Reliability and Robustness in Image Based Surgical Planning

Computational support in intervention planning promises to support the subjective interpretation of data with reproducible measurements. Moreover, it is possible to develop and apply models that provide additional information which is not directly visible in the data. Beside the ability of patient individual adaptation, proper treatment of errors and uncertainty is of crucial importance to assure the clinical relevance of models for computer-assisted diagnosis and therapy. In the context of image based planning for liver surgery, 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 3500 complex surgical cases have been analyzed since 2002.