TY - JOUR
T1 - Automatic image slice marking propagation on segmentation of dental CBCT
AU - Arifin, Agus Zainal
AU - Tanuwijaya, Evan
AU - Nugroho, Baskoro
AU - Priyatno, Arif Mudi
AU - Indraswari, Rarasmaya
AU - Astuti, Eha Renwi
AU - Navastara, Dini Adni
N1 - Publisher Copyright:
© 2019 Universitas Ahmad Dahlan. All rights reserved.
PY - 2019/12
Y1 - 2019/12
N2 - 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 Misclassification Error (ME) and Relative Foreground Area Error (RAE) of 0.112 and 0.478, respectively.
AB - 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 Misclassification Error (ME) and Relative Foreground Area Error (RAE) of 0.112 and 0.478, respectively.
KW - Automatic segmentation
KW - Dental CBCT
KW - Hierarchical clustering
KW - Mean-shift
KW - Morphology
UR - http://www.scopus.com/inward/record.url?scp=85080905838&partnerID=8YFLogxK
U2 - 10.12928/TELKOMNIKA.v17i6.13220
DO - 10.12928/TELKOMNIKA.v17i6.13220
M3 - Article
AN - SCOPUS:85080905838
SN - 1693-6930
VL - 17
SP - 3218
EP - 3225
JO - Telkomnika (Telecommunication Computing Electronics and Control)
JF - Telkomnika (Telecommunication Computing Electronics and Control)
IS - 6
ER -