Stefan Zachow

TL;DR: Combining localized classification via CNNs with statistical anatomical knowledge via SSMs results in a state‐of‐the‐art segmentation method for knee bones and cartilage from MRI data.

TL;DR: The accuracy of the fusion of 3D CT surface data and optical 3D imaging is significantly reduced by metal artefacts, however, it seems appropriate for virtual orthognathic surgery simulation, as post-operative orthodontics are performed frequently.

TL;DR: The results of the study indicate that the algorithm for automatic segmentation of the human pelvic bones from CT datasets that is based on the application of a statistical shape model meets the requirements of clinical routine.

TL;DR: A new approach using not only three-dimensional (3-D) surface models of the patient's anatomy, but also a corresponding volumetric model, is discussed and was found to provide a good correlation between simulation and postoperative outcome.

TL;DR: The honeybee standard brain (HSB) serves as an interactive tool for relating morphologies of bee brain neurons and provides a reference system for functional and bibliographical properties and the most critical issue of this protocol in terms of user interaction time is drastically improved by the use of a model-based segmentation process.