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首页> 外文期刊>Machine Vision and Applications >Automatic image segmentation and classification based on direction texton technique for hemolytic anemia in thin blood smears
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Automatic image segmentation and classification based on direction texton technique for hemolytic anemia in thin blood smears

机译：基于方向texton技术的薄血涂片溶血性贫血自动图像分割与分类

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摘要

This paper proposes an automatic method for cell segmentation and classification of erythrocytes in thin blood smears with hemolytic anemia. First, to remove the background and noises in the blood images, the proposed method detects a series of changes on the edges and analyzes the edge changes by using the 8-connection chain codes technique to recognize isolated erythrocytes. For segmenting the overlapping erythrocytes, the 8-connection chain codes technique obtains the edge direction of the cells to effectively figure out the points of high concavity. Then, the adapted high concavity information is used to separate overlapping erythrocytes and to extract features from each segmented erythro-cyte. After segmenting, all the erythrocytes can be treated equally and the differences between adjacent chain codes of each erythrocyte can be calculated. Furthermore, the proposed method extracts the variation of eight directions from each individual erythrocyte as their features for classifying into four main hemolytic anemia types. Finally, classification process identifies abnormal erythrocytes and the types of hemolytic anemia by using a trained bank of classifiers, utilizing the proposed method to calculate the quantity of erythrocytes and recognize the types of hemolytic anemia effectively.
机译：本文提出了一种用于溶血性贫血薄细胞涂片中红细胞的细胞分割和分类的自动方法。首先，为了去除血液图像中的背景和噪声，该方法检测边缘上的一系列变化，并通过使用8连接链码技术识别分离的红细胞来分析边缘变化。为了分割重叠的红细胞，8连接链编码技术获得了细胞的边缘方向，以有效地找出高凹点。然后，使用适应性高的凹度信息来分离重叠的红细胞，并从每个分割的红细胞中提取特征。分割后，所有红细胞都可以平等对待，并且可以计算出每个红细胞的相邻链码之间的差异。此外，所提出的方法从每个个体红细胞提取八个方向的变化作为其特征，以分类为四种主要的溶血性贫血类型。最后，分类过程使用训练有素的分类器来识别异常的红细胞和溶血性贫血的类型，利用所提出的方法计算红细胞的数量并有效地识别溶血性贫血的类型。

著录项

  • 来源
    《Machine Vision and Applications》 |2014年第2期|501-510|共10页
  • 作者

    Hung-Ming Chen; Ya-Ting Tsao; Shin-Ni Tsai;

  • 作者单位

    Department of Computer Science and Information Engineering, National Taichung University of Science and Technology, No. 129 Sec. 3, San-mind Road, Taichung 404, Taiwan, R.O.C;

    Department of Computer Science and Information Engineering, National Taichung University of Science and Technology, No. 129 Sec. 3, San-mind Road, Taichung 404, Taiwan, R.O.C;

    Institute of Information Systems and Applications, National Tsing Hua University, Hsinchu, Taiwan, R.O.C;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Hemolytic anemia; Erythrocyte; Chain code technique; Feature extraction; Cell classification;

    机译：溶血性贫血;红血球;链码技术;特征提取;细胞分类;

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