瓦瑟斯坦HOG:通过最佳运输提取当地方向性
IEEE transactions on medical imaging
|October 24, 2023
概括
这项研究引入了一种新的方法,可以从医学图像中提取强大的放射性特征,从而改善癌症结果的预测. 更高的图像方向性与更差的存活率相关,而的减少表明更好的结果.
科学领域:
- 放射学和医学成像学 医学成像学
- 计算生物学 计算生物学
- 在瘤学瘤学.
背景情况:
- 像导向梯度 (HOG) 的直方图 (Histogram of Oriented Gradients,简称HOG) 这样的方向敏感的放射性特征在癌症结局预测方面表现有前途.
- 放射性特征通常对成像变异性敏感,限制了临床适用性.
- 强大的局部定向特征提取对于可靠的定量成像生物标志物至关重要.
研究的目的:
- 开发一种强大的,无需培训的方法,从医学图像中提取局部定向特征.
- 评估这些特征在量化瘤异质性和预测不同癌症类型的结果中的有用性.
- 研究图像方向性和质母细胞瘤,头癌和肺癌患者存活率之间的相关性.
主要方法:
- 一种新的方法,使用最佳运输将图像补丁映射到异常密集的补丁,将运输地图分解为定向组件.
- 对质母细胞瘤的MRI扫描,头角状细胞癌的CT扫描以及肺癌患者的纵向CT扫描进行评估.
- 通过分析瘤区域内提取的局部定向的力来量化瘤异质性.
主要成果:
- 瘤内的更高的图像方向性与所有三个评估的癌症数据集中的更差的整体存活率显著相关.
- 在接受免疫治疗的肺癌患者中,从基线CT扫描中减少,与较长的整体存活率相关 (HR=1.95,p=1.65e-5).
- 拟议的方法证明了强度和无需培训的特征,用于量化局部图像方向性.
结论:
- 通过度量化的局部图像方向性作为瘤恶性和患者预后的潜在成像生物标志物.
- 开发的基于运输的最佳方法为提取可靠的放射性特征提供了强大而通用的工具.
- 这种方法有可能通过提供对瘤特征和治疗反应的客观测量来增强临床决策.
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