基于PDE的低剂量CT投影降噪研究

随着医学影像诊断技术的广泛应用,人们逐渐开始重视CT扫描中辐射剂量过高的问题,低剂量CT已成为医用CT发展的必然趋势。然而,低剂量CT重建图像质量会发生严重的退化,从而影响医疗诊断。针对以上问题,本文在各向异性扩散模型基础上,提出一种改进的4邻域偏微分投影域降噪算法。为有效地实现图像噪声快速平滑和特征保留,该模型根据相关像素控制率定义了归一权梯度函数。此外,本文根据扩散图像的特征变化规律构造了时变扩散函数,该函数能够自适应调节噪声平滑和轮廓保留之间的平衡。仿真数据和乳腺模体扫描数据结果表明,改进算法能够获得更高质量的重建图像,并具有较好的运算效率。 

Noise Reduction for Low-dose CT Sinogram Based on PDE

With the wide application of medical imaging technology, the low-dose CT has become an inevitable tendency in medical CT because of the gradual awareness of scan dose. However, the reconstruction image degradation in low-dose CT will affect the medical diagnostic accuracy. In order to solve the problem above, a 4-neighborhood partial differential equation based on anisotropic diffusion equation sinogram noise reduction is proposed. To get more effective at noise smoothing and features preserving, novel model defined a weight normalized gradient according to the control rate of relevant pixel values. Additionally, a time-varied diffusion function based on the regular rule of image feature is provided to be adaptive for the balance between noise removal and edge preservation. Numerical results and scan data of the breast model reveal that the novel method can achieve better reconstruction image quality.