IEEE Trans Med Imaging. 2016 Jun;35(6):1565-74. doi: 10.1109/TMI.2016.2520092. Epub 2016 Jan 21.
In the past 20 years, a wide range of complex fluoroscopically guided procedures have shown considerable growth. Biologic effects of the exposure (radiation induced burn, cancer) lead to reduce the dose during the intervention, for the safety of patients and medical staff. However, when the dose is reduced, image quality decreases, with a high level of noise and a very low contrast. Efficient restoration and denoising algorithms should overcome this drawback. We propose a spatio-temporal filter operating in a multi-scales space. This filter relies on a first order, motion compensated, recursive temporal denoising. Temporal high frequency content is first detected and then matched over time to allow for a strong denoising in the temporal axis. We study this filter in the curvelet domain and in the dual-tree complex wavelet domain, and compare those results to state of the art methods. Quantitative and qualitative analysis on both synthetic and real fluoroscopic sequences demonstrate that the proposed filter allows a great dose reduction.
在过去的 20 年中，广泛的复杂荧光镜引导程序显示出相当大的增长。辐射暴露的生物效应（辐射灼伤、癌症）导致介入期间的剂量减少，以确保患者和医务人员的安全。然而，当剂量减少时，图像质量会下降，噪声水平很高，对比度非常低。高效的恢复和降噪算法应该克服这一缺点。我们提出了一种在多尺度空间中工作的时空滤波器。该滤波器依赖于一阶、运动补偿、递归时间降噪。首先检测时间高频内容，然后随时间匹配，以便在时间轴上进行强降噪。我们在curvelet 域和双树复小波域中研究了这种滤波器，并将结果与最先进的方法进行了比较。对合成和真实荧光序列的定量和定性分析表明，所提出的滤波器允许大幅减少剂量。
