Michikawa Takashi, Suzuki Hiromasa, Moriguchi Masaki, Ogihara Naomichi, Kondo Osamu, Kobayashi Yasushi
Center for Environmental Innovation Design for Sustainability, Osaka University, Suita, Osaka, Japan.
Department of Precision Engineering, The University of Tokyo, Bunkyo, Tokyo, Japan.
PLoS One. 2017 Apr 13;12(4):e0168516. doi: 10.1371/journal.pone.0168516. eCollection 2017.
The authors present a method for extracting polygon data of endocranial surfaces from CT images of human crania. Based on the fact that the endocast is the largest empty space in the crania, we automate a procedure for endocast extraction by integrating several image processing techniques. Given CT images of human crania, the proposed method extracts endocranial surfaces by the following three steps. The first step is binarization in order to fill void structures, such as diploic space and cracks in the skull. We use a void detection method based on mathematical morphology. The second step is watershed-based segmentation of the endocranial part from the binary image of the CT image. Here, we introduce an automatic initial seed assignment method for the endocranial region using the distance field of the binary image. The final step is partial polygonization of the CT images using the segmentation results as mask images. The resulting polygons represent only the endocranial part, and the closed manifold surfaces are computed even though the endocast is not isolated in the cranium. Since only the isovalue threshold and the size of void structures are required, the procedure is not dependent on the experience of the user. The present paper also demonstrates that the proposed method can extract polygon data of endocasts from CT images of various crania.
作者提出了一种从人类颅骨的CT图像中提取颅内表面多边形数据的方法。基于颅内模型是颅骨中最大的空腔这一事实，我们通过整合多种图像处理技术，自动化了颅内模型提取的过程。给定人类颅骨的CT图像，所提出的方法通过以下三个步骤提取颅内表面。第一步是进行二值化，以填充诸如板障间隙和颅骨裂缝等空洞结构。我们使用基于数学形态学的空洞检测方法。第二步是从CT图像的二值图像中基于分水岭算法对颅内部分进行分割。在此，我们使用二值图像的距离场为颅内区域引入一种自动初始种子分配方法。最后一步是使用分割结果作为掩码图像对CT图像进行部分多边形化。所得多边形仅代表颅内部分，并且即使颅内模型在颅骨中未被分离，也能计算出封闭的流形表面。由于只需要等价值阈值和空洞结构的大小，该过程不依赖于用户的经验。本文还证明了所提出的方法能够从各种颅骨的CT图像中提取颅内模型的多边形数据。
