Chuang Ying Ji, Doherty Benjamin M, Adluru Nagesh, Chung Moo K, Vorperian Houri K
J Comput Assist Tomogr. 2018 Mar/Apr;42(2):306-316. doi: 10.1097/RCT.0000000000000669.
We present a registration-based semiautomatic mandible segmentation (SAMS) pipeline designed to process a large number of computed tomography studies to segment 3-dimensional mandibles.
The pipeline consists of a manual preprocessing step, an automatic segmentation step, and a final manual postprocessing step. The automatic portion uses a nonlinear diffeomorphic method to register each preprocessed input computed tomography test scan on 54 reference templates, ranging in age from birth to 19 years. This creates 54 segmentations, which are then combined into a single composite mandible.
This pipeline was assessed using 20 mandibles from computed tomography studies with ages 1 to 19 years, segmented using both SAMS-processing and manual segmentation. Comparisons between the SAMS-processed and manually-segmented mandibles revealed 97% similarity agreement with comparable volumes. The resulting 3-dimensional mandibles were further enhanced with manual postprocessing in specific regions.
Findings are indicative of a robust pipeline that reduces manual segmentation time by 75% and increases the feasibility of large-scale mandibular growth studies.
我们提出一种基于配准的半自动下颌骨分割（SAMS）流程，旨在处理大量计算机断层扫描研究以分割三维下颌骨。
该流程包括一个手动预处理步骤、一个自动分割步骤和一个最终手动后处理步骤。自动部分使用非线性微分同胚方法将每个预处理后的输入计算机断层扫描测试扫描与54个参考模板进行配准，年龄范围从出生到19岁。这会创建54个分割结果，然后将它们组合成一个单一的复合下颌骨。
使用来自年龄为1至19岁的计算机断层扫描研究的20个下颌骨对该流程进行评估，同时使用SAMS处理和手动分割进行分割。SAMS处理的下颌骨与手动分割的下颌骨之间的比较显示，在可比体积方面相似度一致率为97%。所得的三维下颌骨在特定区域通过手动后处理得到进一步增强。
研究结果表明该流程强大，可将手动分割时间减少75%，并提高大规模下颌骨生长研究的可行性。
