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Cytoplasm segmentation on cervical cell images using graph cut-based approach

机译:基于图割的宫颈细胞图像细胞质分割

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摘要

This paper proposes a method to segment the cytoplasm in cervical cell images using graph cut-based algorithm. First, the A* channel in CIE LAB color space is extracted for contrast enhancement. Then, in order to effectively extract cytoplasm boundaries when image histograms present non-bimodal distribution, Otsu multiple thresholding is performed on the contrast enhanced image to generate initial segments, based on which the segments are refined by the multi-way graph cut method. We use 21 cervical cell images with non-ideal imaging condition to evaluate cytoplasm segmentation performance. The proposed method achieved a 93% accuracy which outperformed state-of-the-art works.
机译:本文提出了一种基于图割的分割细胞图像的方法。首先,提取CIE LAB颜色空间中的A *通道以增强对比度。然后,为了在图像直方图呈现非双峰分布时有效地提取细胞质边界,对对比度增强图像执行Otsu多重阈值化以生成初始片段,然后通过多路图切割方法对这些片段进行精炼。我们使用具有非理想成像条件的21个宫颈细胞图像来评估细胞质分割性能。所提出的方法达到了93%的精度,超过了最新技术。

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