The ability to acquire and store radiological images digitally has made this data available to mathematical and scientific
methods. With the step from subjective interpretation to reproducible measurements and knowledge, it is also possible to
develop and apply models that give additional information which is not directly visible in the data. In this context, it is
important to know the characteristics and limitations of each model. Four characteristics assure the clinical relevance of
models for computer-assisted diagnosis and therapy: ability of patient individual adaptation, treatment of errors and
uncertainty, dynamic behavior, and in-depth evaluation. We demonstrate the development and clinical application of a
model in the context of liver surgery. Here, a model for intrahepatic vascular structures is combined with individual, but
in the degree of vascular details limited anatomical information from radiological images. As a result, the model allows
for a dedicated risk analysis and preoperative planning of oncologic resections as well as for living donor liver
transplantations. The clinical relevance of the method was approved in several evaluation studies of our medical partners
and more than 2900 complex surgical cases have been analyzed since 2002.
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