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[Basic principles of data acquisition and data processing for construction of high quality virtual models].

H Shin·G Stamm·D Högemann·M Galanski
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Abstract

Creating models for virtual reality subdivides into several steps. The aim of the data acquisition is the extraction of nearly isotropic (same solution in all three axes) data sets with low noise content. An approximate isotropy can be achieved by suitable choice of scan parameters. For raw data reconstruction, the application of high-resolution reconstruction algorithms is prohibited due to increased noise. A missing isotropy can computationally be approximated by interpolation. Further noise suppression is achieved by applying filters. Additionally, the contrast of the object for segmentation can be increased by image processing operators. The correct choice of the segmentation method and the editing tools is essential for a precise segmentation with minimal user interaction. Prior to visualization, smoothing the shape of the segmented model (shape-based or morphological interpolation, polygon reduction of wire frame model) further improves the visual appearance of the 3D model.

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AlgorithmsComputer GraphicsComputer SimulationDiagnostic ImagingHumansImage EnhancementImage Processing, Computer-AssistedQuality Assurance, Health CareUser-Computer InterfaceEnglish AbstractJournal Article

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H Shin, G Stamm, D Högemann, M Galanski. 2000. [Basic principles of data acquisition and data processing for construction of high quality virtual models].. https://doi.org/10.1007/s001170050673

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