High performance computing in medical science has led to important progress in the field of computer tomography. A fast calculation of various types of images is a precondition for statistical comparison of big sets of input data. With our current research we adapted parallel programs from PVM to CORBA. CORBA makes the integration into clinical environments much easier. In order to improve the efficiency and maintainability we added load balancing and graphical on-line tools to our CORBA-based application program

@inproceedings{TEICMHPCLL01,
	author	 = {Thomas Ludwig and Markus Lindermeier and Alexandros Stamatakis and Günther Rackl},
	title	 = {{Tool Environments in CORBA-Based Medical High Performance Computing}},
	year	 = {2001},
	booktitle	 = {{Parallel Computing Technologies}},
	editor	 = {Victor Malyshkin},
	publisher	 = {Springer},
	address	 = {Berlin / Heidelberg, Germany},
	series	 = {Lecture Notes in Computer Science},
	number	 = {2127},
	pages	 = {447--455},
	conference	 = {PaCT-01},
	organization	 = {Institute of Computational Mathematics and Mathematical Geophysics of the Russian
        Academy of Sciences (Novosibirsk)},
	location	 = {Novosibirsk, Russia},
	doi	 = {http://dx.doi.org/10.1007/3-540-44743-1_47},
	abstract	 = {High performance computing in medical science has led to important progress in the
      field of computer tomography. A fast calculation of various types of images is a precondition
      for statistical comparison of big sets of input data. With our current research we adapted
      parallel programs from PVM to CORBA. CORBA makes the integration into clinical environments
      much easier. In order to improve the efficiency and maintainability we added load balancing
      and graphical on-line tools to our CORBA-based application program},
	url	 = {http://www.springerlink.com/content/duxxkw41pap9uarm/fulltext.pdf},
}