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噪音和斑点抑制方法用于放射治疗输送的累积切伦科夫图像

Jeremy E Hallett¹, Petr Bruza^2,3, Michael Jermyn^2,3

¹Department of Medical Physics, University of Wisconsin-Madison, Madison, WI, United States of America.

Physics in medicine and biology

|October 30, 2024

概括

在放射治疗的切伦科夫成像中,降低噪音至关重要. 非局部手段 (NLM) 和双边过有效提高处理验证的图像质量.

科学领域:

医学物理医学物理
放射治疗成像技术的成像技术
图像处理图像处理

背景情况:

切伦科夫成像可以实时可视化放射治疗束的传递.
切伦科夫图像中的高噪音水平限制了它们在事件检测和处理验证方面的实用性.
图像后处理对于抑制噪音和提高图像质量至关重要.

研究的目的:

评估和比较各种图像后处理算法在切伦科夫成像中的降噪效果.
确定在放射治疗期间获得的切伦科夫图像中抑制噪声和斑点的最佳算法.

主要方法:

应用了几种降噪算法:总变化最小化 (TV-L1),非局部平均值 (NLM),区块匹配3D (BM3D),阿尔法修剪平均值 (ATM) 和双边过.
在使用BeamSite摄像头和TrueBeam linac.从幽灵中获得的切伦科夫图像上测试了算法.
根据峰值信号与噪声比率 (PSNR),噪声功率频谱 (NPS) 和图像清晰度评估无色图像.

主要成果:

NLM和双边过实现了最高的PSNR平均增长 (分别为19.1%和19.0%).
电视-L1也显示了显著的改善 (17.4%的PSNR增长).
NLM和双边过器提供了优越的边缘度和较低的NPS.

结论:

非局部手段 (NLM) 和双边过是消除累积的切伦科夫图像数据的最佳方法.
对于累积图像,TV-L1提供了可比的结果.
单个视频切伦科夫图像需要不同的,可能与ML集成的,由于噪声水平较高的噪声抑制策略.

关键词:

切伦科夫 (Cherenkov) 是一个通过适应性修剪的平均值.这是一个双边的双边关系.区块匹配对应的区块匹配拒绝的意思是拒绝.非本地意味着非本地.总变化的总变化.

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