Marching cubes: A high resolution 3D surface construction algorithm
SIGGRAPH '87 Proceedings of the 14th annual conference on Computer graphics and interactive techniques
Graphical Models and Image Processing
Scale-based fuzzy connected image segmentation: theory, algorithms, and validation
Computer Vision and Image Understanding - Special issue on analysis of volumetric image
Image Analysis and Mathematical Morphology
Image Analysis and Mathematical Morphology
Computer Methods and Programs in Biomedicine
Teeth And Jaw 3D Reconstrucion In Stomatology
MEDIVIS '07 Proceedings of the International Conference on Medical Information Visualisation - BioMedical Visualisation
Image guided oral implantology and its application in the placement of zygoma implants
Computer Methods and Programs in Biomedicine
Computer-based extraction of the inferior alveolar nerve canal in 3-D space
Computer Methods and Programs in Biomedicine
Automatic Extraction of Mandibular Nerve and Bone from Cone-Beam CT Data
MICCAI '09 Proceedings of the 12th International Conference on Medical Image Computing and Computer-Assisted Intervention: Part II
MICCAI'06 Proceedings of the 9th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part I
IEEE Transactions on Image Processing
Teeth segmentation of dental periapical radiographs based on local singularity analysis
Computer Methods and Programs in Biomedicine
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The success of oral surgery is subject to accurate advanced planning. In order to properly plan for dental surgery or a suitable implant placement, it is necessary an accurate segmentation of the jaw tissues: the teeth, the cortical bone, the trabecular core and over all, the inferior alveolar nerve. This manuscript presents a new automatic method that is based on fuzzy connectedness object extraction and mathematical morphology processing. The method uses computed tomography data to extract different views of the jaw: a pseudo-orthopantomographic view to estimate the path of the nerve and cross-sectional views to segment the jaw tissues. The method has been tested in a groundtruth set consisting of more than 9000 cross-sections from 20 different patients and has been evaluated using four similarity indicators (the Jaccard index, Dice's coefficient, point-to-point and point-to-curve distances), achieving promising results in all of them (0.726+/-0.031, 0.840+/-0.019, 0.144+/-0.023mm and 0.163+/-0.025mm, respectively). The method has proven to be significantly automated and accurate, with errors around 5% (of the diameter of the nerve), and is easily integrable in current dental planning systems.