Paper
6 April 2005 Comparing three methods for simplifying mesh models of the lungs: an observer test to assess perceived quality
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Abstract
Meshes are currently used to model objects, namely human organs and other structures. However, if they have a large number of triangles, their rendering times may not be adequate to allow interactive visualization, a mostly desirable feature in some diagnosis (or, more generally, decision) scenarios, where the choice of adequate views is important. In this case, a possible solution consists in showing a simplified version while the user interactively chooses the viewpoint and, then, a fully detailed version of the model to support its analysis. To tackle this problem, simplification methods can be used to generate less complex versions of meshes. While several simplification methods have been developed and reported in the literature, only a few studies compare them concerning the perceived quality of the obtained simplified meshes. This work describes an experiment conducted with human observers in order to compare three different simplification methods used to simplify mesh models of the lungs. We intended to study if any of these methods allows a better-perceived quality for the same simplification rate. A protocol was developed in order to measure these aspects. The results presented were obtained from 32 human observers. The comparison between the three mesh simplification methods was first performed through an Exploratory Data Analysis and the significance of this comparison was then established using other statistical methods. Moreover, the influence on the observers' performances of some other factors was also investigated.
© (2005) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Samuel Silva, Beatriz Sousa Santos, Joaquim Madeira, and Carlos Ferreira "Comparing three methods for simplifying mesh models of the lungs: an observer test to assess perceived quality", Proc. SPIE 5749, Medical Imaging 2005: Image Perception, Observer Performance, and Technology Assessment, (6 April 2005); https://doi.org/10.1117/12.593906
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Cited by 6 scholarly publications.
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KEYWORDS
Data modeling

Lung

3D modeling

Visualization

Radiography

Statistical analysis

Statistical methods

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