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使用非局部否定算法进行数字乳腺图莫合成剂量减少的可行性研究

Marcelo A C Vieira¹, Helder C R de Oliveira¹, Polyana F Nunes¹

¹Department of Electrical Engineering, University of São Paulo, São Carlos, SP, Brazil.

Proceedings of SPIE--the International Society for Optical Engineering

|July 25, 2025

概括

这项研究表明,denoising算法可以减少数字乳腺图像合成 (DBT) 成像中的辐射剂量. 区块匹配3D (BM3D) 算法有效地降低噪音,并在较低剂量下保持图像质量.

科学领域:

医疗成像医学成像
放射学放射学是一门学科.
图像处理图像处理

背景情况:

由于"组合模式"成像,数字乳房图莫合成 (DBT) 涉及比标准乳房造影更高的辐射剂量.
减少DBT中的辐射剂量对于患者的安全至关重要,但它会增加量子噪声并降低图像质量.

研究的目的:

评估无声化算法的有效性,以减少DBT检查中的辐射剂量.
评估是否除雾技术可以保持可接受的图像质量,尽管剂量减少.

主要方法:

研究了两种"最先进"的拒绝技术,即非本地方法 (NLM) 和区块匹配3D (BM3D).
在各种辐射剂量水平下,从乳房幻影获得了DBT预测.
确定最佳的过参数以恢复图像质量.

主要成果:

与NLM相比,BM3D表现出优异的降噪和较少的图像模糊.
BM3D实现了更好的噪声调整 (峰值信号与噪声比的平均差异<0.1dB).
BM3D导致图像模糊性较少 (图像清晰度的平均差异~6%).

结论:

消除算法,特别是BM3D,显示出在DBT中减少辐射剂量的巨大潜力.
在低剂量DBT投影中,BM3D有效地减轻噪音并保持图像质量.
这些发现支持在DBT成像中临床实施剂量降低策略.

关键词:

数字乳腺图片合成区块匹配的3D对应剂量降低剂量降低的方法图像去色化图像去色化非本地意味着非本地.

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