Digital Image Processing (3rd Edition)
Digital Image Processing (3rd Edition)
Teeth And Jaw 3D Reconstrucion In Stomatology
MEDIVIS '07 Proceedings of the International Conference on Medical Information Visualisation - BioMedical Visualisation
An automatic segmentation and reconstruction of mandibular structures from CT-data
IDEAL'09 Proceedings of the 10th international conference on Intelligent data engineering and automated learning
MICCAI'06 Proceedings of the 9th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part I
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This paper presents a method for segmenting the inferior maxillary bone in CT images and a technique to automatically classify bone tissue without requiring a training stage. These methods are used to measure the mean density of seven main anatomical zones of the mandible, making the difference between cortical and cancellous bone. The results lead to determine the normal density values in each region of the inferior maxillary bone and help to evaluate the success of the bone regeneration process. The proposed method was validated on ten axial slices from different zones of a patient mandible, by comparing automatic classification results with those obtained by expert manual classification. A 4% mean difference was found between percentages of bone tissue types, and the mean difference between mean density values was of 88 HU. Once the method was validated, it was applied to measure density in the seven anatomical zones of the inferior maxillary bone.