Abstract. The exact localization of the mandibular nerve with respect to the bone is important for applications in dental implantology and maxillofacial surgery. Cone beam computed tomography (CBCT), often also called digital volume tomography (DVT), is increasingly utilized in maxillofacial or dental imaging. Compared to conventional CT, however, soft tissue discrimination is worse due to a reduced dose. Thus, small structures like the alveolar nerves are even harder recognizable within the image data. We show that it is nonetheless possible to accurately reconstruct the 3D bone surface and the course of the nerve in a fully automatic fashion, with a method that is based on a combined statistical shape model of the nerve and the bone and a Dijkstra-based optimization procedure. Our method has been validated on 106 clinical datasets: the average reconstruction error for the bone is 0.5 ± 0.1 mm, and the nerve can be detected with an average error of 1.0 ± 0.6 mm.
The segmentation accuracy proved to be comparable to that of manual segmentations by experienced users and significantly reduced the time and interaction needed for the lymph node segmentation.
The results show that our method is suitable for the estimation of pose differences of the human rib cage in binary projection images. Thus, it is able to provide crucial 3D information for registration during the generation of 2D subtraction images.
A precise 3D model of the glenoid bony defect can be generated. The computer simulation provides a virtual model of the bone graft, which may potentially improve arthroscopic bone augmentation.
Abstract. In this work we present an articulated statistical shape model (ASSM) of the human knee. The model incorporates statistical shape variation plus explicit degrees of freedom that model physiological joint motion. We also present a strategy for segmentation of the knee joint from medical image data. We show the potential of the model via an evaluation on a set of 40 clinical MRI datasets with manual expert segmentations available.
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