Use of 2D histograms for volume rendering of multidetector CT data: development of a graphical user interface.
| Autor: | Shin HO; Department of Diagnostic Radiology, Medical School of Hannover, Carl-Neuberg-Strasse 1, Hannover 30623, Germany. shin.hoen-oh@mh-hannover.de, King B, Galanski M, Matthies HK |
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| Jazyk: | angličtina |
| Zdroj: | Academic radiology [Acad Radiol] 2004 May; Vol. 11 (5), pp. 544-50. |
| DOI: | 10.1016/j.acra.2004.01.013 |
| Abstrakt: | Rationale and Objectives: Direct volume rendering reveals 3D information on anatomic structures without preprocessing the data. This increases the interest in this technique as a diagnostic tool. A fast and simple method for setting transfer functions is crucial for clinical routine work. However, this is still a complex task. Present commercial workstations are usually limited to design galleries and window/level functionality. Materials and Methods: We present a graphical user interface for volume rendering of multidetector row CT data that permits a much more flexible specification of rendering parameters. A 2D histogram of CT density versus gradient magnitude facilitates the understanding of the spatial connections of different tissues. The incorporation of gradient magnitude into the transfer function domain allows discrimination of features of interest that are not distinguishable on CT density alone. Penetration length, color, and gradient magnitude are depicted on a stack of 2D slices according to the settings of the opacity transfer function and the viewing direction. A gallery of thumbnails with presets of transfer functions is interactively adapted if the volume is rotated or cropped. Results: This allows for fast evaluation of numerous rendering protocols at once. The interface was evaluated with CT data covering skeletal trauma, pathologies of the thorax/abdomen, and CT angiography. Conclusion: We observed that high-quality visualizations could be obtained with reasonable interaction times. The 2D histogram and penetration length displays provided valuable insight into the dataset that made the specification of transfer functions a goal-oriented process. |
| Databáze: | MEDLINE |
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