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Institut für Visualisierung und Interaktive Systeme

Automated 3D Video Documentation for Analysis of Medical Data

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Automated 3D Video Documentation for Analysis of Medical Data

Dieses Dokument ist zur Zeit leider nur in Englisch verfügbar.

Direct volume rendering based on hardware supported 3D texture mapping is an approach which produces images of high quality and interactive frame rates. These features facilitate the practical use in medical applications. The drawback of this technology is that it is limited by the high cost of purchase of the necessary high end computer graphics hardware.

3D visualization is a useful approach for surgery analysis and planning. However, in the field of medical documentation, 3D documentation is currently not frequently used. In conventional visualization applications special software tools or manual doing of snapshots is necessary to produce videos. Both approaches need a lot of resources and time. Additionally these tools are not usually not integrated into the visualization tool which is very inconvenient for the user.

We implemented a hardware supported approach integrated in our visualization tool. SGI offers an OpenGL extension the so-called pixel buffer. The pixel buffer is a hardware accelerated nonvisible (off-screen) rendering buffer. The combination of these features allows us to record digital videos in a fast way and without time delaying. In our application the produced video will be integrated into an HTML document which contains the patient data and information about the disease.

To use automatically generated videos it is necessary to define the content of this video. Usually clinicians examine individual patient data in similar ways. Therefore, using standardized video sequences to record the examination is a feasible approach to use 3D visualization results in documentation. Like aforementioned we want to avoid that all physicians need the expensive special graphics hardware. For that we want to offer a secure web service where the user will send the medical patient data and receive a document which contains all data together with the produced video.

Contact: Sabine Iserhardt-Bauer

[RIH00] C. Rezk-Salama, S. Iserhardt-Bauer, P. Hastreiter, J. Scherer, K. Eberhardt, B. Tomandl, G. Greiner and T. Ertl. Automated 3D Visualization and Documentation for the Analysis of Tomographic Data.