Automatic Image Slice Marking Propagation on Segmentation of Dental CBCT

Agus Zainal Arifin, Evan Tanuwijaya, Baskoro Nugroho, Arif Mudi Priyatno, Rarasmaya Indraswari, Eha Renwi Astuti, Dini Adni Navastara


Cone Beam Computed Tomography (CBCT) is a radiographic technique that has been commonly used to help doctors provide more detailed information for further examination. CBCT tooth segmentation has many challenges such as low contrast, boundaries of blurred teeth and irregular contours of the teeth. In addition, because the CBCT results produce a lot of slices, where each slice has information that is related and the topology of each slice can differ from one another, so the marking on each slice becomes exhaustive and inefficient, due to information similarities on each slice. In this study, we propose an automatic image slice marking propagation on segmentation of dental CBCT. Marker from the result of the first slice segmentation will be use as the information for the next slices propagately. This study was successful in segmenting using the proposed marking method with an error value of Misclassification Error (ME) and Relative Foreground Area Error (RAE) of 0.112 and 0.478, respectively.


Automatic segmentation, Mean-shift, Morphology, Hierarchical clustering, Dental CBCT

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