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.
Haeker
Mona
M
Department of Electrical and Computer Engineering, The University of Iowa, Iowa City, IA 52242, USA. mona-haeker@uiowa.edu
Abràmoff
Michael
M
Kardon
Randy
R
Sonka
Milan
M
D000465:Algorithms; D001185:Artificial Intelligence; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D010211:Papilledema / Q000473:pathology*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012160:Retina / Q000473:pathology*; D012680:Sensitivity and Specificity; D013499:Surface Properties; D041623:Tomography, Optical Coherence / Q000379:methods*