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Erschienen in:
2017 | OriginalPaper | Buchkapitel
Automatic Retinal Layer Segmentation Based on Live Wire for Central Serous Retinopathy
verfasst von : Dehui Xiang, Geng Chen, Fei Shi, Weifang Zhu, Xinjian Chen
Erschienen in: Fetal, Infant and Ophthalmic Medical Image Analysis
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Abstract
Central serous retinopathy is a serious retinal disease. Retinal layer segmentation for this disease can help ophthalmologists to provide accurate diagnosis and proper treatment for patients. In order to detect surfaces in optical coherence tomography images with pathological changes, an automatic method is reported by combining random forests and a live wire algorithm. First, twenty four features are designed for the random forest classifiers to find initial surfaces. Then, a live wire algorithm is proposed to accurately detect surfaces between retinal layers even though OCT images with fluids are of low contrast and layer boundaries are blurred. The proposed method was evaluated on 24 spectral domain OCT images with central serous retinopathy. The experimental results showed that the proposed method outperformed the state-of-art methods.