Institute of Medical Physics, Friedrich-Alexander University Erlangen-Nuremberg, Henkestr. 91, 91052 Erlangen, Germany; Erlangen Graduate School in Advanced Optical Technologies (SAOT), Friedrich-Alexander University Erlangen-Nuremberg, Paul-Gordan-Str. 6, 91052 Erlangen, Germany.
Experimental Ophthalmology, Saarland University, Kirrberger Str. 100, Bldg. 22, 66421 Homburg, Germany.
Z Med Phys. 2014 May;24(2):104-11. doi: 10.1016/j.zemedi.2013.07.002. Epub 2013 Aug 6.
We present a new algorithm for automatic segmentation and detection of an accommodative intraocular lens implanted in a biomechanical eye model. We extracted lens curvature and position. The algorithm contains denoising and fan correction by a multi-level calibration routine. The segmentation is realized by an adapted canny edge detection algorithm followed by a detection of lens surface with an automatic region of interest search to suppress non-optical surfaces like the lens haptic. The optical distortion of lens back surface is corrected by inverse raytracing. Lens geometry was extracted by a spherical fit. We implemented and demonstrated a powerful algorithm for automatic segmentation, detection and surface analysis of intraocular lenses in vitro. The achieved accuracy is within the expected range determined by previous studies. Future improvements will include the transfer to clinical anterior segment OCT devices.
我们提出了一种新的算法，用于自动分割和检测植入生物力学眼球模型中的可调节人工晶状体。我们提取了晶状体曲率和位置。该算法通过多级校准程序进行了去噪和扇形校正。分割是通过自适应的 Canny 边缘检测算法实现的，然后通过自动感兴趣区域搜索来检测晶状体表面，以抑制非光学表面，如晶状体襻。通过反向光线追踪校正了透镜背面的光学失真。通过球面拟合提取了透镜的几何形状。我们在体外实现并演示了一种强大的算法，用于自动分割、检测和分析人工晶状体的表面。所达到的精度在以前的研究确定的预期范围内。未来的改进将包括转移到临床前节 OCT 设备。
