Hanaoka Shouhei, Nomura Yukihiro, Nemoto Mitsutaka, Masutani Yoshitaka, Maeda Eriko, Yoshikawa Takeharu, Hayashi Naoto, Yoshioka Naoki, Ohtomo Kuni
Division of Radiology and Biomedical Engineering, Graduate School of Medicine, University of Tokyo, Tokyo, Japan.
J Comput Assist Tomogr. 2010 Jan;34(1):156-62. doi: 10.1097/RCT.0b013e3181b12242.
Segmentation of vertebral bones in computed tomographic data is important as a first stage of image-based radiological tasks. However, it is a challenging problem to segment an affected spine correctly. In this study, we propose a new method of segmentation of thoracic and lumbar vertebral bodies from thin-slice computed tomographic images. Especially, we focus on a deformable model-based segmentation scheme to confirm the feasibility in clinical data sets with various bone diseases, such as bone metastases and scoliosis. As an application of this algorithm, virtual straightening of the thoracolumbar spine is also performed. Results on a database of 16 patients indicate the applicability of our method to spines affected by scoliosis and multiple bone metastases.
在计算机断层扫描数据中对椎骨进行分割，作为基于图像的放射学任务的第一阶段很重要。然而，正确分割受影响的脊柱是一个具有挑战性的问题。在本研究中，我们提出了一种从薄层计算机断层扫描图像中分割胸腰椎椎体的新方法。特别是，我们专注于基于可变形模型的分割方案，以确认在患有各种骨病（如骨转移瘤和脊柱侧弯）的临床数据集中的可行性。作为该算法的一个应用，还对胸腰椎进行了虚拟矫直。对16名患者的数据库的结果表明，我们的方法适用于受脊柱侧弯和多发性骨转移影响的脊柱。
