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从光学相干断层扫描(OCT)图像中分割视网膜层表面。

Segmentation of the surfaces of the retinal layer from OCT images.

作者信息

Haeker Mona, Abràmoff Michael, Kardon Randy, Sonka Milan

机构信息

Department of Electrical and Computer Engineering, The University of Iowa, Iowa City, IA 52242, USA.

出版信息

Med Image Comput Comput Assist Interv. 2006;9(Pt 1):800-7. doi: 10.1007/11866565_98.

Abstract

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.

摘要

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。

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