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Fast Cryo-EM Image Alignment Algorithm Using Power Spectrum Features.
Chen, Yu-Xuan; Xie, Rui; Yang, Yang; He, Lin; Feng, Dagan; Shen, Hong-Bin.
Afiliación
  • Chen YX; 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.
  • Xie R; 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.
  • Yang Y; Department of Computer Science, Shanghai Jiao Tong University, Shanghai 200240, China.
  • He L; Instrumental Analysis Center, Shanghai Jiao Tong University, Shanghai 200240, China.
  • Feng D; School of Computer Science, University of Sydney, Sydney 2006, Australia.
  • Shen HB; 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.
J Chem Inf Model ; 61(9): 4795-4806, 2021 09 27.
Article en En | MEDLINE | ID: mdl-34523929
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.
Asunto(s)

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Algoritmos / Procesamiento de Imagen Asistido por Computador Tipo de estudio: Prognostic_studies Idioma: En Revista: J Chem Inf Model Asunto de la revista: INFORMATICA MEDICA / QUIMICA Año: 2021 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Algoritmos / Procesamiento de Imagen Asistido por Computador Tipo de estudio: Prognostic_studies Idioma: En Revista: J Chem Inf Model Asunto de la revista: INFORMATICA MEDICA / QUIMICA Año: 2021 Tipo del documento: Article País de afiliación: China