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Study of Automatic Enhancement for Chest Radiograph

机译：胸部X光片自动增强的研究

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摘要

Because of the large difference of the densities in the lung and other structures, the chest x-ray image behaves as a wide-range intensity distribution, which brings on a bit of difficulty to investigate the focus. In the paper, according to the intensity properties of the chest radiograph, the chest radiographic image is divided into three subregions, and a piecewise linear transformation model is established. An approach of automatic enhancement is presented, based on the gray-level normalization. The average enhanced ratios of three subregions of the normal and severe acute respiratory syndrome image are increased by 10.70% and 25.55%, respectively. The technique is proved to be effective through the evaluation of the improved images.
机译：由于肺部和其他结构的密度差异很大，因此胸部X射线图像表现为宽范围的强度分布，这给研究焦点带来了一些困难。本文根据胸部X线照片的强度特性，将胸部X线照片分为三个子区域，建立了分段线性变换模型。提出了一种基于灰度归一化的自动增强方法。正常和严重急性呼吸综合征的三个子区域的平均增强率分别增加了10.70％和25.55％。通过评估改进的图像，证明该技术是有效的。

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  • 来源
    《Journal of Digital Imaging》 |2006年第4期|371-375|共5页
  • 作者

    Chen Shuyue; Hou Honghua; Zeng Yanjun Ph.D.; Xu Xiaomin;

  • 作者单位

    The Key Laboratory of the State Education Ministry on Instrumentation Science and Dynamic Measurement North University of China Taiyuan 030051 People’s Republic of China;

    The Key Laboratory of the State Education Ministry on Instrumentation Science and Dynamic Measurement North University of China Taiyuan 030051 People’s Republic of China;

    Biomedical Engineering Center Beijing University of Technology Beijing 100022 People’s Republic of China;

    Children Hospital of Shanxi Province Taiyuan 030013 People’s Republic of China;

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  • 原文格式 PDF
  • 正文语种 eng
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  • 关键词

    Medical image processing; image enhancement; chest radiograph; SARS;

    机译：医学图像处理;图像增强;胸片;SARS;

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