OCT segmentation: Integrating open parametric contour model of the retinal layers and shape constraint to the Mumford-Shah functional
OCT segmentation: Integrating open parametric contour model of the retinal layers and shape constraint to the Mumford-Shah functional
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DOI：
10.1007/978-3-030-04747-4_17
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发表时间：
2018-08
期刊：
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通讯作者：
J. Duan;Weicheng Xie;R. W. Liu;C. Tench;I. Gottlob;F. Proudlock;L. Bai
中科院分区：
文献类型：
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作者：
J. Duan;Weicheng Xie;R. W. Liu;C. Tench;I. Gottlob;F. Proudlock;L. Bai
本文提出了一种新的视网膜层边界模型用于光学相干层析成像(OCT)图像的分割。视网膜层边界模型由9个开放的参数轮廓线组成，代表OCT图像中的9个视网膜层。首先定义了一种基于强度的Mumford-Shah(MS)变分泛函来演化视网膜层边界模型以同时分割这9层。通过利用开放参数轮廓的法线，我们构造了大小相等的相邻窄带，这些窄带被每个轮廓分割。因此，可以将每个窄带中的区域信息集成到MS能量泛函中，使得其优化对于不同的初始化是稳健的。还对泛函的分段参数轮廓的形状施加统计先验。这样，通过最小化MS能量泛函，可以将参数轮廓驱动到视网膜层的真实边界，同时保持轮廓相对于训练OCT形状的相似性。在实际OCT图像上的实验结果表明，该方法对低对比度和高水平相干斑噪声的低质量OCT图像具有较好的准确性和鲁棒性，并且优于最近提出的基于测地距离的OCT图像视网膜9层分割方法。
In this paper, we propose a novel retinal layer boundary model for segmentation of optical coherence tomography (OCT) images. The retinal layer boundary model consists of 9 open parametric contours representing the 9 retinal layers in OCT images. An intensity-based Mumford-Shah (MS) variational functional is first defined to evolve the retinal layer boundary model to segment the 9 layers simultaneously. By making use of the normals of open parametric contours, we construct equal sized adjacent narrowbands that are divided by each contour. Regional information in each narrowband can thus be integrated into the MS energy functional such that its optimisation is robust against different initialisations. A statistical prior is also imposed on the shape of the segmented parametric contours for the functional. As such, by minimising the MS energy functional the parametric contours can be driven towards the true boundaries of retinal layers, while the similarity of the contours with respect to training OCT shapes is preserved. Experimental results on real OCT images demonstrate that the method is accurate and robust to low quality OCT images with low contrast and high-level speckle noise, and it outperforms the recent geodesic distance based method for segmenting 9 layers of the retina in OCT images.