Many surface rendering techniques are currently available for the three-dimensional display of structure data captured by imaging devices. Comparatively fewer volume rendering techniques are also available for the same purpose. The relative performance of these two methodologies in visualization tasks has been a subject of much discussion recently. Although it is very desirable to establish, based on observer studies, objective guidelines stating the relative merits of the two methodologies even for specific situations, it is impossible to conduct meaningful observer studies that take into account the numerousness of the techniques in each methodology, and within each technique, the numerousness of the parameters and their values that control the outcome of the technique. Our aim in this article is to compare the two methodologies purely on a technical basis in an attempt to understand their common weaknesses and disparate strengths. The purpose of this article is twofoldmto report a new surface rendering technique and to compare it with two volume rendering techniques reported recently in the literature. The bases of comparison are: abUity to portray thin bones; clarity of portrayal of sutures, fractures, fine textures, and gyrations; smoothness of natural ridges and silhouettes; and computational time and storage requirements. We analyze the underlying algorithms to study how they behave under each of these comparative criteria. Our conclusion is that, at the current state of development, the surface method has a slight edge over the volume methods for portrayal of information of the type described above and a significant advantage considering time and storage requirements, for implementations in identical environments.
Multidimensional image data are becoming increasingly common in biomedical imaging. Three-dimensional visualization and analysis techniques based on three-dimensional image data have become an established discipline in biomedicine. Some imaging problems generate image data of even higher dimensions. It often becomes necessary, rather than just convenient, to consider the higher-dimensional data as a whole to adequately answer the underlying imaging questions. Despite this established need for convenient exchange of ima9e and image-derived information, no exchange protocols are available that adequately meet the needs of multidimensional imaging systems. This paper describes an exchange protocol that has been desi9ned after careful consideration of the common requirements of methodologies for visualization and analysis of multidimensional data. Ir is based on and is a generalization of the widely accepted American College of Radiology-National Electrical Manufacturers Association (ACR-NEMA) standards specified for two-dimensional images. It is implemented and actively being used in a data-, application-, and machine-independent software environment, being developed in the authors' department, for the visualization and analysis of muItidimensional images.
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