在胸部CT成像中对放射学估计 (AсquIRE) 的排名获取影响:一项回顾性多站点,多用途案例研究
Dmitry Cherezov1, Vidya Sankar Viswanathan1, Pingfu Fu2
1Department of Biomedical Engineering, Emory University, Atlanta, GA, USA.
Computer methods and programs in biomedicine
|January 9, 2024
概括
像软件版本和卷积内核这样的CT采集参数显著影响放射学纹理特征. 新的AcquIRE方法有助于对这些影响进行排名,以便更好地进行医学成像分析.
科学领域:
- 医学成像分析分析 医学成像分析
- 量化数据提取量化数据提取
- 机器学习在医学中的应用
背景情况:
- 放射学从医学扫描中提取定量数据,用于疾病表型,预后和治疗反应预测.
- CT扫描仪采集参数的变化 (例如,卷积内核,像素间距) 可以改变放射学纹理特征值.
研究的目的:
- 研究CT获取参数对放射学特征的影响.
- 引入和利用一种新的方法,即获取对放射学估计的影响 (AcquIRE),用于对这些参数影响进行排名.
主要方法:
- 利用了来自九个地点的三个胸部CT成像数据集 (n=749名患者).
- 每个患者提取了744个纹理特征和9个获取参数.
- 使用AcquIRE方法开发了一种分类模型,以对放射性特征的获取参数影响进行排序.
主要成果:
- CT软件版本和卷积内核参数在数据集中显示出最大的差异.
- 在一个数据集中,Haralick纹理特征家族受到影响最小,而Gabor特征受到影响最大.
- 在其他数据集中,Gabor特征受到影响最小,这表明上下文依赖的参数影响.
结论:
- CT软件版本和卷积内核参数被确定为对放射学特征影响最大的参数.
- 获取参数对放射性特征的影响取决于具体的临床问题.
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