Rudolph D J, Sinclair P M, Coggins J M
Department of Orthodontics, University of California Los Angeles, USA.
Am J Orthod Dentofacial Orthop. 1998 Feb;113(2):173-9. doi: 10.1016/s0889-5406(98)70289-6.
Computerized cephalometric analysis currently requires manual identification of landmark locations. This process is time-consuming and limited in accuracy. The purpose of this study was to develop and test a novel method for automatic computer identification of cephalometric landmarks. Spatial spectroscopy (SS) is a computerized method that identifies image structure on the basis of a convolution of the image with a set of filters followed by a decision method using statistical pattern recognition techniques. By this method, characteristic features are used to recognize anatomic structures. This study compared manual identification on a computer monitor and the SS automatic method for landmark identification on minimum resolution images (0.16 cm2 per pixel). Minimum resolution (defined as the lowest resolution at which a cephalometric structure could be identified) was used to reduce computational time and memory requirements during this development stage of the SS method. Fifteen landmarks were selected on a set of 14 test images. The results showed no statistical difference (p > 0.05) in mean landmark identification errors between manual identification on the computer display and automatic identification using SS. We conclude that SS shows potential for the automatic detection of landmarks, which is an important step in the development of a completely automatic cephalometric analysis.
计算机化头影测量分析目前需要手动识别标志点位置。这个过程既耗时又在准确性上存在局限。本研究的目的是开发并测试一种用于自动计算机识别头影测量标志点的新方法。空间光谱学(SS)是一种计算机化方法,它基于图像与一组滤波器的卷积,随后使用统计模式识别技术的决策方法来识别图像结构。通过这种方法,特征被用于识别解剖结构。本研究比较了在计算机显示器上的手动识别和在最低分辨率图像(每像素0.16平方厘米)上使用SS自动方法进行标志点识别。在SS方法的这个开发阶段,使用最低分辨率(定义为能够识别头影测量结构的最低分辨率)来减少计算时间和内存需求。在一组14张测试图像上选择了15个标志点。结果显示,在计算机显示器上的手动识别和使用SS的自动识别之间,平均标志点识别误差没有统计学差异(p > 0.05)。我们得出结论,SS在标志点的自动检测方面显示出潜力,这是完全自动头影测量分析发展中的重要一步。