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The use of conspicuous visible features in medical images for objective assessment of image quality.

机译：在医学图像中使用明显的可见特征进行图像质量的客观评估。

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摘要

We developed and assessed the usefulness of an objective image quality measure that is correlated with perceived image quality, as a function of the most conspicuous features contained within an image. Our salience measure is useful for identifying image features that are particularly conspicuous across a range of spatial scales. This new measure was applied to medical images; salience features within mammograms were exclusively studied.;The notion of feature salience was thoroughly investigated. We developed a scale-based salience model to assess low-level visual features that are contained in digitized mammograms. We found these features to be correlated with observer performance during detection and discrimination tasks. Two studies were performed that correlated the salience measure with task-dependent observer performance. In the first study, we used eye-position data to develop a model that relates the salience measure to the time required to fixate a mass. The model is useful for predicting time-to-first-hit in less than two seconds, but can only be applied to trained readers. In the second study, we found that the salience measure was useful for discrimination of true positive, true negative and false positive cases across different levels of reader experience.;Using feature salience, we developed a quantitative measure of breast density as a percentage of the whole breast. Our measure is semi-automatic and shows good correlation with the adaptive thresholding technique. Adaptive thresholding is a popular percentage breast density measurement; however, more reader interaction is required than is needed for our technique.;We developed a new method for quantifying case difficulty for use in the training and testing of CAD algorithms using a small number of cases. Using a large data set, we clustered cases into groups of perceived difficulty as quantified by our salience measure. We showed that test subsets can be objectively constructed and related to reader perception of case difficulty.
机译：我们根据图像中包含的最明显特征，开发并评估了与感知图像质量相关的客观图像质量度量的实用性。我们的显着性度量对于识别在一系列空间尺度上特别显着的图像特征很有用。这项新措施已应用于医学图像；专门研究了乳房X线照片中的显着特征。彻底研究了特征显着性的概念。我们开发了基于比例的显着性模型，以评估数字化乳腺X线照片中包含的低级视觉特征。我们发现这些功能与检测和辨别任务期间的观察者表现相关。进行了两项研究，这些研究将显着性测度与任务依赖的观察者绩效相关联。在第一个研究中，我们使用眼位数据开发了一个模型，该模型将显着性度量与固定质量所需的时间相关联。该模型可用于预测不到两秒钟的首次点击时间，但只能应用于受过训练的读者。在第二项研究中，我们发现显着性度量可用于在不同水平的读者体验中区分真实阳性，真实阴性和假阳性案例。;使用特征显着性，我们开发了定量的乳腺密度测量值（占百分比）整个乳房。我们的测量是半自动的，并且显示与自适应阈值技术的良好相关性。自适应阈值是流行的百分比的乳房密度测量。然而，与我们的技术相比，需要更多的读者交互作用。；我们开发了一种量化案例难度的新方法，可用于少量案例的CAD算法的训练和测试。使用大型数据集，我们将案例聚类为可感知的难度组，通过显着性度量对其进行了量化。我们表明，测试子集可以客观构建，并与读者对案例难易程度的感知有关。

著录项

  • 作者

    Perconti, Philip.;

  • 作者单位

    The George Washington University.;

  • 授予单位 The George Washington University.;
  • 学科 Engineering Biomedical.;Health Sciences Radiology.;Biophysics Medical.
  • 学位 Ph.D.
  • 年度 2006
  • 页码 193 p.
  • 总页数 193
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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