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A Biased Median Filtering Algorithm for Segmentation of Intestinal Cell Gland Images

机译:一种有偏中值滤波算法用于肠细胞腺图像的分割

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摘要

In this paper, we introduce a biased median filtering image segmentation algorithm for intestinal cell glands consisting of goblet cells. While segmentation of individual cells are generally based on the dissimilarities in intensities, textures, and shapes between cell regions and background, the proposed segmentation algorithm of intestine cell glands is based on the differences in cell distributions. The intestine cell glands consist of goblet cells that are distributed in the chain-organized patterns in contrast to the more randomly distributed nongoblet cells scattered in the bright background. Four biased median filters with long rectangular windows of identical dimension, but different orientations, are designed based on the shapes and distributions of cells. Each biased median filter identifies a part of gland segments in a particular direction. The complete gland regions are the combined responses of the four biased median filters. A postprocessing procedure is designed to reduce the defects that may occur when glands are located very close together and to narrow the gapping areas because of the thin distribution of goblet cells. Segmentation results of real intestinal cell gland images are provided to show the effectiveness of the proposed algorithm.
机译:在本文中,我们介绍了一种由杯状细胞组成的肠道细胞腺体的有偏差中值滤波图像分割算法。虽然单个细胞的分割通常基于细胞区域和背景之间的强度,纹理和形状的差异,但建议的肠道细胞腺体分割算法是基于细胞分布的差异。肠道细胞腺体由杯状细胞组成,杯状细胞分布在链状组织的模式中,与散布在明亮背景中的随机分布的非杯状细胞相反。根据单元的形状和分布,设计了四个具有相同尺寸但方向不同的长矩形窗口的偏置中值滤波器。每个有偏差的中值滤波器会在特定方向上识别一部分腺体段。完整的腺体区域是四个偏置中值滤波器的组合响应。设计后处理程序是为了减少由于腺杯状细胞分布较稀而使腺体非常靠近在一起时可能出现的缺陷,并缩小间隙区域。提供了真实的肠道细胞腺体图像的分割结果,以显示该算法的有效性。

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