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Journal from gdlhub / 2020-01-10 09:03:28
Oleh : Agus Zainal Arifin,Evan Tanuwijaya,Baskoro Nugroho,Arif Mudi Priyatno, Rarasmaya Indraswari,Eha Renwi Astuti,Dini Adni Navastara, Telkomnika
Dibuat : 2020-01-10, dengan 1 file

Keyword : automatic segmentation, dental CBCT, hierarchical clustering, mean-shift, morphology.
Url : http://journal.uad.ac.id/index.php/TELKOMNIKA/issue/view/640
Sumber pengambilan dokumen : web

Cone Beam Computed Tomography (CBCT) is a radiographic technique that has been commonly

used to help doctors provide more detailed information for further examination. Teeth segmentation on

CBCT image has many challenges such as low contrast, blurred teeth boundary and irregular contour of

the teeth. In addition, because the CBCT produces a lot of slices, in which the neighboring slices have

related information, the semi-automatic image segmentation method, that needs manual marking from

the user, becomes exhaustive and inefficient. In this research, we propose an automatic image slice

marking propagation on segmentation of dental CBCT. The segmentation result of the first slice will

be propagated as the marker for the segmentation of the next slices. The experimental results show that

the proposed method is successful in segmenting the teeth on CBCT images with the value of

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