S-Space College of Engineering/Engineering Practice School (공과대학/대학원) Dept. of Industrial Engineering (산업공학과) Journal Papers (저널논문_산업공학과)
Automatic Skull Segmentation and Registration for Tissue Change Measurement After Mandibular Setback Surgery
- Lee, Jeongjin; Kim, Namkug; Kang, Suk-Ho; Park, Jae-Woo; Chang, Young-Il
- Issue Date
- Springer Verlag
- Lecture Notes in Computer Science, Vol. 4319/2006 (2006) 322-331
- In this paper, we propose an automated system that registers dental
CT scans at pre- and post-operative states for a three-dimensional analysis on
soft and hard tissue changes after mandibular setback surgery. Our registration
method matches automatically extracted skulls to obtain optimal registration
parameters based on the rigid transformation. Chamfer distance map algorithm
is employed to accelerate a registration speed by referring to pre-calculated
distance value and eliminating burdens of point-to-point correspondence
identification. Skull surface registration corrects the translational and rotational
mismatch. During an adaptive optimization, search range and step are
dynamically changed to achieve finer alignments fast and robustly. Our method
has been successfully applied to eight pairs of pre- and post-operative CT scans.
Experimental results show that our algorithm is more accurate, and converges
faster than conventional ones. Using a grid measurement, the changes of bone,
and soft tissue were measured in skeletal Class III mandibular prognathism
patients. Our method could be applicable to the other oral and maxillofacial
surgeries as well as plastic surgeries.
- 0302-9743 (print)
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