Klinder Tobias, Lorenz Cristian, von Berg Jens, Dries Sebastian P M, Bülow Thomas, Ostermann Jörn
Institut für Informationsverarbeitung, University of Hannover, Germany.
Med Image Comput Comput Assist Interv. 2007;10(Pt 2):195-202. doi: 10.1007/978-3-540-75759-7_24.
We present a new model-based approach for an automated labeling and segmentation of the rib cage in chest CT scans. A mean rib cage model including a complete vertebral column is created out of 29 data sets. We developed a ray search based procedure for rib cage detection and initial model pose. After positioning the model, it was adapted to 18 unseen CT data. In 16 out of 18 data sets, detection, labeling, and segmentation succeeded with a mean segmentation error of less than 1.3 mm between true and detected object surface. In one case the rib cage detection failed, in another case the automated labeling.
我们提出了一种基于模型的新方法，用于在胸部CT扫描中对胸廓进行自动标记和分割。利用29个数据集创建了一个包含完整脊柱的平均胸廓模型。我们开发了一种基于射线搜索的程序来进行胸廓检测和初始模型定位。在对模型进行定位后，使其适应18个未见过的CT数据。在18个数据集中，有16个成功实现了检测、标记和分割，真实物体表面与检测到的物体表面之间的平均分割误差小于1.3毫米。在一个案例中胸廓检测失败，在另一个案例中自动标记失败。
