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A general model for multiphase texture segmentation and its applications to retinal image analysis

机译：多相纹理分割的通用模型及其在视网膜图像分析中的应用

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摘要

In this paper we propose a general variational segmentation model for multiphase texture segmentation based on fuzzy region competition principle. An important strength of the proposed framework is that different region terms (e.g. mutual information Kim et al. (2005) [1], local histogram Ni et al. (2009) [2] models for texture-based segmentation, and piecewise constant intensity model Chan and Vese (2001) [3] for intensity-based segmentation) can be included as appropriate to the problem. Constraints of different phases are considered by introducing Lagrangian multipliers into the energy functional, and a fast numerical solution is achieved by employing the fast dual projection algorithm Chambolle (2004) [4]. The proposed model has been applied to synthetic and natural images in order to make comparisons with other competing models in literature. Our results demonstrate superiority in dealing with multiphase texture segmentation problems. To demonstrate its usefulness in biomedical applications we have applied the new model to two retinal image segmentation problems: segmentation of capillary non-perfusion regions in fluorescein angiogram and segmentation of cellular layers of the retina in optical coherence tomography, and evaluated against the gold standard set by experts. The generalized overlap analysis shows good agreement for both applications. As a generic segmentation technique our new model has the potential to be extended for wider applications.
机译：本文提出了一种基于模糊区域竞争原理的多相纹理分割通用变分分割模型。提出的框架的一个重要优点是可以使用不同的区域项（例如，互信息Kim Kim等人（2005）[1]，局部直方图Ni等人（2009）[2]用于基于纹理的分割的模型以及分段恒定强度）对于基于强度的分割，可以使用模型Chan和Vese（2001）[3]。通过将拉格朗日乘子引入能量泛函来考虑不同阶段的约束，并通过使用快速对偶投影算法Chambolle（2004）[4]实现快速数值解。提出的模型已应用于合成图像和自然图像，以便与文献中的其他竞争模型进行比较。我们的结果证明了在处理多相纹理分割问题方面的优势。为了证明其在生物医学应用中的有用性，我们将新模型应用于两个视网膜图像分割问题：荧光血管造影中毛细管非灌注区域的分割和光学相干断层扫描中视网膜细胞层的分割，并针对金标准集进行了评估由专家。广义重叠分析显示了两种应用的良好一致性。作为一种通用的细分技术，我们的新模型具有扩展到更广泛应用的潜力。

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