Retrieving the parameters of cryo Electron Microscopy dataset in the heterogeneous ab-initio case
Estimation de paramètres pour la reconstruction tomographique d'objets déformable en cryo-microscopie électronique à particules isolées
Résumé
A cryo Electron Microscopy dataset is composed on tomo-graphic projections of an object (e.g. a macromolecule). The projection orientation information is unknown. The scope of this paper is the projection parameterization in the case of a deformable object. An overview of the parametrization methods is presented. Then a new approach based on manifold learning is detailed. Finally, an evaluation method for each substep of the parameterization is proposed. The resulting evaluation of the different methods on a 2D synthetic database shows the efficiency of our approach.
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