Paper
1 May 1991 Comparison of three-dimensional surface rendering techniques
Judith G. Thomas, Robert L. Galloway Jr., Charles A. Edwards II, Gerald L. Haden, Robert J. Maciunas
Author Affiliations +
Abstract
To make use of the three-dimensional information contained in a series of computed tomography (CT) or magnetic resonance (MR) slices, one must either mentally reconstruct the data or generate a model using a computer display. Computer-aided rendering of a three- dimensional surface allows inspection of the model from different angles. Creation of a three- dimensional model in wireframe or shaded surface format from tomographic slices requires identification of points along the surface of interest in each slice. This task can be accomplished (1) by manually outlining the surface in the images, or (2) by a computer algorithm designed to produce points along the surface of interest. In dealing with image sets of the head, objects outside the head (e.g., support structures, stereotactic frames, and noise) complicate the automatic detection of the perimeter of the head. This paper examines three methods of automatic wireframe generation from CT or MR slices of the head. The three approaches are based on the following techniques: traditional edge detection filters, neural networks, and thresholding combined with region connectivity analysis and region elimination. Results of the three approaches are presented along with a comparison of the relative advantages and disadvantages of each.
© (1991) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Judith G. Thomas, Robert L. Galloway Jr., Charles A. Edwards II, Gerald L. Haden, and Robert J. Maciunas "Comparison of three-dimensional surface rendering techniques", Proc. SPIE 1444, Medical Imaging V: Image Capture, Formatting, and Display, (1 May 1991); https://doi.org/10.1117/12.45190
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Cited by 3 scholarly publications.
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KEYWORDS
Head

3D modeling

Neural networks

Edge detection

Binary data

Computed tomography

Visualization

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