Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, and Key Laboratory of System Control and Information Processing, Ministry of Education of China, Shanghai 200240, China.
Department of Computer Science, Shanghai Jiao Tong University, Shanghai 200240, China.
J Chem Inf Model. 2021 Sep 27;61(9):4795-4806. doi: 10.1021/acs.jcim.1c00745. Epub 2021 Sep 15.
Cryo-electron microscopy (cryo-EM) single-particle image analysis is a powerful technique to resolve structures of biomacromolecules, while the challenge is that the cryo-EM image is of a low signal-to-noise ratio. For both two-dimensional image analysis and three-dimensional density map analysis, image alignment is an important step to improve the precision of the image distance calculation. In this paper, we introduce a new algorithm for performing two-dimensional pairwise alignment for cryo-EM particle images, which is based on the Fourier transform and power spectrum analysis. Compared to the existing heuristic iterative alignment methods, our method utilizes the signal distribution and signal feature on images' power spectrum to directly compute the alignment parameters. It does not require iterative computations and is robust against the cryo-EM image noise. Both theoretical analysis and experimental results suggest that our power-spectrum-feature-based alignment method is highly computational-efficient and is capable of offering effective alignment results. This new alignment algorithm is publicly available at: www.csbio.sjtu.edu.cn/bioinf/EMAF/for academic use.
冷冻电子显微镜（cryo-EM）单颗粒图像分析是解析生物大分子结构的强大技术，但其挑战在于 cryo-EM 图像的信噪比低。对于二维图像分析和三维密度图分析，图像配准是提高图像距离计算精度的重要步骤。在本文中，我们引入了一种新的 cryo-EM 粒子图像二维对对准算法，该算法基于傅里叶变换和功率谱分析。与现有的启发式迭代对准方法相比，我们的方法利用图像功率谱上的信号分布和信号特征直接计算对准参数。它不需要迭代计算，并且对 cryo-EM 图像噪声具有鲁棒性。理论分析和实验结果表明，我们基于功率谱特征的对准方法具有很高的计算效率，并且能够提供有效的对准结果。此新的对准算法可在：www.csbio.sjtu.edu.cn/bioinf/EMAF/ 上公开获取，供学术使用。
