Modern 3D visualization environments for medical image data provide high interactivity and flexibility but
depend on the expert knowledge and the experience of the user with respect to the software application. The
definition of the visualization parameters is a manual time-consuming process and as a result, inter-patient
or inter-study comparisons are extremely difficult. To overcome these drawbacks in case of the analysis and
diagnosis of pathologies, standardization of 3D visualization is an important issue. For this purpose automatically
generated digital video sequences can be used to convey the most important information contained in the data.
In this paper, we present an improvement of our existing web-based service which is now able to calculate the
video sequences in much shorter time exploiting the power of a GPU-cluster. The system requires to transfer a
medical volume dataset from an arbitrary computer connected via Internet and sends back a number of video
files automatically generated with direct volume rendering. To achieve an optimal load balancing of the available
resources, the tasks of automatic adjustment of transfer functions, volume rendering, and video encoding are
divided into small sub-requests, which are distributed to the different cluster nodes in order to be performed in
parallel. An additional preview mode, which renders a number of dedicated frames, provides a direct feedback
and quick overview. For the evaluation, we were focusing on the analysis of intracranial aneurysms and were
able to show that the system can be successfully applied. Further on, the system was developed in a way that
allows easy integration of other analysis tasks.