Model-Based Segmentation of Reconstructed Dental X-Ray Volumes

Modern reconstruction algorithms allow volumetric imaging with conventional 2D dental X-ray systems. Volumetric images are useful in dental implantology, where the correct identification of key structures such as the edges of the mandible and the mandibular nerve is critical. This paper presents a segmentation method capable of extracting the mandible. The segmentation is based on a statistical model which was first transformed affinely and finally deformed non-rigidly to the object. The method was tested on three volumes with good results: mean distances between the deformed and manually segmented reference surfaces were 0.26, 0.34 and 0.50 mm. Applications of the method include the extraction of slices orthogonal to the mandibular bone centerline and local, anatomy based image enhancement.