Stamm T, Brinkhaus H A, Ehmer U, Meier N, Bollmann F
Department of Orthodontics, University of Münster, Germany.
J Orofac Orthop. 1998;59(2):73-81. doi: 10.1007/BF01340641.
The computer-aided method presented is able to interpret and measure radiological structures automatically and reproducibly on a large number of randomly selected lateral head films of different film quality. For example the hard and soft tissue expression of the profile is used to discuss method, application and disadvantages. The performance of the system depends on image quality. The algorithm cannot be influenced by opacifications due to metal structure. In 90% of all cases the contours are identified correctly. Even if the image quality is poor, the recognition rate is about 84%. The selected cephalometric landmarks are placed in the right way in 85% of all cases. The constraint mathematical conditions and the high reproducibility improve the quality process of the cephalometric analysis. Recognition rates of 84% to 90% justify even nowadays the routine use of semi-automatic systems in PC-based analysis. With advancing digital radiography and improved computer performance, image interpreting systems will certainly become established.
所提出的计算机辅助方法能够在大量随机选择的、具有不同胶片质量的头颅侧位片上自动且可重复地解释和测量放射学结构。例如，利用轮廓的软硬组织表现来讨论该方法、应用及缺点。系统的性能取决于图像质量。该算法不会受到金属结构导致的影像模糊的影响。在所有病例中，90%的轮廓能被正确识别。即便图像质量较差，识别率也约为84%。在所有病例中，85%的情况下所选的头影测量标志点放置正确。约束性数学条件和高重复性提高了头影测量分析的质量过程。即便在如今，84%至90%的识别率也证明了半自动系统在基于个人电脑的分析中可常规使用。随着数字放射摄影技术的进步和计算机性能的提升，图像解释系统必将得到广泛应用。
