Alexander Hagemann

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The accuracy of image-guided neurosurgery generally suffers from brain deformations due to intraoperative changes. These deformations cause significant changes of the anatomical geometry (organ shape and spatial interorgan relations), thus making intraoperative navigation based on preoperative images error prone. In order to improve the navigation accuracy,(More)
In order to improve the accuracy of image-guided neurosurgery, different biomechanical models have been developed to correct preoperative images with respect to intraoperative changes like brain shift or tumor resection. All existing biomechanical models simulate different anatomical structures by using either appropriate boundary conditions or by spatially(More)
The accuracy of image-guided neurosurgery generally su ers from brain deformations due to intraoperative changes, e.g., brain shift or tumor resection. In order to improve the accuracy, we developed a biomechanical model of the human head which can be employed for the correction of preoperative images. By now, the model comprises two different materials.(More)
In order to improve the accuracy of image-guided neuro-surgery, diierent biomechanical models have been developed to correct preoperative images w.r.t. intraoperative changes like brain shift or tumor resection. For the simulation of deformations of anatomical structures with diierent material properties, all existing biomechanical models use either(More)
The accuracy of image-guided neurosurgery generally su ers from brain deformations due to intraoperative changes, e.g. brain shift or tumor resection. In order to improve the accuracy, we developed a biomechanical model of the human head which can be employed for the correction of preoperative images. By now, the model comprises two different materials(More)
The accuracy of image-guided neurosurgery generally su ers from brain deformations due to intraoperative changes, e.g. brain shift or tumor resection. In order to improve the accuracy, we developed a biomechanical model of the human head which can be employed for the correction of preoperative images. By now, the model comprises two different materials(More)
Intelligent systems interacting with users often need to relate ambiguous natural language phrases to formal entities which can be further processed. This work strives for learning an optimal sequence of disambiguation questions asked by an agent in order to achieve a perfect interactive disambiguation, setting itself off against previous work on(More)