Graf Franz, Kriegel Hans-Peter, Schubert Matthias, Pölsterl Sebastian, Cavallaro Alexander
Institut für Informatik, Ludwig-Maximilians-Universität München Oettingenstr. 67, D-80538 München, Germany.
Med Image Comput Comput Assist Interv. 2011;14(Pt 2):607-14. doi: 10.1007/978-3-642-23629-7_74.
Registering CT scans in a body atlas is an important technique for aligning and comparing different CT scans. It is also required for navigating automatically to certain regions of a scan or if sub volumes should be identified automatically. Common solutions to this problem employ landmark detectors and interpolation techniques. However, these solutions are often not applicable if the query scan is very small or consists only of a single slice. Therefore, the research community proposed methods being independent from landmark detectors which are using imaging techniques to register the slices in a generalized height scale. In this paper, we propose an improved prediction method for registering single slices. Our solution is based on specialized image descriptors and instance-based learning. The experimental evaluation shows that the new method improves accuracy and stability of comparable registration methods by using only a single CT slice is required for the registration.
将CT扫描图像注册到人体图谱中是对齐和比较不同CT扫描图像的一项重要技术。在自动导航到扫描的特定区域或需要自动识别子体积时，这也是必需的。解决此问题的常见方法是使用地标检测器和插值技术。然而，如果查询扫描非常小或仅由单个切片组成，这些方法通常不适用。因此，研究界提出了一些独立于地标检测器的方法，这些方法使用成像技术在广义高度尺度上注册切片。在本文中，我们提出了一种改进的单切片注册预测方法。我们的解决方案基于专门的图像描述符和基于实例的学习。实验评估表明，新方法通过仅使用单个CT切片进行注册，提高了可比注册方法的准确性和稳定性。
