...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Journal of Digital Imaging >The Self-Overlap Method for Assessment of Lung Nodule Morphology in Chest CT
【24h】

The Self-Overlap Method for Assessment of Lung Nodule Morphology in Chest CT

机译：自重叠法评估胸部CT肺结节形态

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Surface morphology is an important indicator of malignant potential for solid-type lung nodules detected at CT, but is difficult to assess subjectively. Automated methods for morphology assessment have previously been described using a common measure of nodule shape, representative of the broad class of existing methods, termed area-to-perimeter-length ratio (APR). APR is static and thus highly susceptible to alterations by random noise and artifacts in image acquisition. We introduce and analyze the self-overlap (SO) method as a dynamic automated morphology detection scheme. SO measures the degree of change of nodule masks upon Gaussian blurring. We hypothesized that this new metric would afford equally high accuracy and superior precision than APR. Application of the two methods to a set of 119 patient lung nodules and a set of simulation nodules showed our approach to be slightly more accurate and on the order of ten times as precise, respectively. The dynamic quality of this new automated metric renders it less sensitive to image noise and artifacts than APR, and as such, SO is a potentially useful measure of cancer risk for solid-type lung nodules detected on CT.
机译：表面形态是在CT上检测到的实性肺结节恶性潜能的重要指标，但很难主观评估。先前已经使用一种常见的结节形状测量方法来描述形态学评估的自动化方法，这种方法代表了广泛的现有方法，称为面积与周长比（APR）。 APR是静态的，因此在图像采集中极易受到随机噪声和伪影的影响。我们介绍并分析了自重叠（SO）方法作为动态的自动形态学检测方案。 SO测量高斯模糊时根瘤掩模的变化程度。我们假设该新指标将提供与APR相同的准确性和优越的精度。将这两种方法应用于一组119个患者肺结节和一组模拟结节表明，我们的方法分别稍微更精确，并且精确度大约是其十倍。这种新的自动化指标的动态质量使其对图像噪声和伪像的敏感性不及APR，因此，SO是对CT上检测到的实性肺结节患癌风险的潜在有用度量。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号