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Patch-based segmentation of overlapping cervical cells using active contour with local edge information

机译:使用具有本地边缘信息的主动轮廓的重叠宫颈单元的基于补丁的分割

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The Pap test is a manual screening procedure that is used to detect the precursor lesions of cervical cancer by analyzing changes in nuclei and cytoplasms of cervical cells. Due to the sensitivity of the Pap test to intra- and inter-observer variability, automating the procedure using digital image analysis test is still an open problem. Within this context, segmentation of overlapping cervical cells is a key component to develop image analysis methods. In this paper, we propose a framework for segmenting the cytoplasm of each individual cell depicted within an image of overlapping cervical cells. The proposed framework uses a patch-based approach where a parametric active contour detects, on a patch-by-path basis, the cytoplasm boundary of each overlapping cell. The active contour within the patch deforms under the influence of Gradient Vector Flow (GVF) forces computed based on the local edges depicted in each patch region. Results show that the proposed framework achieves more accurate cytoplasm segmentation results compared to the current state-of-art methods.
机译:PAP测试是一种手动筛查程序,用于通过分析宫颈细胞的细胞核和细胞质的变化来检测宫颈癌的前体病变。由于PAP测试对内部和观察者间的敏感性,使用数字图像分析测试自动化程序仍然是一个开放问题。在这种情况下,重叠宫颈单元的分割是开发图像分析方法的关键组分。在本文中,我们提出了一种用于分割在重叠宫颈细胞的图像中描绘的每个单独细胞的细胞质的框架。所提出的框架使用基于补丁的方法,其中参数激活轮廓在逐个路径基础上检测每个重叠细胞的细胞质边界。贴片内的主动轮廓在基于每个贴片区域中所示的局部边缘计算的梯度矢量流(GVF)力的影响下变形。结果表明,与目前的最先进的方法相比,该框架达到了更准确的细胞质分段结果。

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