Automatic Tooth Region Separation for Dental CT Images

2008 ◽  
Author(s):  
Hui Gao ◽  
Oksam Chae
Keyword(s):  
Ct Images ◽  
Dental Ct

Method for reduction of metal artifacts in dental CT images by use of frequency analysis

ICCAS 2010 ◽  
2010 ◽  
Author(s):  
Keishi Mito ◽  
Hyoungseop Kim ◽  
Joo Kooi Tan ◽  
Seiji Ishikawa ◽  
Tatsuro Tanaka ◽  
...  
Keyword(s):  
Frequency Analysis ◽  
Ct Images ◽  
Metal Artifacts ◽  
Dental Ct

Three-dimensional analysis of alveolar bone resorption by image processing of 3-D dental CT images

2006 ◽  
Author(s):  
Jiro Nagao ◽  
Takayuki Kitasaka ◽  
Kensaku Mori ◽  
Yasuhito Suenaga ◽  
Shohzoh Yamada ◽  
...  
Keyword(s):  
Image Processing ◽  
Bone Resorption ◽  
Dimensional Analysis ◽  
Alveolar Bone ◽  
Three Dimensional ◽  
Ct Images ◽  
Dental Ct

scholarly journals High-quality Stitching Method of 3D Multiple Dental CT Images

2014 ◽  
Vol 17 (10) ◽  
pp. 1205-1212 ◽  
Author(s):  
Seyoon Park ◽  
Seongjin Park ◽  
Jeongjin Lee ◽  
Juneseuk Shin ◽  
Yeong-Gil Shin
Keyword(s):  
Ct Images ◽  
High Quality ◽  
Dental Ct

scholarly journals Study on selection of methods of mandibular resection based on evaluation of the extent of mandibular bone invasin by oral cancer using reformatted dental CT images.

1998 ◽  
Vol 24 (1) ◽  
pp. 109-115 ◽  
Author(s):  
Toyoko KISHI ◽  
Mikio KUSAMA ◽  
Kentaro HOSHI ◽  
Keiko NATORI ◽  
Reiko MATSUMOTO ◽  
...  
Keyword(s):  
Oral Cancer ◽  
Ct Images ◽  
Mandibular Bone ◽  
Dental Ct ◽  
Selection Of

scholarly journals Metal artifact reduction in dental CT images using polar mathematical morphology

2011 ◽  
Vol 102 (1) ◽  
pp. 64-74 ◽  
Author(s):  
Valery Naranjo ◽  
Roberto Lloréns ◽  
Mariano Alcañiz ◽  
Fernando López-Mir
Keyword(s):  
Mathematical Morphology ◽  
Ct Images ◽  
Artifact Reduction ◽  
Metal Artifact ◽  
Metal Artifact Reduction ◽  
Dental Ct

scholarly journals Fast and Accurate Semiautomatic Segmentation of Individual Teeth from Dental CT Images

2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
Ho Chul Kang ◽  
Chankyu Choi ◽  
Juneseuk Shin ◽  
Jeongjin Lee ◽  
Yeong-Gil Shin
Keyword(s):  
Multicore Processors ◽  
Region Growing ◽  
Volume Measurement ◽  
Ct Images ◽  
Average Error ◽  
Dental Surgery ◽  
Dental Ct ◽  
Seeded Region Growing ◽  
Conventional Methods ◽  
The Individual

DIn this paper, we propose a fast and accurate semiautomatic method to effectively distinguish individual teeth from the sockets of teeth in dental CT images. Parameter values of thresholding and shapes of the teeth are propagated to the neighboring slice, based on the separated teeth from reference images. After the propagation of threshold values and shapes of the teeth, the histogram of the current slice was analyzed. The individual teeth are automatically separated and segmented by using seeded region growing. Then, the newly generated separation information is iteratively propagated to the neighboring slice. Our method was validated by ten sets of dental CT scans, and the results were compared with the manually segmented result and conventional methods. The average error of absolute value of volume measurement was2.29±0.56%, which was more accurate than conventional methods. Boosting up the speed with the multicore processors was shown to be 2.4 times faster than a single core processor. The proposed method identified the individual teeth accurately, demonstrating that it can give dentists substantial assistance during dental surgery.

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