High performance medical image processing in client/server-environments.
As 3D scanning devices like computer tomography (CT) or magnetic resonance imaging (MRI) become more widespread, there is also an increasing need for powerful computers that can handle the enormous amounts of data with acceptable response times. We describe an approach to parallelize some of the more frequently used image processing operators on distributed memory architectures. It is desirable to make such specialized machines accessible on a network, in order to save costs by sharing resources. We present a client/server approach that is specifically tailored to the interactive work with volume data. Our image processing server implements a volume visualization method that allows the user to assess the segmentation of anatomical structures. We can enhance the presentation by combining the volume visualizations on a viewing station with additional graphical elements, which can be manipulated in real-time. The methods presented were verified on two applications for different domains.
Mayer
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Department of Medical and Biological Informatics / H0100 Deutsches Krebsforschungszentrum, Heidelberg, Germany. a.mayer@dkfz-Heidelberg.de
Meinzer
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HP
D000465:Algorithms; D003195:Computer Communication Networks; D003196:Computer Graphics; D003199:Computer Systems; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000295:instrumentation* / Q000379:methods*; D008279:Magnetic Resonance Imaging; D008327:Mammography; D014057:Tomography, X-Ray Computed; D014584:User-Computer Interface