egmentation of cytoplasm and nuclei of abnormal cells in cervical ytology using global and local graph cuts
egmentation of cytoplasm and nuclei of abnormal cells in cervical ytology using global and local graph cuts
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Ling Zhang;Hui Kong;Ti-Hsuan Chien;Chin;Shaoxiong Liu;Zhi Chen;Tianfu Wang;Siping Chen
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作者：
Ling Zhang;Hui Kong;Ti-Hsuan Chien;Chin;Shaoxiong Liu;Zhi Chen;Tianfu Wang;Siping Chen
自动化辅助阅读（AAR）技术有可能减少宫颈癌筛查的错误并提高生产率。 AAR 的灵敏度在很大程度上依赖于异常宫颈细胞的自动分割，而当前的分割算法对此处理不佳。在本文中，提出了一种基于图割方法的全局和局部方案来分割图像中含有健康和异常细胞的宫颈细胞。对于细胞质分割，对a*通道增强图像进行全局多路切图，当图像直方图呈现非双峰分布时，这可能是有效的。对于细胞核的分割，特别是当它们异常时，我们建议使用自适应和局部的图切割，它允许强度、纹理、边界和区域信息的组合。集成了两种基于凹点的方法来分裂接触核。作为正在进行的临床试验的一部分，从 21 个具有非理想成像条件和病理的宫颈细胞图像获得的初步验证结果表明，我们的分割方法对细胞质的准确率达到 93%，对异常细胞核的 F 测量准确率达到 88.4%，在准确度方面优于最先进的方法。我们的方法有可能提高 AAR 在宫颈癌筛查中的敏感性。
Automation-assisted reading (AAR) techniques have the potential to reduce errors and increase productivity in cervical cancer screening. The sensitivity of AAR relies heavily on automated segmentation of abnormal cervical cells, which is handled poorly by current segmentation algorithms. In this paper, a global and local scheme based on graph cut approach is proposed to segment cervical cells in images with a mix of healthy and abnormal cells. For cytoplasm segmentation, the multi-way graph cut is performed globally on the a* channel enhanced image, which can be effective when the image histogram presents a non-bimodal distribution. For segmentation of nuclei, especially when they are abnormal, we propose to use graph cut adaptively and locally, which allows the combination of intensity, texture, boundary and region information. Two concave points-based approaches are integrated to split the touching-nuclei. As part of an ongoing clinical trial, preliminary validation results obtained from 21 cervical cell images with non-ideal imaging condition and pathology show that our segmentation method achieved 93% accuracy for cytoplasm, and 88.4% F-measure for abnormal nuclei, outperforming state of the art methods in terms of accuracy. Our method has the potential to improve the sensitivity of AAR in screening for cervical cancer.