2019/05/31 by Yifeng Fan, Tingran Gao, Fan, Yifeng +3 · 1 citation
Biochemistry, Genetics and Molecular Biology · Engineering · Physics and Astronomy · #20G05 #33C45 #33C55 #55R25 #Advanced Electron Microscopy Techniques and Applications #Characterization and Applications of Magnetic Nanoparticles #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #FOS: Electrical engineering #FOS: Mathematics #Force Microscopy Techniques and Applications #Functional Analysis (math.FA) #I.4.10 #I.4.5 #Image and Video Processing (eess.IV) #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.1906.01082
openalex publication_date 2019/05/31 · openalex created_date 2019/06/14 · openalex updated_date 2026/07/28
We develop in this paper a novel intrinsic classification algorithm -- multi-frequency class averaging (MFCA) -- for classifying noisy projection images obtained from three-dimensional cryo-electron microscopy (cryo-EM) by the similarity among their viewing directions. This new algorithm leverages multiple irreducible representations of the unitary group to introduce additional redundancy into the representation of the optimal in-plane rotational alignment, extending and outperforming the existing class averaging algorithm that uses only a single representation. The formal algebraic model and representation theoretic patterns of the proposed MFCA algorithm extend the framework of Hadani and Singer to arbitrary irreducible representations of the unitary group. We conceptually establish the consistency and stability of MFCA by inspecting the spectral properties of a generalized local parallel transport operator through the lens of Wigner D-matrices. We demonstrate the efficacy of the proposed algorithm with numerical experiments.