Segmentation and classification of white blood cells

Sawsan F. Bikhet, A. Darwish, Hany A. Tolba, S. Shaheen
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引用次数: 78

Abstract

Automated medical image processing and analysis offers a powerful tool for medical diagnosis. In this work we tackle the problem of white blood cell shape analysis based on the morphological characteristics of their outer contour and nuclei. The paper presents a set of preprocessing and segmentation algorithms along with a set of features that are able to recognize and classify different categories of normal white blood cells. The system was tested on gray level images obtained from a CCD camera through a microscope and produced a correct classification rate close to 91%.
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白细胞的分割和分类
自动医学图像处理和分析为医学诊断提供了有力的工具。在这项工作中,我们解决了基于白细胞外轮廓和细胞核形态特征的形状分析问题。本文提出了一套预处理和分割算法以及一套能够识别和分类不同类别的正常白细胞的特征。该系统通过显微镜对CCD相机获得的灰度图像进行了测试,正确分类率接近91%。
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