Segmentation of the Surfaces of the Retinal Layer from OCT Images

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.

[1]  Scott T. Acton,et al.  Speckle reducing anisotropic diffusion , 2002, IEEE Trans. Image Process..

[2]  Xiaodong Wu,et al.  Optimal Net Surface Problems with Applications , 2002, ICALP.

[3]  Kim L. Boyer,et al.  Retinal thickness measurements from optical coherence tomography using a Markov boundary model , 2001, IEEE Transactions on Medical Imaging.

[4]  Xiaodong Wu,et al.  Optimal Surface Segmentation in Volumetric Images-A Graph-Theoretic Approach , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[5]  Steven R. Fleagle,et al.  Methods of graph searching for border detection in image sequences with applications to cardiac magnetic resonance imaging , 1995, IEEE Trans. Medical Imaging.

[6]  Demetri Terzopoulos,et al.  Deformable models in medical image analysis: a survey , 1996, Medical Image Anal..

[7]  J. Caprioli,et al.  Optical coherence tomography to detect and manage retinal disease and glaucoma. , 2004, American journal of ophthalmology.

[8]  Kecheng Liu,et al.  Shape recovery algorithms using level sets in 2-D/3-D medical imagery: a state-of-the-art review , 2002, IEEE Transactions on Information Technology in Biomedicine.

[9]  Tony F. Chan,et al.  Active contours without edges , 2001, IEEE Trans. Image Process..