Automated layer segmentation of macular OCT images via graph-based SLIC superpixels and manifold ranking approach.
Using the graph-based a simple linear iterative clustering (SLIC) superpixels and manifold ranking technology, a novel automated intra-retinal layer segmentation method is proposed in this paper. Eleven boundaries of ten retinal layers in optical coherence tomography (OCT) images are exactly, fast and reliably quantified. Instead of considering the intensity or gradient features of the single-pixel in most existing segmentation methods, the proposed method focuses on the superpixels and the connected components-based image cues. The image is represented as some weighted graphs with superpixels or connected components as nodes. Each node is ranked with the gradient and spatial distance cues via graph-based Dijkstra's method or manifold ranking. So that it can effectively overcome speckle noise, organic texture and blood vessel artifacts issues. Segmentation is carried out in a three-stage scheme to extract eleven boundaries efficiently. The segmentation algorithm is validated on 2D and 3D OCT images in three databases, and is compared with the manual tracings of two independent observers. It demonstrates promising results in term of the mean unsigned boundaries errors, the mean signed boundaries errors, and layers thickness errors.
School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China; College of Computer and Information Engineering, Heilongjiang University of Science and Technology, Harbin 150022, China. Electronic address: zhjgao@163.com.
Zhijun
Z
Gao
Department of Media Technology and Art, Harbin Institute of Technology, Harbin 150001, China. Electronic address: buwei@hit.edu.cn.
Wei
W
Bu
Department of Eye and Vision Science, Institute of Ageing and Chronic Disease, University of Liverpool, UCD Building, Liverpool L69 3GA, United Kingdom.
Yalin
Y
Zheng
School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China.
Xiangqian
X
Wu
D000465:Algorithms; D016477:Artifacts; D006801:Humans; D021621:Imaging, Three-Dimensional / Q000379:methods; D010363:Pattern Recognition, Automated / Q000379:methods*; D012160:Retina / Q000000981:diagnostic imaging*; D041623:Tomography, Optical Coherence / Q000379:methods*
Graph; Manifold ranking; Optical coherence tomography (OCT); SLIC superpixels; Segmentation