatively analyze the intrinsic information contained in biomedical images, in particular, have begun to recognize and unearth the rich treasures o such recordings. This tutorial will provide an introduction to several and demonstration of (using ANALYZE) advanced methodologies being developed and applied to address the need for new approaches to image display and analysis as improvements in imaging technology enable more complex objects and processes to be imaged and simulated. These will include methods for segmentation (e.g. by math morphology) of 3-D images and for integration (e.g. by surface matching) of multi-modality images. Arguably, these are two of the most important and challenging problems in multidimensional biomedical imaging today. In addition the tutorial will emphasize the significant potential of 3-D image classification (e.g. using multi-spectral analysis) and feature measurements to enhance specificity and sensitivity in studies of biological structure-to-function relationships; in diagnostic accuracy and discriminating power; and in clinical/surgical treatment planning and delivery. Advanced volume rendering (using several ray casting algorithms) to simultaneously and interactively produce multiple individual, combined, and transparent objects and parametric displays for visualization of segmented, fused and/or classified objects will be discussed and demonstrated.

Paper Details

Date Published: 22 September 1992
PDF: 1 pages
Proc. SPIE 1808, Visualization in Biomedical Computing '92, (22 September 1992); doi: 10.1117/12.131124
Show Author Affiliations
Richard A. Robb, Mayo Clinic (United States)
Armando Manduca, Mayo Clinic (United States)
Dennis P. Hanson, Mayo Clinic (United States)
Ronald A. Karwoski, Mayo Clinic (United States)


Published in SPIE Proceedings Vol. 1808:
Visualization in Biomedical Computing '92
Richard A. Robb, Editor(s)

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