Haeker Mona, Abràmoff Michael, Kardon Randy, Sonka Milan
Department of Electrical and Computer Engineering, The University of Iowa, Iowa City, IA 52242, USA.
Med Image Comput Comput Assist Interv. 2006;9(Pt 1):800-7. doi: 10.1007/11866565_98.
We have developed a method for the automated segmentation of the internal limiting membrane and the pigment epithelium in 3-D OCT retinal images. Each surface was found as a minimum s-t cut from a geometric graph constructed from edge/regional information and a priori-determined surface constraints. Our approach was tested on 18 3-D data sets (9 from patients with normal optic discs and 9 from patients with papilledema) obtained using a Stratus OCT-3 scanner. Qualitative analysis of surface detection correctness indicates that our method consistently found the correct surfaces and outperformed the proprietary algorithm used in the Stratus OCT-3 scanner. For example, for the internal limiting membrane, 4% of the 2-D scans had minor failures with no major failures using our approach, but 19% of the 2-D scans using the Stratus OCT-3 scanner had minor or complete failures.
我们开发了一种用于在三维光学相干断层扫描(OCT)视网膜图像中自动分割内界膜和色素上皮的方法。每个表面都是从由边缘/区域信息和先验确定的表面约束构建的几何图中找到的最小s-t割。我们的方法在使用Stratus OCT-3扫描仪获得的18个三维数据集上进行了测试(9个来自视盘正常的患者,9个来自视乳头水肿的患者)。对表面检测正确性的定性分析表明,我们的方法始终能找到正确的表面,并且优于Stratus OCT-3扫描仪中使用的专有算法。例如,对于内界膜,使用我们的方法,二维扫描中有4%出现轻微失败,无重大失败情况,但使用Stratus OCT-3扫描仪的二维扫描中有19%出现轻微或完全失败的情况。