PMID: 20625221Jul 14, 2010Paper

Automatic segmentation of teeth from dentomaxillofacial 3D-CT images

Nihon Hoshasen Gijutsu Gakkai zasshi
Mitsuhiro AizawaShinichi Murakami

Abstract

CT is an effective tool for image diagnosis because it enables noninvasive observation of internal organs. In the course of CT, 3D-CT, such as a helical scanning CT and a multi-detector row CT, has been developed. With the use of 3D-CT, organs can be observed from several viewing directions. Even now, however, 3D-CT images are generated by manual procedures to extract objective organs using the threshold method. These procedures waste time and effort. Therefore, development of highly automated and effective extracting techniques has been desired. The region growing (RG) method is one of the effective techniques of extracting internal organs. The conventional RG method, however, has some defects. Extracted regions are strongly affected by the threshold value for segmentation. A break point on a region contour yields a leakage of region. To overcome these defects, we formulated a modified region growing method with edge detection (MRGWED) which combines a three-dimensional region growing technique and an edge detection technique. Using the MRGWED, we tried to extract teeth from dentomaxillofacial 3D-CT image data.

References

Jul 9, 2003·IEEE Transactions on Medical Imaging·Yan KangWilli A Kalender
Jan 1, 1995·IEEE Transactions on Medical Imaging·Z YueL V Ackerman
Feb 8, 2008·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society·J FanW G Aref
Jun 1, 1986·IEEE Transactions on Pattern Analysis and Machine Intelligence·J Canny

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