Generation and Initialization of Stable 3D Mass-Spring Models for the Segmentation of the Thyroid Cartilage

The preoperative planning of primary tumor resections in the larynx region shall be supported by a 3D visualization of the patientspeci c anatomy and pathological situation. This requires a segmentation of the larynx cartilage structures from computed tomography (CT) datasets. In our work, we use 3D Stable Mass-Spring Models (SMSMs) for this segmentation task. Thereto, we create a speci c 3D deformable shape model for the segmentation of the thyroid cartilage. A new concept for elastic initialization of this model is presented, allowing the deformable model to adapt speci cally to patient-speci c shape variations and pathological deformations. We show that using our generation and initialization method, prototypical 3D deformable shape models can be adapted to very di erent patients without any prior training and prior knowledge about new patients' data.